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Background: Most breast cancers are detected at an early stage in which case conservative surgery is indicated. An accurate preoperative localization technique is essential for conservative surgery of non-palpable breast lesions. Currently, the gold standard technique is wire localization (WL). However, this technique has well-known drawbacks. Several wire-free techniques have been developed to overcome these drawbacks; one technique is localisation by Radiofrequency Identification (RFID). The purpose of this clinical trial was to assess the superiority of RFID tags (HOLOGIC) in terms of patient satisfaction, over wire localization of non-palpable breast lesions., Methods: This was a single-centre, prospective, controlled and non-interventional trial. Patients were followed from their inclusion at the time of the preoperative consultation to the postoperative consultation, one month after surgery. Data on anxiety and satisfaction was collected from patients and clinicians using questionnaires, and clinical data was collected from the medical files. The primary outcome was the patients' satisfaction scores, assessed using a visual analogue scale., Results: Eighty patients were sequentially enrolled in two groups: the wire group (n = 40) and the RFID group (n = 40). One patient from the RFID group was excluded from the analysis because of a substantial migration during deployment. On a 10-point Visual Analogue Scale, the patients' median satisfaction score was 9.8 (IQR = 1.32) for the wire group and 10 (IQR = 0.07) for the RFID group (p < 0.001). A reduction in pain between device insertion and surgery was observed in the RFID group (p = 0.009). The median placement time was shorter in the RFID group (15 min, IQR = 6) than in the wire group (20 min, IQR = 30) (p = 0.01)., Conclusion: Our results show a statistically significant difference in median patient satisfaction score with the localization of non-palpable breast cancer lesions using RFID tags compared to the use of the WL. Although our results did not show clinically significant outcomes in terms of satisfaction, RFID tags are a reliable alternative to WL and simplify the organization of patients' healthcare trajectories., Trial Registration: ClinicalTrials.gov ID; NCT04750889 registered on February 11, 2021. https://clinicaltrials.gov/ct2/show/NCT04750889?term=rfid&draw=2&rank=1., Competing Interests: Declarations. Ethics approval and consent to participate: The RFID trial was approved by the ethics committee (Ile de France XI) (ID-RCB number: 2021-A00281-40). Patients who agreed to participate in this study provided oral consent for enrolment and the investigator signed a document stating that the patient had been informed and had agreed to participate. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

In recent years, Lip-reading has emerged as a significant research challenge. The aim is to recognise speech by analysing Lip movements. The majority of Lip-reading technologies are based on cameras and wearable devices. However, these technologies have well-known occlusion and ambient lighting limitations, privacy concerns as well as wearable device discomfort for subjects and disturb their daily routines. Furthermore, in the era of coronavirus (COVID-19), where face masks are the norm, vision-based and wearable-based technologies for hearing aids are ineffective. To address the fundamental limitations of camera-based and wearable-based systems, this paper proposes a Radio Frequency Identification (RFID)-based smart mask for a Lip-reading framework capable of reading Lips under face masks, enabling effective speech recognition and fostering conversational accessibility for individuals with hearing impairment. The system uses RFID technology to make Radio Frequency (RF) sensing-based Lip-reading possible. A smart RFID face mask is used to collect a dataset containing three different classes of vowels (A, E, I, O, U), Consonants (F, G, M, S), and words (Fish, Goat, Meal, Moon, Snake). The collected data are fed into well-known machine-learning models for classification. A high classification accuracy is achieved by individual classes and combined datasets. On the RFID combined dataset, the Random Forest model achieves a high classification accuracy of 80%., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Introduction: To improve patient safety and reduce burden on healthcare professionals and institutions, the individual management of surgical instruments is essential. There are two methods for individual item management: radio-frequency identification (RFID) and barcoding. However, there has been no examination of efficiency regarding reading times. Therefore, this study aimed to compare the reading times of RFID-tagged and barcode-engraved surgical instruments and evaluate the influence of operator proficiency., Methods: The participants included 8 individuals and 41 surgical instruments from a varicose vein set. RFID tags and barcodes were attached to the surgical instruments. Five trials were conducted for each, and the reading times were measured., Results: The reading times for RFID-tagged surgical instruments in the skilled and unskilled groups were 64.0 ± 9.0s and 79.4 ± 17.0 s, respectively, whereas those for barcode-engraved surgical instruments were 190.4 ± 28.1 s and 212.3 ± 40.3 s, respectively. Barcodes took 3.0 and 2.7 times longer to read than RFID-tagged instruments for the skilled and unskilled groups, respectively. Additionally, skilled operators using barcodes required 2.4 times more time than unskilled operators using RFID. Even nonmedical individuals were able to achieve quick and accurate readings with RFID. The estimated labor hours per person were $24,146-$42,322 for RFID and $71,078-$110,898 for barcode scanning for a year (working 8 h/d for 250 d)., Conclusions: RFID-tagged surgical instruments impose a lighter workload and financial burden than barcode-engraved surgical instruments. RFID technology may also improve patient safety due to less dependency on operator proficiency., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Current approaches to activity-assisted living (AAL) are complex, expensive, and intrusive, which reduces their practicality and end user acceptance. However, emerging technologies such as artificial intelligence and wireless communications offer new opportunities to enhance AAL systems. These improvements could potentially lower healthcare costs and reduce hospitalisations by enabling more effective identification, monitoring, and localisation of hazardous activities, ensuring rapid response to emergencies. In response to these challenges, this paper introduces the Transparent RFID Tag Wall (TRT-Wall), a novel system taht utilises a passive ultra-high frequency (UHF) radio-frequency identification (RFID) tag array combined with deep learning for contactless human activity monitoring. The TRT-Wall is tested on five distinct activities: sitting, standing, walking (in both directions), and no-activity. Experimental results demonstrate that the TRT-Wall distinguishes these activities with an impressive average accuracy of 95.6 % under four distinct distances (2, 2.5, 3.5 and 4.5 m) by capturing the RSSI and phase information. This suggests that our proposed contactless AAL system possesses significant potential to enhance elderly patient-assisted living., (© 2024. The Author(s).)

Background: The use of sublobar resection has increased with advances in imaging technologies. However, it is difficult for thoracic surgeons to identify small lung tumours intraoperatively. Radiofrequency identification (RFID) lung-marking systems are useful for overcoming this difficulty; however, accurate placement is essential for maximum effectiveness., Methods: We retrospectively reviewed patients who underwent RFID tag placement via fluoroscopic bronchoscopy under virtual bronchoscopic navigation (VBN) guidance before our institution's sublobar resection of lung lesions. Thirty-one patients with 31 lung lesions underwent RFID lung-marking with fluoroscopic bronchoscopy under VBN guidance., Results: Of the 31 procedures, 26 tags were placed within 10 mm of the target site, 2 were placed more than 10 mm away from the target site, and 3 were placed in a different area from the target bronchus. No clinical complications were associated with RFID tag placement, such as pneumothorax or bleeding. The contribution of the RFID lung-marking system to surgery was high, particularly when the RFID tag was placed at the target site and tumour was located in the intermediate hilar zone., Conclusions: An RFID tag can be placed near the target site using fluoroscopic bronchoscopy in combination with VBN guidance. RFID tag placement under fluoroscopic bronchoscopy with VBN guidance is useful for certain segmentectomies., (© 2024. The Author(s).)

This paper proposes a novel multi-band textile monopole antenna for patient tracking applications. The designed antenna has compact footprints (0.13 λ 0 2 ) and works in the narrow band-internet of things (NB-IoT) 1.8 GHz, radio frequency identification (RFID), and industrial, scientific, and medical (ISM) 2.45 GHz and 5.8 GHz bands. The impedance bandwidths and gain of the antenna at 1.8 GHz, 2.45 GHz, and 5.8 GHz are 310 MHz, 960 MHz, and 1140 MHz; 3.7 dBi, 5.3 dBi, and 9.6 dBi, respectively. Also, the antenna's behavior is checked on different body parts of the human body in various bending scenarios. As per the evaluated link budget, the designed antenna can easily communicate up to 100 m of distance. The specific absorption rate values of the designed antenna are also within acceptable limits as per the (FCC/ICNIRP) standards at the reported frequency bands. Unlike traditional rigid antennas, the proposed textile antenna is non-intrusive, enhancing user safety and comfort. The denim material makes it comfortable for extended wear, reducing the risk of skin irritation. It can also withstand regular wear and tear, including stretching and bending. The presented denim-based antenna can be seamlessly integrated into clothing and accessories, making it less obtrusive and more aesthetically pleasing.

Background: Dual-person inspection in IVF laboratories cannot fully avoid mix-ups or embryo transfer errors, and data transcription or entry is time-consuming and redundant, often leading to delays in completing medical records., Methods: This study introduced a workflow-based RFID tag witnessing and real-time information entry platform for addressing these challenges. To assess its potential in reducing mix-ups, we conducted a simulation experiment in semen preparation to analyze its error correction rate. Additionally, we evaluated its impact on work efficiency, specifically in operation and data entry. Furthermore, we compared the cycle costs between paper labels and RFID tags. Finally, we retrospectively analyzed clinical outcomes of 20,424 oocyte retrieval cycles and 15,785 frozen embryo transfer cycles, which were divided into paper label and RFID tag groups., Results: The study revealed that comparing to paper labels, RFID tag witnessing corrected 100% of tag errors, didn't affect gamete/embryo operations, and notably shorten the time of entering data, but the cycle cost of RFID tags was significantly higher. However, no significant differences were observed in fertilization, embryo quality, blastocyst rates, clinical pregnancy, and live birth rates between two groups., Conclusions: RFID tag witnessing doesn't negatively impact gamete/embryo operation, embryo quality and pregnancy outcomes, but it potentially reduces the risk of mix-ups or errors. Despite highly increased cost, integrating RFID tag witnessing with real-time information entry can remarkably decrease the data entry time, substantially improving the work efficiency. This workflow-based management platform also enhances operational safety, ensures medical informational integrity, and boosts embryologist's confidence., (© 2024. The Author(s).)

Background: People with blindness and intellectual disability can have problems locating, identifying, and retrieving objects needed for daily activities (e.g., clothes and food items) from familiar storage contexts, such as cupboards and cabinets., Objective: This preliminary study assessed a technological system designed to help three people with those problems improve their performance., Methods: The technological system, which involved the use of tags with radio frequency identification codes, a smartphone, and a tag reader, aimed to guide the participants in searching and retrieving objects from three different storage units. In practice, the system provided different feedbacks depending on whether the participants were searching (a) in a wrong storage unit, (b) in a wrong shelf/drawer of the right storage unit, or (c) in the right shelf/drawer of the right storage unit., Results: All participants were successful in retrieving objects correctly with the technological system. The results also showed that (a) the participants preferred using the system over a control strategy, (b) were able to switch on and off the system independently, and (b) staff rated the system positively., Conclusions: These preliminary findings suggest that the system might be a useful support tool for people with blindness and intellectual disability.

Background: Many methods have been developed for localizing non-palpable breast lesions. This study investigated the success rate and surgical results of the magnetic seed (Magseed) and radiofrequency identification (RFID) method, which are relatively new compared to standard wire-guided localizations., Materials and Methods: 20 simulation (10 Magseed, 10 RFID) models were created using turkey breasts and raisins. Raisins containing magnetic seed and RFID tags were placed on the turkey breast. Sentimag® probe was used for the Magseed group, and Faxitron LOCalizer™ System device was used in the RFID group. Both methods were evaluated in terms of accuracy in detecting breast lesion localization, operation times, excised tissue weights, total resection volume, surgical margin negativity, and re-excision rates., Results: Lesion localization success in both techniques was 100%. While procedure times were statistically significantly shorter in the Magseed group, incision lengths were shorter in the RFID group (P = 0.013, P = 0.007, respectively). No statistically significant difference was found between the groups for the weight of the removed parts, total resection volume, and surgical margin distance (P > 0.05)., Conclusion: In this feasibility study, it was concluded that neither the RFID nor Magseed methods had a significant advantage over each other, in terms of localization detection and surgical margin negativity, and both methods could be used successfully for localization., (Copyright © 2024 Copyright: © 2024 Journal of Cancer Research and Therapeutics.)

Access to brushes allows for natural scratching behaviors in cattle, especially in confined indoor settings. Cattle are motivated to use brushes, but brush use varies with multiple factors including social hierarchy and health. Brush use might serve an indicator of cow health or welfare, but practical application of these measures requires accurate and automated monitoring tools. This study describes a machine learning approach to monitor brush use by dairy cattle. We aimed to capture the daily brush use by integrating data on the rotation of a mechanical brush with data on cow identify derived from either 1) low-frequency radio frequency identification or 2) a computer vision system using fiducial markers. We found that the computer vision system outperformed the RFID system in accuracy, and that the machine learning algorithms enhanced the precision of the brush use estimates. This study presents the first description of a fiducial marker-based computer vision system for monitoring individual cattle behavior in a group setting; this approach could be applied to develop automated measures of other behaviors with the potential to better assess welfare and improve the care for farm animals., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sadrzadeh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

To provide diverse in-home services like elderly care, versatile activity recognition technology is essential. Radio-based methods, including WiFi CSI, RFID, and backscatter communication, are preferred due to their minimal privacy intrusion, reduced physical burden, and low maintenance costs. However, these methods face challenges, including environmental dependence, proximity limitations between the device and the user, and untested accuracy amidst various radio obstacles such as furniture, appliances, walls, and other radio waves. In this paper, we propose a frequency-shift backscatter tag-based in-home activity recognition method and test its feasibility in a near-real residential setting. Consisting of simple components such as antennas and switches, these tags facilitate ultra-low power consumption and demonstrate robustness against environmental noise because a context corresponding to a tag can be obtained by only observing frequency shifts. We implemented a sensing system consisting of SD-WiFi, a software-defined WiFi AP, and physical switches on backscatter tags tailored for detecting the movements of daily objects. Our experiments demonstrate that frequency shifts by tags can be detected within a 2 m range with 72% accuracy under the line of sight (LoS) conditions and achieve a 96.0% accuracy (F-score) in recognizing seven typical daily living activities with an appropriate receiver/transmitter layout. Furthermore, in an additional experiment, we confirmed that increasing the number of overlaying packets enables frequency shift-detection even without LoS at distances of 3-5 m.

Background: As advancements in surgical instruments and techniques continue to evolve, minimally invasive surgery has become increasingly preferred as a means of reducing patient pain and recovery time. However, one major challenge in performing minimally invasive surgery for early gastrointestinal cancer is accurately identifying the location of the lesion. This is particularly difficult when the lesion is confined to the lumen of the intestine and cannot be visually confirmed from the outside during surgery. In such cases, surgeons must rely on CT or endoscopic imaging to locate the lesion. However, if the lesion is difficult to identify with these images or if the surgeon has less experience, it can be challenging to determine its precise location. This can result in an excessive resection margin, deviating from the goal of minimally invasive surgery. To address this challenge, researchers have been studying the development of a marker for identifying the lesion using a radio-frequency identification (RFID) system. One proposed method for clinical application of this detection system is to attach an RFID tag to an endoscopic hemostatic clip and fix it to the intended position, providing a stable marker for the inner wall of the organ. This approach has the potential to improve the accuracy and effectiveness of minimally invasive surgery for early gastrointestinal cancer., Methods: In the development of a marker for identifying gastrointestinal lesions using a radio-frequency identification (RFID) system, the shape of the clip and suitable materials for attaching the RFID tag were determined through finite element method (FEM) analysis. A prototype of the clip was then fabricated and ex-vivo experiments were conducted using porcine intestine to evaluate the stability of the clip in relation to its position. To further evaluate the performance of the RFID-integrated clip in vivo, the clip was placed in the gastric wall of the stomach of anesthetized porcine using an endoscopic instrument. The clip was then detected using a RFID detector designed for laparoscopic approach. And later, the accuracy of detection was confirmed by incising the lesion., Results: The design and fabrication of a clip with varying thicknesses using STS316 and STS304 stainless steel were accomplished using the results of finite element method analysis. The stability of the clip was evaluated through ex-vivo experiments, showing it to be a viable option. In-vivo experiments were performed on anesthetized porcine, in which the RFID-integrated clip was placed in the gastric wall and detected using a custom-made RFID detector. The resection margin, measured at about 30 mm from the detector position, was accomplished with low error. These findings indicate the feasibility and efficacy of using an RFID-integrated clip as a marker in minimally invasive surgery for the identification of gastrointestinal lesions., Conclusions: The study evaluated the feasibility of using stainless steel clips for lesion detection in endoscopic surgery using computer-aided engineering analysis and ex-vivo experimentation. Results showed that STS304 was suitable for use while STS316L was not. The ex-vivo experiments revealed that the clip holding force and tissue retention length varied depending on the location of attachment. In-vivo experiments confirmed the accuracy and usefulness of the RFID lesion detection system. However, challenges remain for its use in clinical field, such as ensuring the stability of the clip and the safe attachment of the RFID tag, which requires further research for commercialization., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Joo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background and Objectives: Currently, blood allocation is solely done by scanning barcode labels for each bag of blood, with low efficiency. However, the rapid allocation of emergency blood is required owing to the rapid increase in blood consumption during unconventional emergencies. This study aimed to design and apply radiofrequency identification (RFID) technology for the rapid allocation of blood in batches with advantages in time, efficiency and accuracy., Materials and Methods: A blood emergency allocation system based on RFID technology was designed using a multi-label anti-collision algorithm and tested with automatic information check, a comparative study of scanning speed and accuracy, data analysis and other methods., Results: The optimal packing quantities of suspended red blood cells and fresh frozen plasma were 40 and 50 bags per box, respectively. The application of rapid batch allocation of blood using RFID technology was performed, and the data sent and received by RFID scanning and barcode scanning were compared., Conclusion: The designed RFID blood emergency allocation system could effectively achieve the rapid and batch allocation of emergency blood and has the advantages of stability, efficiency and accuracy in blood emergency allocation and management., (© 2023 International Society of Blood Transfusion.)

Passive radio frequency identification (RFID) can advance poultry behavior research by enabling automated, individualized, longitudinal, in situ, and noninvasive monitoring; these features can usefully extend traditional approaches to animal behavior monitoring. Furthermore, since the technology can provide insight into the visiting patterns of tagged animals at functional resources (e.g., feeders), it can be used to investigate individuals' welfare, social position, and decision-making. However, the lack of guidelines that would facilitate implementing an RFID system for such investigations, describing it, and establishing its validity undermines this technology's potential for advancing poultry science. This paper aims to fill this gap by 1) providing a nontechnical overview of how RFID functions; 2) providing an overview of the practical applications of RFID technology in poultry sciences; 3) suggesting a roadmap for implementing an RFID system in poultry behavior research; 4) reviewing how validation studies of RFID systems have been done in farm animal behavior research, with a focus on terminologies and procedures for quantifying reliability and validity; and 5) suggesting a way to report on an RFID system deployed for animal behavior monitoring. This guideline is aimed mainly at animal scientists, RFID component manufacturers, and system integrators who wish to deploy RFID system as an automated tool for monitoring poultry behavior for research purposes. For such a particular application, it can complement indications in classic general standards (e.g., ISO/IEC 18000-63) and provide ideas for setting up, testing, and validating an RFID system and a standard for reporting on its adequacy and technical aspects., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death in women. Approximately 50% of breast cancers are discovered at an early stage in patients for whom conservative surgery is indicated. Intraoperative localization of non-palpable breast lesions is generally accomplished using a hook wire to mark the area of concern under ultrasound or stereotactic localization. But this technique has several drawbacks (painful, stressful…). We propose the use of a wire-free breast lesion system using miniature radiofrequency identification (RFID) tags. This technique could improve patient comfort and surgical comfort for surgeons. We therefore propose a study to assess the interest of introducing the RFID localization technique at the Jean PERRIN comprehensive cancer center., Methods: This is a single-center prospective trial designed to assess the interest in introducing the RFID localization technique at the Jean Perrin center. It aims to show the superiority of the RFID technique in terms of patient tolerance compared to the gold-standard (hook wire). A sequential inclusion in time will be performed: 20 inclusions in the gold-standard group, then 20 patients in the RFID group before repeating the inclusion scheme. Any patient requiring preoperative localization will receive a senology consultation. The RFID tag will be placed during this consultation. The hook wire localization will be done the day before the surgery. Patients will fill out a Hospital Anxiety and Depression scale (HAD) questionnaire at the time of inclusion. They will then fill out a satisfaction questionnaire in 2 steps: during the placement of the device (RFID tag or hook wire) or during the postoperative consultation at 1 month. Radiologists and surgeons will fill out a questionnaire to evaluate the localization technique, respectively after the localization and surgery procedures., Discussion: The RFID study is the first study in France which specifically assesses the interest of the RFID localization in terms of patients comfort. Patient comfort is one of the key elements to take into consideration when managing patients in oncology and new technologies such as RFID tags could improve it., Trial Registration: ClinicalTrials.gov ID; NCT04750889 registered on February 11, 2021., (© 2023. The Author(s).)

Exploiting Radio Frequency Identification (RFID) technology in healthcare systems has become a common practice, as it ensures better patient care and safety. However, these systems are prone to security vulnerabilities that can jeopardize patient privacy and the secure management of patient credentials. This paper aims to advance state-of-the-art approaches by developing more secure and private RFID-based healthcare systems. More specifically, we propose a lightweight RFID protocol that safeguards patients' privacy in the Internet of Healthcare Things (IoHT) domain by utilizing pseudonyms instead of real IDs, thereby ensuring secure communication between tags and readers. The proposed protocol has undergone rigorous testing and has been proven to be secure against various security attacks. This article provides a comprehensive overview of how RFID technology is used in healthcare systems and benchmarks the challenges faced by these systems. Then, it reviews the existing RFID authentication protocols proposed for IoT-based healthcare systems in terms of their strengths, challenges, and limitations. To overcome the limitations of existing approaches, we proposed a protocol that addresses the anonymity and traceability issues in existing schemes. Furthermore, we demonstrated that our proposed protocol had a lower computational cost than existing protocols and ensured better security. Finally, our proposed lightweight RFID protocol ensured strong security against known attacks and protected patient privacy using pseudonyms instead of real IDs.

This paper is focused on the use of radio frequency identification (RFID) technology operating at 125 kHz in a communication layer for a network of mobile and static nodes in marine environments, with a specific focus on the Underwater Internet of Things (UIoT). The analysis is divided into two main sections: characterizing the penetration depth at different frequencies and evaluating the probabilities of data reception between antennas of static nodes and a terrestrial antenna considering the line of sight (LoS) between antennas. The results indicate that the use of RFID technology at 125 kHz allows for data reception with a penetration depth of 0.6116 dB/m, demonstrating its suitability for data communication in marine environments. In the second part of the analysis, we examine the probabilities of data reception between static-node antennas at different heights and a terrestrial antenna at a specific height. Wave samples recorded in Playa Sisal, Yucatan, Mexico, are used for this analysis. The findings show a maximum reception probability of 94.5% between static nodes with an antenna at a height of 0 m and a 100% data reception probability between a static node and the terrestrial antenna when the static-node antennas are optimally positioned at a height of 1 m above sea level. Overall, this paper provides valuable insights into the application of RFID technology in marine environments for the UIoT, considering the minimization of impacts on marine fauna. The results suggest that by adjusting the characteristics of the RFID system, the proposed architecture can be effectively implemented to expand the monitoring area, considering variables both underwater and on the surface of the marine environment.

Aim: The purpose of this study is to report the surgical experience and outcomes with pre-operative localisation of non-palpable breast lesions using the RFID tag system., Methods: The cohort for this prospective study included patients over the age of 18 with biopsy proven, non-palpable indeterminate lesions, DCIS or breast cancer requiring pre-operative localisation before surgical excision between September 2020 and July 2022., Results: A total of 312 RFID tags were placed in 299 consecutive patients. Indications for localisation included non-palpable invasive cancer in 255 (85.3%) patients, in situ disease in 38 (12.7%) and indeterminate lesions requiring surgical excision in 6 (2.0%). Both in situ and invasive lesions had a median size of 13 mm (range 4-100 mm) on pre-operative imaging. The RFID tags were in situ for a median time of 21 days before surgery (range 0-233 days). Of the 213 tags, 292 (93.6%) were introduced using ultrasound (USS) guidance and stereotactically in 20 (6.4%). In 3 (1.0%) cases the RFID tag was either not satisfactorily deployed at the intended target or retrieved intra-operatively. Following discussion of post-operative histology by the multi-disciplinary team, further surgery for close or involved margins was for 26 (8.7%) patients., Conclusion: The Hologic RFID tag system can be used for accurate pre-operative localisation of non-palpable masses as well as diffuse abnormalities such as mammographic distortions and calcifications. It has advantages of flexibility for scheduling image-guided insertion independently of scheduled operating lists and can be placed to localise lesions prior to initiating neoadjuvant systemic treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

With the rapid growth in wireless communication and IoT technologies, Radio Frequency Identification (RFID) is applied to the Internet of Vehicles (IoV) to ensure the security of private data and the accuracy of identification and tracking. However, in traffic congestion scenarios, frequent mutual authentication increases the overall computing and communication overhead of the network. For this reason, in this work, we propose a lightweight RFID security fast authentication protocol for traffic congestion scenarios, designing an ownership transfer protocol to transfer access rights to vehicle tags in non-congestion scenarios. The edge server is used for authentication, and the elliptic curve cryptography (ECC) algorithm and the hash function are combined to ensure the security of vehicles' private data. The Scyther tool is used for the formal analysis of the proposed scheme, and this analysis shows that the proposed scheme can resist typical attacks in mobile communication of the IoV. Experimental results show that, compared to other RFID authentication protocols, the calculation and communication overheads of the tags proposed in this work are reduced by 66.35% in congested scenarios and 66.67% in non-congested scenarios, while the lowest are reduced by 32.71% and 50%, respectively. The results of this study demonstrate a significant reduction in the computational and communication overhead of tags while ensuring security.

Phenotypes on individual animals are required for breeding programs to be able to select for traits. However, phenotyping individual animals can be difficult and time-consuming, especially for traits related to health, welfare, and performance. Individual broiler behavior could serve as a proxy for these traits when recorded automatically and reliably on many animals. Sensors could record individual broiler behavior, yet different sensors can differ in their assessment. In this study a comparison was made between a passive radio frequency identification (RFID) system (grid of antennas underneath the pen) and video tracking for the determination of location and movement of 3 color-marked broilers at d 18. Furthermore, a systems comparison of derived behavioral metrics such as space usage, locomotion activity and apparent feeding and drinking behavior was made. Color-marked broilers simplified the computer vision task for YOLOv5 to detect, track, and identify the animals. Animal locations derived from the RFID-system and based on video were largely in agreement. Most location differences (77.5%) were within the mean radius of the antennas' enclosing circle (≤128 px, 28.15 cm), and 95.3% of the differences were within a one antenna difference (≤256 px, 56.30 cm). Animal movement was not always registered by the RFID-system whereas video was sensitive to detection noise and the animal's behavior (e.g., pecking). The method used to determine location and the systems' sensitivities to movement led to differences in behavioral metrics. Behavioral metrics derived from video are likely more accurate than RFID-system derived behavioral metrics. However, at present, only the RFID-system can provide individual identification for non-color marked broilers. A combination of verifiable and detailed video with the unique identification of RFID could make it possible to identify, describe, and quantify a wide range of individual broiler behaviors., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

With the rapid development towards smart Internet of Things (IoT), detection of human activity has become essential in a variety of applications. Various radio-frequency (RF) sensing technologies, such as WiFi, Radio-Frequency Identification (RFID), and Frequency-Modulated Continuous Wave (FMCW) radar, have been utilized for non-invasive human activity recognition (HAR). It will be highly desirable to develop a HAR solution that can work with different types of RF technologies, such that the cost and the barrier of wide deployment can both be greatly reduced, and more robust performance can be achieved by utilizing the complementary RF sensory data. In this paper, we propose a technology-agnostic approach for RF-based HAR, termed TARF, which works with several different RF sensing technologies. A novel data generalization technique is proposed to mitigate the disparity in measured data from different RF devices. A domain adversarial neural network is proposed to combat the interference from various RF sensing technologies. The performance of the proposed system is evaluated with experiments using four different RF sensing technologies. TARF is shown to outperform the state-of-the-art Convolutional Neural Network (CNN)-based solution with considerable gains.

COVID-19 is highly contagious and spreads rapidly; it can be transmitted through coughing or contact with virus-contaminated hands, surfaces, or objects. The virus spreads faster indoors and in crowded places; therefore, there is a huge demand for contact tracing applications in indoor environments, such as hospitals and offices, in order to measure personnel proximity while placing as little load on them as possible. Contact tracing is a vital step in controlling and restricting pandemic spread; however, traditional contact tracing is time-consuming, exhausting, and ineffective. As a result, more research and application of smart digital contact tracing is necessary. As the Internet of Things (IoT) and wearable sensor device studies have grown in popularity, this work has been based on the practicality and successful implementation of Bluetooth low energy (BLE) and radio frequency identification (RFID) IoT based wireless systems for achieving contact tracing. Our study presents autonomous, low-cost, long-battery-life wireless sensing systems for contact tracing applications in hospital/office environments; these systems are developed with off-the-shelf components and do not rely on end user participation in order to prevent any inconvenience. Performance evaluation of the two implemented systems is carried out under various real practical settings and scenarios; these two implemented centralised IoT contact tracing devices were tested and compared demonstrating their efficiency results.

In this study, we propose a specimen tube prototype and smart specimen transport box using radio frequency identification (RFID) and narrow band-Internet of Things (NB-IoT) technology to use in the Department of Laboratory Medicine, King Chulalongkorn Memorial Hospital. Our proposed method replaces the existing system, based on barcode technology, with shortage usage and low reliability. In addition, tube-tagged barcode has not eliminated the lost or incorrect delivery issues in many laboratories. In this solution, the passive RFID tag is attached to the surface of the specimen tube and stores information such as patient records, required tests, and receiver laboratory location. This information can be written and read multiple times using an RFID device. While delivering the specimen tubes via our proposed smart specimen transport box from one clinical laboratory to another, the NB-IoT attached to the box monitors the temperature and humidity values inside the box and tracks the box's GPS location to check whether the box arrives at the destination. The environmental condition inside the specimen transport box is sent to the cloud and can be monitored by doctors. The experimental results have proven the innovation of our solution and opened a new dimension for integrating RFID and IoT technologies into the specimen logistic system in the hospital.

Background: One of the main problems that may put people's safety in danger is the lack of real-time detection, evaluation, and recognition of predictable safety risks. Current real-time risk identification solutions are limited to proximity sensing, which lack providing the exposed person with risk-specific information in real-time. Combined values of concurrently presented risks are either unrecognized or underestimated., Objective: This study goes beyond the proximity sensing state-of-the-art by envisioning, planning, designing, developing, assembling, and examining an automated intelligent real-time risk (AIR) assessment system., Methods: A holistic safety assessment approach is followed to include identification, prioritization, detection, evaluation, and control at risk exposure time. Multi-sensor technologies based on RFID are integrated with a risk assessment intelligent system. System prototype is developed and examined to prove the concept for on-foot building construction workers., Results: The evaluation of AIR assessment system's performance proved its validity, significance, simplicity, representation, accuracy, precision, and timeliness. The reliability of providing quantitative proximity values of risk can be limited due to the signal attenuation; however, it can be reliable in providing risk proximity in a subjective linguistic fashion (Near/Far)., Conclusion: The main contributions of the AIR assessment system are that the mobile wearable device can provide a linguistic meaningful risk assessment resultant value, the value represents the combined evaluation of concurrently presented risks, and can be sound delivered to the exposed person in real-time of exposure. Therefore, AIR system can be used as an effective prognostic risk assessment tool that can empower workers with real-time recognition and measurability of risk exposure.

Fast and reliable identification of Radio Frequency Indentification (RFID) tags by means of anticollision (MAC) protocols has been a problem of substantial interest for more than a decade. However, improvements in identification rate have been slow, as most solutions rely on sequential approaches that try to avoid collisions, which have limited margin for performance improvement. Recently, there has been growing interest in concurrent techniques that exploit the structure of collisions to recover tag IDs. While these techniques promise substantial improvements in speed, a key question that remains unaddressed is how to deal with noise or interference that might introduce errors in the recovery process at the reader. Our goal in this paper is to consider a noisy wireless channel and add robustness to concurrent RFID identification techniques. We propose a new protocol, called CIRF (Concurrent Identification of RFids), which uses multiple antennas to add robustness to noise and leverages block sparsity-based optimization to recover EPC IDs of transmitting tags. We include fail-safe methods to handle errors that persist after the optimization stage. Extensive simulations show that CIRF achieves substantial resilience improvement in a range of very low to medium Signal-to-Noise (SNR) situations, being able to always correctly recover 99% of tags.

Recently, radio frequency identification (RFID) sensing has attracted much attention due to its contact-free nature, low cost, light weight and other advantages. RFID-based person detection has also become a hot research topic, but there are still some problems in the existing research. First, most of the current studies cannot identify numerous people at a time well. Second, in order to detect more accurately, it is necessary to evaluate the whole-body activity of a person, which will consume a lot of time to process the data and cannot be applied in time. To solve these problems, in this paper we propose RF-Detection, a person detection system using RFID. First of all, RF-Detection takes step length as the standard for person detection, divides step length into specific sections according to the relationship between step length and height, and achieves high accuracy for new user detection through a large amount of training for a specific step length. Secondly, RF-Detection can better identify the number of people in the same space by segmenting continuous people. Finally, the data collection was reduced by expanding the data set, and the deep learning method was used to further improve the accuracy. The results show that the overall recognition accuracy of RF-Detection is 98.93%.

Effective conservation management strategies require accurate information on the movement patterns and behaviour of wild animals. To collect these data, researchers are increasingly turning to remote sensing technology such as radio-frequency identification (RFID). RFID technology is a powerful tool that has been widely implemented in ecological research to identify and monitor unique individuals, but it bears a substantial price tag, restricting this technology to generously-funded disciplines and projects. To overcome this price hurdle, we provide detailed step-by-step instructions to source the components for, and construct portable RFID loggers in house, at a fraction of the cost (~5%) of commercial RFID units. Here, we assess the performance of these RFID loggers in the field and describe their application in two studies of Australian mammal species; monitoring nest-box use in the Northern quolls (Dasyurus hallucatus) and observing the foraging habits of quenda (Isoodon fusciventer) at feeding stations. The RFID loggers performed well, identifying quenda in >80% of visits, and facilitating the collection of individual-level behavioural data including common metrics such as emergence time, latency to approach, and foraging effort. While the technology itself is not novel, by lowering the cost per unit, our loggers enabled greater sample sizes, increasing statistical power from 0.09 to 0.75 in the quoll study. Further, we outline and provide solutions to the limitations of this design. Our RFID loggers proved an innovative method for collecting accurate behavioural and movement data. With their ability to successfully identify individuals, the RFID loggers described here can act as an alternative or complementary tool to camera traps. These RFID loggers can also be applied in a wide variety of projects which range from monitoring animal welfare or demographic traits to studies of anti-predator responses and animal personality, making them a valuable addition to the modern ecologists' toolkit., Competing Interests: The authors have declared that no competing interests exist.

Moisture content (MC) detection plays a vital role in the monitoring and management of living trees. Its measurement accuracy is of great significance to the progress of the forestry informatization industry. Targeting the drawbacks of high energy consumption, low practicability, and poor sustainability in the current field of living tree MC detection, this work designs and implements an ultra-high-frequency radio frequency identification (UHF RFID) sensor system based on a deep learning model, with the main goals of non-destructive testing and high-efficiency recognition. The proposed MC diagnostic system includes two passive tags which should be mounted on the trunk and one remote data processing terminal. First, the UHF reader collects information from the living trees in the forest; then, an improved online sequential parallel extreme learning machine algorithm (OS-PELM) is proposed and trained to establish a specific MC prediction model. This mechanism could self-adjust its neuron network structure according to the features of the data input. The experimental results show that, for the entire living tree dataset, the MC prediction model based on the OS-PELM algorithm can identify the MC level with a root-mean-square error (RMSE) of no more than 0.055 within a measurement range of 1.2 m. Compared with the results predicted by other algorithms, the mean absolute error (MAE) and RMSE are 0.0225 and 0.0254, respectively, which are better than the ELM and OS-ELM algorithms. Comparisons also prove that the prediction model has the advantages of high precision, strong robustness, and broad applicability. Therefore, the designed MC detection system fully meets the demand of forestry Artificial Intelligence of Things.

Respiratory monitoring is widely used in the field of health care. Traditional respiratory monitoring methods bring much inconvenience to users. In recent years, a great number of respiratory monitoring methods based on wireless technology have emerged, but multi-person respiratory monitoring is still very challenging; therefore, this paper explores multi-person respiratory monitoring. Firstly, the characteristics of human respiratory movement have been analyzed, and a suitable tag deployment method for respiratory monitoring is proposed. Secondly, aiming at the ambiguity and entanglement of radio frequency identification (RFID) phase data, a method of removal of phase ambiguity and phase wrapping is given. Then, in order to monitor multi-person respiration in a noisy environment, the frequency extraction method and waveform reconstruction method of multi-person respiration are proposed. Finally, the feasibility of the method is verified by experiments.

Chipless radio frequency identification (RFID) technology has been widely used in the field of structural health monitoring (SHM), but most of the current research mainly focuses on the detection of mechanical properties and there are few studies on the multi-physical parameters (for example, temperature and humidity) in the climatic environment around the structure. Thus, it is necessary to design a small and compact sensor for multi-parameter detection. This paper proposes a multi-parameter chipless RFID sensor based on microstrip coupling, which supports 4-bit ID code and integrates two detection functions of temperature and humidity. Through linear normalization fitting, the sensitivity of the sensor is about 2.18 MHz/RH in the ambient relative humidity test and the sensitivity of the sensor is about 898.63 KHz/°C in the experimental test of water bath heating from 24.6 °C to 75 °C. In addition, this paper proposes an engineering application detection method, designs a lightweight dynamic spectrum detection and wireless transmission platform based on a lightweight vector network analyzer (VNA) and realizes the real-time extraction and transmission of RFID spectrum sensing data. The means are more flexible and economical than traditional experimental scenarios.

Motion information collection technology is a means for measuring, tracking, and recording the movement traces of individuals in space. This method can complete the data collection of volleyball players and the ball trajectory and realize quantification and statistical analysis of the data to present a virtual model of the player's movement trajectory. It is inseparable from the acquisition of information to complete the information collection. Therefore, this work uses the radio frequency identification (RFID) technology in the Internet of Things technology to build an information collection system and apply it to volleyball sports. The existing positioning system based on RFID has problems such as significant positioning errors and high system costs due to the arrangement of a large number of readers. This paper first introduces the theoretical knowledge of the RFID system, wireless network positioning technology, and RFID system positioning method in the Internet of Things. Besides, the theoretical framework of the volleyball movement information acquisition system is presented based on the Received Signal Strength Indication of the RFID system and Location Identification based on the Dynamic Active RFID Calibration (LANDMARC) algorithm. Then, the LANDMARC algorithm is improved through the Centroid Positioning algorithm, forming the CP-LANDMARC algorithm. Finally, a simulation experiment is conducted to test the system effect. The results demonstrate that: (1) the average error of the basic LANDMARC algorithm is 0.55 meters, and the average error of the CP-LANDMARC algorithm is 0.46 meters; (2) the average error of the CP-LANDMARC algorithm is 0.43 meters when the reference label is set to be evenly distributed in a square, and the average error of the optimized algorithm is 0.38 m when the reference label is set as an equilateral triangle; and (3) when the number of reference labels increases to 110, the average error decreases from 0.38 to 0.29. This paper aims to improve the quality of volleyball teaching and training by designing a relevant sports information acquisition system., Competing Interests: The authors declare that there are no conflicts of interest., (Copyright © 2022 Tao Zhang et al.)

Objective: To evaluate a novel technology for real time tracking of RF-Identified (RFID) surgical tools (Biotic System), providing intraoperative data analytics during simulated cardiovascular procedures. Ineffective asset management in the Operating Room (OR) leads to inefficient utilization of resources and contributes to prolonged operative times and increased costs. Analysis of captured data can assist in quantifying instrument utilization, procedure flow, performance and prevention of retained instruments. Methods & Results: Five surgeons performed thirteen simulated surgical cases on three human cadavers. Procedures included (i) two abdominal aortic aneurysm (AAA) repairs, (ii) three carotid endarterectomies (CE), (iii) two femoropopliteal (fem-pop) bypasses, (iv) thoracic aortic aneurysm repair, (v) coronary artery bypass graft, (vi) aortic valve replacement, (vii) ascending aortic aneurysm repair, (viii) heart transplants, and (ix) mitral valve replacement. For each case an average of 139 surgical instruments were RFID-tagged and tracked intraoperatively. Data was captured and analyzed retrospectively. Of the 139 instruments tracked across each of the 13 cases, 55 instruments (39.5%) were actually used, demonstrating a high level of redundancy. For repeat cases (i.e. CE/AAA/fem-pop): (i) average instrument usage was 41 ± 3.6 (8.8% variation) for CE (n=3); (ii) average instrument usage was 69 ± 4.0 (5.8% variation) for AAA (n=2); and (iii) average instrument usage was 48 ± 2.5 (5.3% variation) for fem- pop (n=2). Results also showed a reduction in end-of-procedure instrument counting times of 58-87%. Conclusions: We report on a method for collecting intraoperative data analytics regarding instrument usage via RFID technology. This system will help refine instrument selection, quantitate instrument utilization and prevent inadvertent retention in a patient. This should help increase efficiency in packaging and sterilization and let surgeons make objective decisions in the composition of surgical trays. Clinical and Translational Impact Statement -Intraoperative analytics of surgical tools and associated equipment may ultimately lead to safer more efficient surgeries that increase patient outcomes while decreasing the cost of care.

Missing tag incidents are common in RFID-enabled supply-chain and warehousing scenarios due to cargo theft and employee error operations, which may lead to serious economic losses or potential safety hazards. On the premise of ensuring the accuracy of missing tag detection, this paper aims to improve the time efficiency in an integrated RFID system. Unlike prior work focusing on detecting missing items from a large number of homogeneous tags that are monitored by a single reader, one integrated RFID system possesses multiple readers to communicate with the heterogeneous tags, which have different categorical attributes. In addition, the prior work required repeating the execution several times to capture the missing tags in assorted categories, which is of low time efficiency. Thus, a protocol called Multi-reader Missing Tag Detection (MMTD) is proposed to capture the missing tag quickly and reliably, which can detect missing tags from different categories in a parallel manner and is much more time-efficient than previous work. MMTD has two major advantages compared to prior work: (i) It leverages the knowledge of the spatial distribution of tags to divide up a difficult detection task into several lightweight tasks, which are shared by multiple readers. (ii) It personalizes the time frame of the reader based on the tag population to optimize the utilization of the communication channel. The final simulation results reveal that MMTD is the best in time-efficiency among the comparison protocols, and MMTD outperforms the other missing tag detection protocols by at least 1.5× in the Integrated RFID scenarios.

Inventorying blood products is an essential process in blood station management. Traditional methods need to integrate barcodes with refrigerators, which suffer from low time efficiency, high error rate and high labour cost. Several methods have been proposed to automate this process in blood stations. However, none of them is ideal enough. In this paper, we analyse the difficulties of automation in blood inventory, and propose an automated blood inventory system based on UHF RFID technology. Comparisons over our method with manual inventory and handheld RFID inventory are conducted. The result shows that our method is nearly 10 times higher than manual inventory in time efficiency while increases the accuracy to 100%., (Copyright © 2021 Société française de transfusion sanguine (SFTS). Published by Elsevier Masson SAS. All rights reserved.)

In an IoT (Internet of Things) system where each IoT device has one/many RFID tags, there might be many RFID tags. However, when multiple tags respond to the reader's interrogation at the same time, their signals collide. Due to the collision, the reader must request the colliding tags to retransmit their IDs, resulting in higher communication overhead and longer identification time. Therefore, this paper presents a Bit-tracking Knowledge-based Query Tree (BKQT), which uses two techniques: knowledge , which stores all the tag IDs that can possibly occur, and bit tracking , which allows the reader to detect the locations of the collided bits in a collision slot. BKQT constructs a query tree for all possible tags, called a k-tree, by using knowledge while it constructs bit-collision cases and the corresponding actions for each node in this k-tree by using bit tracking. In the identification process, BKQT traverses this constructed k-tree and thus identifies the colliding tags faster by taking the actions according to the happening bit-collision cases. From the simulation results, BKQT can improve the identification time by 44.3%, 46.4%, and 25.1%, compared with the previous knowledge-based protocols, Knowledge Query Tree (KQT), Heuristic Query Tree (H-QT), Query Tree with Shortcutting and Couple Resolution (QTSC), respectively.

Existing methods for analysis of home cage-based preference tests are either time-consuming, not suitable for group management, expensive, and/or based on proprietary equipment that is not freely available. To correct this, we developed an automated system for group-housed mice based on radio frequency identification: the Mouse Position Surveillance System (MoPSS). The system uses an Arduino microcontroller with compatible components; it is affordable and easy to rebuild for every laboratory because it uses free and open-source software and open-source hardware with the RFID readers as the only proprietary component. The MoPSS was validated using female C57BL/6J mice and manual video comparison. It proved to be accurate even for fast-moving mice (up to 100% accuracy after logical reconstruction), and is already implemented in several studies in our laboratory. Here, we provide the complete construction description as well as the validation data and the results of an example experiment. This tracking system will allow group-based preference testing with individually identified mice to be carried out in a convenient manner. This facilitation of preference tests creates the foundation for better housing conditions from the animals' perspective., (© 2021. The Author(s).)

The era people live in is the era of big data, and massive data carry a large amount of information. This study aims to analyze RFID data based on big data and clustering algorithms. In this study, a RFID data extraction technology based on joint Kalman filter fusion is proposed. In the system, the proposed data extraction technology can effectively read RFID tags. The data are recorded, and the KM-KL clustering algorithm is proposed for RFID data, which combines the advantages of the K-means algorithm. The improved KM-KL clustering algorithm can effectively analyze and evaluate RFID data. The experimental results of this study prove that the recognition error rate of the RFID data extraction technology based on the joint Kalman filter fusion is only 2.7%. The improved KM-KL clustering algorithm also has better performance than the traditional algorithm., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Lihua Lv.)

A 32-bit chipless RFID tag operating in the 4.5-10.9 GHz band is presented in this paper. The tag has a unique multiple-arc-type shape consisting of closely packed 0.2 mm wide arcs of different radii and lengths. The specific tag geometry provides multiple resonances in frequency domain of an RCS plot. A frequency domain coding technique has also been proposed to encode the tag's RCS signature into a 32-bit digital identification code. The tag has an overall dimension of 17.9 × 17.9 mm 2 , resulting in a high code density of 9.98 bits/cm 2 and spectral efficiency of 5 bits/GHz. The proposed tag is built on a low loss substrate bearing a very small footprint, thereby making it extremely suitable for large-scale product identification purposes in future chipless RFID tag systems.

To solve the inspection problems in cotton storage, as well as the need for environmental monitoring in the process of modern cotton bale storage, an intelligent inspection and temperature and humidity intelligent monitoring system based on RFID cotton bale was developed by adopting RFID (Radio Frequency Identification) technology, wireless temperature and humidity real-time monitoring technology and handheld terminal intelligent inspection technology. The system was composed of RFID positioning inspection module and temperature and humidity real-time monitoring and transmission module. The artificial neural network (ANN) based on the particle swarm optimization (PSO) algorithm was used to process the monitoring data of the system by Gaussian filtering, and an accurate classification model of RSSI and label position was established. The test results showed that: Through the comparative analysis of the RFID indoor positioning algorithm, the positioning error of the PSO-ANN algorithm was small. In the actual cotton bale warehouse test, the relative error of positioning and monitoring for RFID cotton bale intelligent inspection and monitoring system was less than 6.7%, which effectively improved the working efficiency of inspection personnel and the security of cotton bale storage. The relative error of temperature and humidity was less than 8% and less than 7%, which could display the temperature and humidity information in real time and meet the real-time demand. This study improved the management personnel's effective positioning and inspection of the cotton bale, prevented the loss of cotton bale, reduced the deterioration probability of cotton bale, and effectively improved the storage management level of the cotton bale. It was of great practical significance to realize the networking, automation, and intelligence of cotton bale storage management., (© 2022. The Author(s).)

Objective: Failure to follow-up on laboratory test results can lead to missed diagnoses, diagnostic delays, patient harm, and potential malpractice claims against providers. State-of-the-art tracking technologies such as the radio frequency identification (RFID) can potentially improve laboratory order processing and test result communication. We conducted a comparative evaluation of differences in completion rates for 5 testing process milestones and time to reach these process milestones, with and without RFID order tracking for skin biopsy orders., Methods: This observational study analyzed 48,515 orders from 20 dermatology providers, sent to 8 pathology laboratories in 2016 to 2017. Descriptive t tests and multiple Cox proportional hazard regressions were used to examine the differences in completion rates and times to the 5 testing process milestones, namely, (1) provider receipt of results, (2) provider review of results, (3) patient notification, (4) follow-up scheduling, and (5) order case closure, for orders processed with and without RFID order tracking., Results: Descriptive statistics illustrated that all 5 testing process milestone completion rates were statistically higher for RFID tracked orders compared with non-RFID tracked orders, and RFID tracked orders took 3 to 5 days lesser than non-RFID tracked orders to reach the 5 testing process milestones. Multiple cox proportional hazard regressions showed that the process milestones were achieved faster if orders were RFID tracked versus not (hazard ratios ranged from 1.3 to 4.9)., Conclusions: The RFID tracking technology considerably improved test result communication timeliness and reliability. Such technologies can be beneficial for laboratory order processing, and their effectiveness should be explored in other practice settings., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Camouflage is a strategy that animals utilize for concealment in their habitat, making themselves invisible to their predators and preys. In RF systems, steganography or stealth transmission is the camouflage of information - a technology of hiding and transmitting secret messages in public media. Steganography conceals the secret message in publicly available media such that the eavesdropper or attacker will not be able to tell if there is a secret message to look for. Marine hatchetfish have two effective camouflage skills to help them hide from their predators - silvering and counterillumination. Silvering in marine hatchetfish uses its microstructured skin on its sides to achieve destructive interference at colors that could indicate the presence of the fish, while they also emit light at their bottom part to match its color and intensity to its surrounding, making it invisible from below, referred to as counterillumination. In this work, we borrow the two underwater camouflage strategies from marine hatchetfish, mimic them with photonic phenomena, and apply the camouflage strategies for physical stealth transmission of a 200 MBaud/s 16QAM OFDM secret signal at 5 GHz over a 25-km of optical fiber. The proposed bio-inspired steganography strategies successfully hid the secret signal in plain sight in temporal, RF spectral, and optical spectral domains, by blending in using counterillumination and turning invisible using silvering techniques. The stealth signal can only be retrieved with the precise and correct parameter for constructive interference at the secret signal frequency to unmask the silvering.

Background: We aimed to improve the tumor localization system using radiofrequency identification (RFID) technology used during laparoscopic surgery for gastric and colorectal cancer. To this end, we developed a detection algorithm and designed improvement for the RFID clip., Methods: To evaluate the proposed system, a swine-based animal study was conducted, followed by experiments on porcine stomachs and colons using the EASIE-R simulator. The success rates of endoscopic clipping, detection time, and detection accuracy, which is the distance between the detection point and RFID tag, were measured., Results: Results of the in vivo swine animal study showed success in all three clippings and detections of the RFID clips. Results of the 60 RFID endoclip attempts using the EASIE-R simulator showed a total clipping success rate of 85.0% (n = 51/60; stomach, 83.3%, n = 25/30; colon, 86.7%, n = 26/30). The median detection times were 29.2 s for the stomach and 25.5 s for the colon. The median detection accuracy was 4.0 mm for the stomach and 4.5 mm for the colon., Conclusions: We confirmed that the proposed RFID-based system showed improvements over the system of a previous study. This RFID-based system is effective at localizing gastric and colorectal tumors.

We report the results of an experiment on radio-tracking of individual grey field slugs in an arable field and associated data modelling designed to investigate the effect of slug population density in their movement. Slugs were collected in a commercial winter wheat field in which a 5x6 trapping grid had been established with 2m distance between traps. The slugs were taken to the laboratory, radio-tagged using a recently developed procedure, and following a recovery period released into the same field. Seventeen tagged slugs were released singly (sparse release) on the same grid node on which they had been caught. Eleven tagged slugs were released as a group (dense release). Each of the slugs was radio-tracked for approximately 10 h during which their position was recorded ten times. The tracking data were analysed using the Correlated Random Walk framework. The analysis revealed that all components of slug movement (mean speed, turning angles and movement/resting times) were significantly different between the two treatments. On average, the slugs released as a group disperse more slowly than slugs released individually and their turning angle has a clear anticlockwise bias. The results clearly suggest that population density is a factor regulating slug movement.

Background/aim: The purpose of this study was to evaluate, whether radio frequency identification (RFID) labeling of axillary lymph nodes (LNs) for the use of targeted resection is feasible in primary breast cancer patients with suspicious LNs., Patients and Methods: We analyzed 10 consecutive patients where RFID technique was used for intraoperative detection of suspicious LNs without preceding neoadjuvant chemotherapy (NACT). We compared the specifics of these procedures to 10 consecutive sentinel lymph node biopsies (SLNB) in the cN0 situation., Results: Intraoperative detection rate (DR) for the RFID-labeled target lymph node (TLN) was 100%. Perioperative complications were infrequent and comparable to SLNB. Average time for location of the RFID labeled TLN was quicker than for the SLN. In 71.4% the chip bearing TLN equaled a SLN., Conclusion: The use of the RFID technique for intraoperative localization of axillary LNs for targeted excision seems feasible. RFID technique for targeted axillary dissection (TAD) following NACT should be investigated in a prospective manner., (Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Radio Frequency Identification (RFID) technology has been widely used in indoor location tracking, especially serving human beings, due to its advantage of low cost, non-contact communication, resistance to hostile environments and so forth. Over the years, many indoor location tracking methods have been proposed. However, tracking mobile RFID readers in real-time has been a daunting task, especially for achieving high localization accuracy. In this paper, we propose a new Mobile RFID (M-RFID)-based Localization approach for Indoor Human Tracking, named MRLIHT. Based on the M-RFID model where RFID readers are equipped on the moving objects (human beings) and RFID tags are fixed deployed in the monitoring area, MRLIHT implements the real-time indoor location tracking effectively and economically. First, based on the readings of multiple tags detected by an RFID reader simultaneously, MRLIHT generates the response regions of tags to the reader. Next, MRLIHT determines the potential location region of the reader where two algorithms are devised. Finally, MRLIHT estimates the location of the reader by dividing the potential location region of the reader into finer-grained grids. The experimental results demonstrate that the proposed MRLIHT performs well in both accuracy and scalability.

A common goal of captive animal institutions is to create environments that allow for the most naturalistic behavior from their animals. Behavioral data is often used as a measure of how an animal is thriving in its current environment. Obtaining this data can be very difficult and time-consuming. New technological advances, such as radio frequency identification (RFID) technology, may allow for data collection to be automated. RFID tags placed on the wingband of 16 little blue penguins housed at the Cincinnati Zoo and Botanical Garden, as well as 8 antennae placed in their habitat, continuously recorded individual penguin swimming behavior. The continuous data collected via the RFID system reveals individual patterns of swimming behavior among indoor and outdoor pool areas, as well as relationships between swimming and water temperature, and temporal factors. Additionally, the effectiveness of an enrichment item meant to increase swimming time is evaluated using the RFID system. The presence of the RFID system allows for continuous, reliable data collection that can provide valuable insight regarding the quantifiable relationship between little blue behavior, environment, and overall health.

Background/aim: Wire-guided localisation (WGL) has been the mainstay for localisation of clinically occult breast lesions before excision. However, it has restrictive scheduling requirements, and causes patient discomfort. This has prompted the development of various wireless alternatives. In this prospective study we shall evaluate the role of radiation-free wireless localisation using a radiofrequency identification (RFID) tag and a hand-held reader (LOCalizer™) in the management of occult breast lesions., Patients and Methods: This technique was evaluated in a prospective cohort of 10 patients. The evaluation focused on: i) successful deployment, ii) identification and retrieval, iii) the status of surgical margins and need for re-operation, iv) resected specimen weight, v) marker migration rates (>5mm), and vi) acceptance by patients, radiologists and surgeons., Results: RFID tags (n=11) were deployed under ultrasound guidance pre-operatively to localise occult breast lesions in 10 patients. The mean time for deployment of the RFID tag was 5.4 min (range=2-20). The mean distance from the lesion was 0.45 mm (range=0-3). The mean duration for retrieval was 10.2 min (range=6-20). Mean specimen weight was 19.6 g for malignant lesions (range=4.5-42). All tags were identified, and none had migrated. There were no positive margins, re-operations, nor complications. Patient feedback was highly positive. Both radiologists and surgeons rated the LOCalizer™ technique as better than WGL., Conclusion: Our study demonstrates that wireless localisation using RFID is an effective and time-efficient alternative to WGL, with low margin positivity and re-operation rates, and high patient, radiologist and surgeon acceptance., (Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

It is difficult for visually impaired people to move indoors and outdoors. In 2018, world health organization (WHO) reported that there were about 253 million people around the world who were moderately visually impaired in distance vision. A navigation system that combines positioning and obstacle detection has been actively researched and developed. However, when these obstacle detection methods are used in high-traffic passages, since many pedestrians cause an occlusion problem that obstructs the shape and color of obstacles, these obstacle detection methods significantly decrease in accuracy. To solve this problem, we developed an application "Follow me!". The application recommends a safe route by machine learning the gait and walking route of many pedestrians obtained from the monocular camera images of a smartphone. As a result of the experiment, pedestrians walking in the same direction as visually impaired people, oncoming pedestrians, and steps were identified with an average accuracy of 0.92 based on the gait and walking route of pedestrians acquired from monocular camera images. Furthermore, the results of the recommended safe route based on the identification results showed that the visually impaired people were guided to a safe route with 100% accuracy. In addition, visually impaired people avoided obstacles that had to be detoured during construction and signage by walking along the recommended route., Competing Interests: The authors declare no conflict of interest.

Background: Faulty cleaning of surgical instruments may lead to corrosion damage and a higher risk of surgical site infection. We have developed a method in which each instrument has an attached radiofrequency identification (RFID) tag for individual management. However, because of the structure of the instruments, a risk of corrosion from poor cleaning exists; therefore, observation during long-term usage is necessary. Methods: The cleaning effect at the jig of the RFID tag was verified by the amount of residual protein left by various cleaning methods. In our investigation of long-term usage, we examined 94 surgical instruments with RFID tags used in the operating room for 50 months employing a microscope to identify any corrosion at the jig. Results: The method using a washer disinfector (WD) was found to be highly effective. From observation after long-term usage, friction by the RFID tag occurred in about 70% of the jigs. However, no pitting or general corrosion was seen. Conclusions: When WD is used properly, there is only a minor risk of residual protein, and corrosion does not occur even with long-term use. By using surgical instruments with RFID tags, it is possible to determine the number of uses and the history at the individual level. This facilitates operation of safe surgical instruments by limiting the number of times a particular instrument is used.