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Leveraging the fluidity and excellent conductivity of liquid metal (gallium‐indium alloy), liquid metal (LM) can be utilized to manufacture flexible and stretchable electronic products for applications in soft robotics, wearable devices, and human–machine interaction. However, the high surface tension and low surface adhesion of LM hinder its patterning and high‐resolution fabrication of soft electronics. Here a recyclable LM‐silicon dioxide (LMS) ink is proposed. Under stirring, silicon dioxide (SiO2) particles are encapsulated by the oxide layer of the LM, consuming the oxide layer. Meanwhile, gallium in the LM reacts with oxygen from the air to form a new oxide layer, enhancing the adhesion of the LM to the substrate while maintaining its conductivity. The in‐situ printing of LMS ink is verified on various materials (e.g., paper, polymer, and glass) with a resolution of up to 165 µm and an exceptional conductivity of ≈6.53 × 106 S m−1. The printed patterns can be erased with an anhydrous ethanol solution, allowing the recovered LMS ink to be reused for multiple writing cycles. The general method for direct LM circuits printing can fabricate various wearable sensors for soft electronic devices and human–machine interaction. [ABSTRACT FROM AUTHOR]

The hand tremor symptoms of Parkinson’s disease (PD) patients are expressed in a wide variety of forms. These tremors are not limited to specific areas, but the most experienced by PD patients are hand-related. To detect such hand tremor symptoms, a device based on an inertial measurement unit (IMU) was used to measure changes in the vibration speed around the wrist. The sensor data collected from the gyroscope through a dedicated algorithm can be reflected to convert it into a result value of the number of tremors of the user, and hand tremor characteristics can be extracted. The performance of the system was validated using a hand tremor simulator. The experiments confirmed that the algorithm operated normally under the specific conditions set (5–18Hz) for hand tremor detection, and the operation results matched those of the theoretically detectable range. The wearable device can measure the user’s bio-kinetic signals in daily life using a gyroscope, adjust the algorithm’s sensitivity based on the severity of tremor symptoms, and continuously monitor symptoms by transmitting the recognition results via Bluetooth communication. [ABSTRACT FROM AUTHOR]

Soft strain sensors can accurately monitor the deformation of irregular and dynamic surfaces. However, traditional thin‐film strain sensors are generally not direction‐specific, and the sensor becomes unpredictable when stretched in different directions simultaneously. Here, a soft 1D strain sensor is reported that is only sensitive to axial deformation by rolling up a thin‐film strain sensor based on liquid metals (LM) and thermoplastic polyurethane (TPU) elastomer. The sensitivity of the 1D sensor can be regulated by rolling the 2D sensor at different angles. The 1D strain sensors have a large strain measuring range (>100%), high strain resolution (0.5%), fast responsiveness (<40 ms), and high reproducibility (over 2000 cycles), which are expected to adapt to various application scenarios with different sensitivity requirements. In addition, 1D strain sensors with different sensitivities can be braided into a three‐strand braid to provide measurements with three different sensitivities at the same time. [ABSTRACT FROM AUTHOR]

In this work, BC-PVA composite organohydrogels are prepared using polyvinyl alcohol (PVA) as matrix and bacterial cellulose (BC) nanofibers as reinforcement. BC-PVA@PPY conductive organohydrogels are obtained by depositing polypyrrole (PPY) on the BC-PVA organohydrogels via in situ polymerization of pyrrole. The mechanical properties of the organohydrogels are improved by the addition of BC nanofibers. The BC-PVA@PPY organohydrogels show good stability and repeatability in strain sensing. Due to their superior sensing performance, the BC-PVA@PPY organohydrogels can be used to monitor human activities (such as elbow movement and finger movement), indicating potential applications in wearable electronic devices. BC-PVA composite organohydrogels were prepared using polyvinyl alcohol (PVA) as a matrix and reinforced with bacterial cellulose (BC) nanofibers. BC-PVA@PPy conductive organohydrogels were obtained by depositing polypyrrole (PPy) on the BC-PVA organohydrogels via in situ polymerization of pyrrole. The mechanical properties of the organohydrogels were improved by the addition of BC nanofibers. The BC-PVA@PPy organohydrogels exhibited good stability and repeatability in strain sensing and has potential applications in monitoring human activities. [ABSTRACT FROM AUTHOR]

Wearable devices have a significant impact on society, and recent advancements in modern sensor technologies are opening up new possibilities for healthcare applications. Continuous vital sign monitoring using Internet of Things solutions can be a crucial tool for emergency management, reducing risks in rescue operations and ensuring the safety of workers. The massive amounts of data, high network traffic, and computational demands of a typical monitoring application can be challenging to manage with traditional infrastructure. Cloud computing provides a solution with its built-in resilience and elasticity capabilities. This study presents a Cloud-based monitoring architecture for remote vital sign tracking of paramedics and medical workers through the use of a mobile wearable device. The system monitors vital signs such as electrocardiograms and breathing patterns during work sessions, and it is able to manage real-time alarm events to a personnel management center. In this study, 900 paramedics and emergency workers were monitored using wearable devices over a period of 12 months. Data from these devices were collected, processed via Cloud infrastructure, and analyzed to assess the system's reliability and scalability. The results showed a significant improvement in worker safety and operational efficiency. This study demonstrates the potential of Cloud-based systems and Internet of Things devices in enhancing emergency response efforts. [ABSTRACT FROM AUTHOR]

IMU sensors (three-dimensional accelerometer, gyroscope and magnetometer) enable assessment of walking in older adults outside the laboratory. We studied whether IMUs are valid for detecting walking parameters (step events, time, length, and cadence) in a laboratory and outdoors on a level surface in older adults. This validation study is part of a larger cross-sectional study. Twenty-six participants (mean age 76 years, 65 % female) walked on a treadmill indoors and on a sport track outdoors at self-selected speed. IMUs were attached laterally on the shanks and on the lower back at the level of L3-L4. Initial contact (IC) and step lengths were also estimated using acceleration signals (vertical, antero-posterior) from the pelvic IMU. Terminal contact (TC) was determined from the shank IMU sagittal angular velocity. For step length, inverted pendulum model and participant's leg length (0.53 x height) was used. Step duration was calculated from IC to the opposite leg IC and stride duration from IC to next ipsilateral IC. Cadence was calculated as steps/min. As reference data, 3D motion capture was used in the laboratory and a high-speed video camera outdoors. Intraclass correlation coefficients (ICC), root mean squared errors (RMSE), typical errors and Bland-Altman plots were calculated and drawn. When comparing IC timing between IMU and reference data, mean bias was 0.031 s in the laboratory and −0.004 s outdoors, and for TC −0.057 s and −0.070 s respectively. Step and stride duration and cadence showed ICC values >0.80 and mean bias was <0.005 s for step and stride durations and <0.05 steps/min for cadence in both environments. Step length ICC values were <0.40 in the laboratory and outdoors. IMUs can be used to monitor temporal walking variables in older adults and may be useful for rehabilitation interventions and functional capacity assessment. • Older adults' walking parameters can be assessed also outdoors with IMU sensors • Accuracy of step/stride duration and cadence is good outdoors and in the laboratory • Accuracy of step length and walking speed is poorer in both environments [ABSTRACT FROM AUTHOR]

Assessing the effect of insoles on gait biomechanics and foot comfort remains challenging. Our novel in-insole-type wearable sensor device (smart insole) enables accurate quantitative evaluation of gait parameters without affecting the subject's foot comfort. What are the effects of insoles on gait biomechanics and foot comfort in patients with flatfoot, as evaluated using a novel smart insole? Thirty-three subjects with 61 flatfeet were recruited. Three different types of prefabricated insoles were tested: a control insole as an experimental control, a flat insole with only cushion pads for the shock absorbing function, and an arch support insole with both cushioning pads and arch support functions. Gait parameters and visual analog scale (VAS) scores for foot comfort were measured during 30 m of straight walking with each insole incorporating the wearable sensor device. The differences in gait parameters and foot comfort between the flat and arch support insoles relative to the control insole were analyzed. Additionally, the correlations between gait parameters and foot comfort were evaluated. Maximum plantarflexion angle significantly decreased (p = 0.03) and the toe-out angle significantly increased (p < 0.01) with arch support insoles compared to flat insoles. Significantly better foot comfort was demonstrated when walking with arch support insoles than with flat insoles (p < 0.01). The only gait parameter correlated with foot comfort was foot lift height while walking with an arch support insole (r = −0.45, p < 0.01). A novel smart insole revealed that foot lift height was a key gait parameter for determining foot comfort while walking with an arch support insole. Our findings provide important evidence for selecting a comfortable flatfoot insole based on gait data measured using a smart insole. • This study is the first smart insole-based gait analysis of insoles in patients with flatfoot. • Our novel smart insole is an effective tool to evaluate the effects of insoles. • Foot lift height was a key parameter for foot comfort while walking with an arch support insole. [ABSTRACT FROM AUTHOR]

Background: Sarcopenia and osteoarthritis are prevalent age-related diseases that mutually exacerbate each other, creating a vicious cycle that worsens both conditions. Exercise is key to breaking this detrimental cycle. Facing increasing demand for rehabilitation services within this patient demographic, ChatGPT-4 and wearable device may increase the availability, efficiency and personalization of such health care. Aim: To evaluate the clinical efficacy and cost-effectiveness of a rehabilitation system implemented on mobile platforms, utilizing the integration of ChatGPT-4 and wearable devices. Methods: The study design is a prospective randomized open blinded end-point (PROBE) non-inferiority trial. 278 patients diagnosed with osteoarthritis and sarcopenia will be recruited and randomly assigned to the intervention group and the control group. In the intervention group patients receive mobile phone-based rehabilitation service where ChatGPT-4 generates personalized exercise therapy, and wearable device guides and monitor the patient to implement the exercise therapy. Traditional clinic based face-to-face exercise therapy will be prescribed and implemented in the control group. All patients will receive three-months exercise therapies following the frequency, intensity, type, time, volume and progression (FITT-VP) principle. The patients will be assessed at baseline, one month, three months, and six months after initiation. Outcome measures will include ROM, gait patterns, Visual Analogue Scale (VAS) for pain assessment, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Knee Injury and Osteoarthritis Outcome Score (KOOS) for functional assessment, Short-Form Health Survey 12 (SF-12) for quality of life, Minimal Clinically Important Difference (MCID), Patient Acceptable Symptom State (PASS), and Substantial Clinical Benefit (SCB) for clinically significant measures. Discussion: A rehabilitation system combining the capabilities of ChatGPT-4 and wearable devices potentially enhance the availability and efficiency of professional rehabilitation services, thus enhancing the therapeutic outcomes for a substantial population concurrently afflicted with sarcopenia and osteoarthritis. [ABSTRACT FROM AUTHOR]

Researchers have attempted to control robotic hands and prostheses through biosignals but could not match the human hand. Surface electromyography records electrical muscle activity using non-invasive electrodes and has been the primary method in most studies. While surface electromyography-based hand motion decoding shows promise, it has not yet met the requirements for reliable use. Combining different sensing modalities has been shown to improve hand gesture classification accuracy. This work introduces a multimodal bracelet that integrates a 24-channel force myography system with six commercial surface electromyography sensors, each containing a six-axis inertial measurement unit. The device's functionality was tested by acquiring muscular activity with the proposed device from five participants performing five different gestures in a random order. A random forest model was then used to classify the performed gestures from the acquired signal. The results confirmed the device's functionality, making it suitable to study sensor fusion for intent detection in future studies. The results showed that combining all modalities yielded the highest classification accuracies across all participants, reaching 92.3 ± 2.6 % on average, effectively reducing misclassifications by 37% and 22% compared to using surface electromyography and force myography individually as input signals, respectively. This demonstrates the potential benefits of sensor fusion for more robust and accurate hand gesture classification and paves the way for advanced control of robotic and prosthetic hands. [ABSTRACT FROM AUTHOR]

Recently, eutectogels have emerged as ideal candidates for flexible wearable strain sensors. However, the development of eutectogels with robust mechanical strength, high stretchability, excellent transparency, and desirable conductivity remains a challenge. Herein, a covalently cross-linked eutectogel was prepared by exploiting the high solubility of oligoethylene glycol in a polymerizable deep eutectic solvent (DES) form of acrylic acid (AA) and choline chloride (ChCl). The resulting eutectogel exhibited high transparency (90%), robust mechanical strength (up to 1.5 MPa), high stretchability (up to 962%), and desirable ionic conductivity (up to 1.22 mS cm−1). The resistive strain sensor fabricated from the eutectogel exhibits desirable linear sensitivity (GF: 1.66), wide response range (1–200%), and reliable stability (over 1000 cycles), enabling accurate monitoring of human motions (fingers, wrists, and footsteps). We believe that our DES-based eutectogel has great potential for applications in wearable strain sensors with high sensitivity and reliability. [ABSTRACT FROM AUTHOR]

Fiber‐based thermoelectric (TE) device that can collect waste heat of human body and convert it into electricity is growing fast and is of great significance for sustainable development. Although ionic thermoelectric (i‐TE) ionogels are considered to be the next generation of TE materials, to construct ionogel fiber with synergistically enhanced mechanical and i‐TE performances remains big challenge. Herein, the poly(vinylidene fluoride‐co‐hexafluoropropylene)/1‐ethyl‐3‐methylimidazolium dicyanamide/ethanol/NaTFSI/SiO2 (PH/ED‐E‐Na‐SiO2) ionogel with ultrahigh ionic Seebeck coefficient of 47.5 mV K−1 and ionic conductivity of 43.7 mS cm−1 is constructed by a proposed antisolvent‐doping‐hybrid synergistic strategy. The enhanced i‐TE performances are mainly attributed to the low crystalline structure and the improvement in ions dissociation, migration, and diffusion difference. The corresponding power factor of the PH/ED‐E‐Na‐SiO2 ionogel film is as high as 9845.8 µW m−1 K−2, which is almost the highest value ever reported. Based on this, the ionogel fiber with comparable i‐TE performances and significantly enhanced tensile strength and strain (from 327 KPa and 47% of film to 17.7 MPa and 70% of fiber) is prepared by a simple coating process. It can be weaved into wearable i‐TE device that generates high thermovoltage and lights the light‐emitting diode (LED) bulb, demonstrating its great application potential as wearable energy supply device. [ABSTRACT FROM AUTHOR]

This study introduces a novel wearable device that combines dual‐functional modules for energy storage and sensing. The device features an ionic gel serving as both the battery electrolyte and sensor dielectric layer, along with VO2‐nanoneedles electrodes. The solid‐state zinc‐ion battery module demonstrates a specific capacity of 286 mAh g−1, delivering consistent and long‐lasting power output even under variable pressure conditions. Moreover, the iontronic pressure sensor module exhibits high sensitivity, achieving 2.3 × 104 kPa−1, enabling precise detection of fingertip pulses and identification of respiratory patterns. The device's flexibility and structural resilience allow it to endure complex deformations, ensuring continuous operation in challenging environments. These results highlight the potential of the all‐in‐one device for wearable smart healthcare monitoring and management. [ABSTRACT FROM AUTHOR]

AbstractPurposeMaterials and methodsResultsConclusions\nIMPLICATIONS FOR REHABILITATIONTo evaluate the validity of a consumer-grade wearable for estimating energy expenditure, sedentary behaviour, and physical activity in manual wheelchair users with spinal cord injury (SCI).Fifteen manual wheelchair users with SCI (C5-L1, four female) completed activities of daily living and wheelchair propulsion (2–8 km·h−1). Wrist-worn accelerometry data were collected using consumer-grade (z-Track) and research-grade (ActiGraph GT9X) devices. Energy expenditure was measured via indirect calorimetry. Linear regression was used to evaluate the prediction of criterion metabolic equivalent of task (MET) by each accelerometer’s vector magnitude (VM). Area under the receiver operating characteristic curve (ROC-AUC) evaluated the accuracy of VM for discriminating between physical activity intensities and for identifying accelerometer cut-points.Standardised β-coefficients for the association between z-Track and ActiGraph VM for criterion MET were 0.791 (p < 0.001) and 0.774 (p < 0.001), respectively. The z-Track had excellent accuracy for classifying time in sedentary behaviour (ROC-AUC = 0.95) and moderate-to-vigorous physical activity (ROC-AUC = 0.93); similar values to the ActiGraph (ROC-AUC = 0.96 and 0.88, respectively). Cut-points for the z-Track were ≤37 g·min−1 for sedentary behaviour and ≥222 g·min−1 for moderate-to-vigorous physical activity.This study supports the validity of a consumer-grade wearable to measure sedentary time and physical activity in manual wheelchair users with SCI.A consumer-grade wearable device provides valid estimations of sedentary time and physical activity in manual wheelchair users with spinal cord injury.Commercially available consumer-grade wearables may enable accurate self-monitoring in this population and, therefore, have potential for supporting behaviour change.A consumer-grade wearable device provides valid estimations of sedentary time and physical activity in manual wheelchair users with spinal cord injury.Commercially available consumer-grade wearables may enable accurate self-monitoring in this population and, therefore, have potential for supporting behaviour change. [ABSTRACT FROM AUTHOR]

Introduction: This study examined how a six-week progressive flywheel resistance training program for the core muscles affects gymnasts' core explosive strength and floor exercise performance. Methods: Ten elite male artistic gymnasts were recruited. Core explosive strength was measured using average power, maximum concentric power, maximum eccentric power, and average strength obtained from a flywheel resistance training machine. Inertial sensors were used to collect trunk acceleration and rotational angular velocity during straight-back somersaults with 2/1 and 3/1. After the pretest, the participants were divided into experimental and control groups (n = 5/group) using a randomized crossover trial design. Following six weeks of progressive training, a posttest was conducted to collect relevant data. After a seven-week washout period, the two groups were swapped and underwent another six weeks of training. Statistical analyses were performed using dependent and independent samples t-tests, considering a significance level of α = 0.05. Results: The experimental group showed significant pretest-to-posttest improvements in average power and maximum concentric power during the supine rotational explosive strength tests and in average power, maximum eccentric power, and average strength during prone rotational explosive strength tests (p < 0.05). It also showed significant pretest-to-posttest improvements in trunk acceleration at takeoff in straight-back somersaults with 2/1 and 3/1 (p < 0.05). Conclusion: The adopted training program can effectively enhance the core explosive strength and trunk acceleration capabilities of gymnasts' floor exercise athletic performance. Future studies may integrate lower body and core training to explore the optimal training schedules for artistic gymnasts. [ABSTRACT FROM AUTHOR]

[Display omitted] • Achieve high-precision DIW printing using conductive hydrogel ink. • Conductive hydrogel electrodes have remarkable stretchability and self-healing capabilities. • Develop a self-powered strain sensing system employing conductive hydrogel electrodes. • Construct a complex internal structure within the electrode. • Remote human motion detection based on hydrogel strain sensors. With rapid advancements in health and human–computer interaction, wearable electronic skins (e-skins) designed for application on the human body provide a platform for real-time detection of physiological signals. Wearable strain sensors, integral functional units within e-skins, can be integrated with Internet of Things (IoT) technology to broaden the applications for human body monitoring. A significant challenge lies in the reliance of most existing wearable strain sensors on rigid external power supplies, limiting their practical flexibility. In this study, we present an innovative strategy to fabricate glutaraldehyde (GA)-poly(vinyl alcohol) (PVA)/cellulose nanocrystals (CNC)/Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) conductive hydrogels through multiple hydrogen bonding systems. Combining the advantageous rheological properties of the precursor solution and the high specific surface area after freeze–thaw cycling, we have created a self-powered sensing system prepared by large-area printing using direct ink writing (DIW) printing. The resulting conductive hydrogel exhibits commendable mechanical properties (411 KPa), impressive stretchability (580 %), and robust self-healing capabilities (>98.3 %). The strain sensor, derived from the conductive hydrogel, demonstrates a gauge factor (GF) of 2.5 within a stretching range of 0–580 %. Additionally, the resultant supercapacitor displays a peak energy density of 0.131 mWh/cm3 at a power density of 3.6 mW/cm3. Benefiting from its elevated strain response and remarkable power density features, this self-powered strain sensing system enables the real-time monitoring of human joint motion. The incorporation of a 5G transmission module enhances its capabilities for remote data monitoring, thereby contributing to the progress of wireless tracking technologies for self-powered electronic skin. [ABSTRACT FROM AUTHOR]

[Display omitted] • MOF nanosheets reconfigured by electrostatic coupling and interfacial conditioning strategies. • PEDOT:PSS and MOF nanosheets with interoperable conductive network and excellent interfacial properties. • MOF nanosheets attenuate the entanglement of PEDOT:PSS. • Homogeneous ink prepared using solution engineering for flexible supercapacitor preparation. Two-dimensional metal – organic frameworks (2D MOFs) hold great promise as electrochemically active materials. However, their application in MOF nanocomposite electrodes in solution engineering is limited by structural self-stacking and imperfect conductive pathways. In this study, we used meso -tetra(4-carboxyphenyl) porphine (TCPP) with off-domain π-bonds to reconstitute Zn-TCPP (ZMOF) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) through an interfacial modulation strategy involving electrostatic coupling and hydrogen bonding, creating a conductive composite with a nanosheet structure. The negatively charged PSS and ZMOF formed a three-dimensional interconnected conductive network with excellent interfaces. The positively charged PEDOT, fine tuned with the lamellar structure, established strong π-π stacking interactions between the porphyrin and thiophene rings. ZMOF also induced changes in the PEDOT chain structure, weakening PSS entanglement and enhancing charge-transport properties. The specific capacitance of the prepared supercapacitor was as high as 967.8 F g−1. Flexible supercapacitors produced on a large scale using dispensing printing technology exhibited an energy density of 1.85 μWh cm−2 and a power density of 7.08 μW cm−2. This interfacial modulation strategy also exhibited excellent wearable properties, with 96 % capacitance retention at a 180° bending angle and stable cycling performance. This study presented a significant advancement in the functionalization of 2D materials, highlighting their potential for device-grade capacitive architectures. [ABSTRACT FROM AUTHOR]

Wearable technology has seen rapid advancement, yet the integration of responsive materials into wearable devices poses significant challenges, particularly in maintaining fabric integrity and user comfort while ensuring sensitivity and responsiveness to environmental stimuli. In this work, these challenges are addressed by developing an ultra‐stable hydrochromic fabric that exhibits both hydro‐ and halochromic responsiveness. Utilizing a bimolecular fluoran dye system composed of a black leuco dye (ODB‐2) and a weak acid developer (benzyl 4‐hydroxybenzoate, B4H), these materials are embedded into a robust fibrous matrix constructed through an electrospinning process with thermoplastic polyurethane (TPU). This approach ensures the breathability, flexibility, and structural integrity of the fabrics, while the hydrophobic nature of TPU contributes to the stability and reversibility of the hydro/halochromic properties. The strategy allows for immediate, high‐contrast color changes upon exposure to water and acidic/basic vapors. These fabrics are also applied in rewritable data encryption, demonstrating their potential in anti‐counterfeiting. Furthermore, the investigation into the mechanical properties of these fabrics confirms their durability and resilience, making them ideal for wearable technology. [ABSTRACT FROM AUTHOR]

Arrhythmias range from mild nuisances to potentially fatal conditions, detectable through electrocardiograms (ECGs). With advancements in wearable technology, ECGs can now be monitored on-the-go, although these devices often capture noisy data, complicating accurate arrhythmia detection. This study aims to create a new deep learning model that utilizes generative adversarial networks (GANs) for effective noise removal and ResNet for precise arrhythmia classification from wearable ECG data. We developed a deep learning model that cleans ECG measurements from wearable devices and detects arrhythmias using refined data. We pretrained our model using the MIT-BIH Arrhythmia and Noise databases. Least squares GANs were used for noise reduction, maintaining the integrity of the original ECG signal, while a residual network classified the type of arrhythmia. After initial training, we applied transfer learning with actual ECG data. Our noise removal model significantly enhanced data clarity, achieving over 30 dB in a signal-to-noise ratio. The arrhythmia detection model was highly accurate, with an F1-score of 99.10% for noise-free data. The developed model is capable of real-time, accurate arrhythmia detection using wearable ECG devices, allowing for immediate patient notification and facilitating timely medical response. [ABSTRACT FROM AUTHOR]

The wearable device market is growing rapidly, as evidenced by the growth in sales of smartwatches. However, these have a tiny touch screen so users cannot perform complex operations with a smartwatch. Few studies address the user experience of gestures to interact with wearable devices. This study uses a bone-conduction smartwatch to study the user experience of gestures for interaction with a wearable device in terms of four dimensions: pragmatic quality, hedonic quality–identification and hedonic quality–stimulation and attractiveness. Task loads ae also evaluated for further analysis of the user experience This study determines the relationship between these factors to determine the effect of using hand gestures to interact with wearable devices. The results of this study show that all of the users easily accept gesture interaction with wearable devices. Pragmatic quality, hedonic quality–identification and hedonic quality–stimulation are positively associated with attractiveness. A higher level of attractiveness reduces the perceived task load. Attractiveness has a significant positive effect on performance and task load has a significant negative effect on performance. [ABSTRACT FROM AUTHOR]

Background: Mixed reality (MR) is helpful in hand training for patients with stroke, allowing them to fully submerge in a virtual space while interacting with real objects. The recognition of individual finger movements is required for MR rehabilitation. This study aimed to assess the effectiveness of updated MR-board 2, adding finger training for patients with stroke. Methods: Twenty-one participants with hemiplegic stroke (10 with left hemiplegia and 11 with right hemiplegia; nine female patients; 56.7 ± 14.2 years of age; and onset of stroke 32.7 ± 34.8 months) participated in this study. MR-board 2 comprised a board plate, a depth camera, plastic-shaped objects, a monitor, a palm-worn camera, and seven gamified training programs. All participants performed 20 self-training sessions involving 30-min training using MR-board 2. The outcome measurements for upper extremity function were the Fugl–Meyer assessment (FMA) upper extremity score, repeated number of finger flexion and extension (Repeat-FE), the thumb opposition test (TOT), Box and Block Test score (BBT), Wolf Motor Function Test score (WMFT), and Stroke Impact Scale (SIS). One-way repeated measures analysis of variance and the post hoc test were applied for the measurements. MR-board 2 recorded the fingers' active range of motion (AROM) and Dunnett's test was used for pairwise comparisons. Results: Except for the FMA-proximal score (p = 0.617) and TOT (p = 0.005), other FMA scores, BBT score, Repeat-FE, WMFT score, and SIS stroke recovery improved significantly (p < 0.001) during MR-board 2 training and were maintained until follow-up. All AROM values of the finger joints changed significantly during training (p < 0.001). Conclusions: MR-board 2 self-training, which includes natural interactions between humans and computers using a tangible user interface and real-time tracking of the fingers, improved upper limb function across impairment, activity, and participation. MR-board 2 could be used as a self-training tool for patients with stroke, improving their quality of life. Trial registration number: This study was registered with the Clinical Research Information Service (CRIS: KCT0004167). [ABSTRACT FROM AUTHOR]

Several power assist robots have been developed to reduce workloads, and address worker shortages and an aging workforce. Previously, the authors developed a power assist device to maintain shoulder posture using a braking mechanism; however, the device presented technical issues regarding the rigidity and weight of the mechanism. To address these issues, in this study, a flexible linear brake (FLB), a brake mechanism driven by negative pressure, was developed for power assist devices. Additionally, a braking force model for the FLB is proposed; the proposed model was verified by comparing the measured and modelled values. Finally, a shoulder assist device that uses the FLB and designed based on the proposed model is discussed in detail. [ABSTRACT FROM AUTHOR]

Essential tremor (ET) stands as the most prevalent movement disorder, characterized by rhythmic and involuntary shaking of body parts. Achieving an accurate and comprehensive assessment of tremor severity is crucial for effectively diagnosing and managing ET. Traditional methods rely on clinical observation and rating scales, which may introduce subjective biases and hinder continuous evaluation of disease progression. Recent research has explored new approaches to quantifying ET. A promising method involves the use of intelligent devices to facilitate objective and quantitative measurements. These devices include inertial measurement units, electromyography, video equipment, and electronic handwriting boards, and more. Their deployment enables real-time monitoring of human activity data, featuring portability and efficiency. This capability allows for more extensive research in this field and supports the shift from in-lab/clinic to in-home monitoring of ET symptoms. Therefore, this review provides an in-depth analysis of the application, current development, potential characteristics, and roles of intelligent devices in assessing ET. [ABSTRACT FROM AUTHOR]

Accurately obtaining a patient's respiratory rate is crucial for promptly identifying any sudden changes in their condition during emergencies. Typically, the respiratory rate is assessed through a combination of impedance change measurements and electrocardiography (ECG). However, impedance measurements are prone to interference from body movements. Conversely, a capnometer coupled with a ventilator offers a method of measuring the respiratory rate that is unaffected by body movements. However, capnometers are mainly used to evaluate respiration when using a ventilator or an Ambu bag by measuring the CO2 concentration at the breathing circuit, and they are not used only to measure the respiratory rate. Furthermore, capnometers are not suitable as wearable devices because they require intubation or a mask that covers the nose and mouth to prevent air leaks during the measurement. In this study, we developed a reliable system for measuring the respiratory rate utilizing a small wearable MOx sensor that is unaffected by body movements and not connected to the breathing circuit. Subsequently, we conducted experimental assessments to gauge the accuracy of the rate estimation achieved by the system. In order to avoid the effects of abnormal states on the estimation accuracy, we also evaluated the classification performance for distinguishing between normal and abnormal respiration using a one-class SVM-based approach. The developed system achieved 80% for both true positive and true negative rates. Our experimental findings reveal that the respiratory rate can be precisely determined without being influenced by body movements. [ABSTRACT FROM AUTHOR]

The prevalence of e‐cigarette use among young adults in the USA is high (14%). Although the majority of users plan to quit vaping, the motivation to make a quit attempt is low and available support during a quit attempt is limited. Using wearable sensors to collect physiological data (eg, heart rate) holds promise for capturing the right timing to deliver intervention messages. This study aims to fill the current knowledge gap by proposing statistical methods to (1) de‐noise beat‐to‐beat interval (BBI) data from smartwatches worn by 12 young adult regular e‐cigarette users for 7 days; and (2) summarize the de‐noised data by event and control segments. We also conducted a comprehensive review of conventional methods for summarizing heart rate variability (HRV) and compared their performance with the proposed method. The results show that the proposed singular spectrum analysis (SSA) can effectively de‐noise the highly variable BBI data, as well as quantify the proportion of total variation extracted. Compared to existing HRV methods, the proposed second order polynomial model yields the highest area under the curve (AUC) value of 0.76 and offers better interpretability. The findings also indicate that the average heart rate before vaping is higher and there is an increasing trend in the heart rate before the vaping event. Importantly, the development of increasing heart rate observed in this study implies that there may be time to intervene as this physiological signal emerges. This finding, if replicated in a larger scale study, may inform optimal timings for delivering messages in future intervention. [ABSTRACT FROM AUTHOR]

Fewer layer graphene principally has a higher surface area to support more catalytic sites for energy conversion, but it is still challenging to synthesize monolayer graphene without oxidation from graphite at a low cost. Here, a method for synergistically thinning graphene layers and constructing catalytic sites to create a superior bifunctional oxygen catalyst through vapor intercalation of multi‐layer graphene or its derivatives is described. The synthesized small sheet sizes of 1–2 layer graphene‐supported FeN4 and FeCo active sites exhibit superior reversible activity of oxygen reduction and evolution reactions with a low overall overpotential of 0.648 V. The sheet‐shaped catalyst is further used to fabricate flexible soft‐packed and wearable cable‐type quasi‐solid‐state zinc–air batteries, achieving high performances (>188 mW cm−2, >450 cycles) and enabling smartphone charging. DFT calculations reveal that fewer layer graphene coupled with atomic FeN4 and alloy FeCo sites enables lower Gibbs free energy for favorable OOH* intermediate adsorption/desorption benefiting superior oxygen redox process. This study introduces a strategy for scalable synthesis of 1–2 layer graphene from cheap microcrystalline graphite minerals for wearable and durable energy devices. [ABSTRACT FROM AUTHOR]

Self‐powered pressure detection using smart wearable devices is the subject of intense research attention, which is intended to address the critical need for prolonged and uninterrupted operations. Current piezoelectric and triboelectric sensors well respond to dynamic stimuli while overlooking static stimuli. This study proposes a dual‐response potentiometric pressure sensor that responds to both dynamic and static stimuli. The proposed sensor utilizes interdigital electrodes with MnO2/carbon/polyvinyl alcohol (PVA) as the cathode and conductive silver paste as the anode. The electrolyte layer incorporates a mixed hydrogel of PVA and phosphoric acid. The optimized interdigital electrodes and sandpaper‐like microstructured surface of the hydrogel electrolyte contribute to enhanced performance by facilitating an increased contact area between the electrolyte and electrodes. The sensor features an open‐circuit voltage of 0.927 V, a short‐circuit current of 6 µA, a higher sensitivity of 14 mV/kPa, and outstanding cycling performance (>5000 cycles). It can accurately recognize letter writing and enable capacitor charging and LED lighting. Additionally, a data acquisition and display system employing the proposed sensor, which facilitates the monitoring of athletes' rehabilitation training, and machine learning algorithms that effectively guide rehabilitation actions are presented. This study offers novel solutions for the future development of smart wearable devices. [ABSTRACT FROM AUTHOR]

With the development of technology, people's demand for pressure sensors with high sensitivity and a wide working range is increasing. An effective way to achieve this goal is simulating human skin. Herein, we propose a facile, low-cost, and reproducible method for preparing a skin-like multi-layer flexible pressure sensor (MFPS) device with high sensitivity (5.51 kPa−1 from 0 to 30 kPa) and wide working pressure range (0–200 kPa) by assembling carbonized fabrics and micro-wrinkle-structured Ag@rGO electrodes layer by layer. In addition, the highly imitated skin structure also provides the device with an extremely short response time (60/90 ms) and stable durability (over 3000 cycles). Importantly, we integrated multiple sensor devices into gloves to monitor finger movements and behaviors. In summary, the skin-like MFPS device has significant potential for real-time monitoring of human activities in the field of flexible wearable electronics and human–machine interaction. [ABSTRACT FROM AUTHOR]

A two-stream convolutional neural network (TCNN) for breathing pattern classification has been devised for the continuous monitoring of patients with infectious respiratory diseases. The TCNN consists of a convolutional neural network (CNN)-based autoencoder and classifier. The encoder of the autoencoder generates deep compressed feature maps, which contain the most important information constituting data. These maps are concatenated with feature maps generated by the classifier to classify breathing patterns. The TCNN, single-stream CNN (SCNN), and state-of-the-art classification models were applied to classify four breathing patterns: normal, slow, rapid, and breath holding. The input data consisted of chest tissue hemodynamic responses measured using a wearable near-infrared spectroscopy device on 14 healthy adult participants. Among the classification models evaluated, random forest had the lowest classification accuracy at 88.49%, while the TCNN achieved the highest classification accuracy at 94.63%. In addition, the proposed TCNN performed 2.6% better in terms of classification accuracy than an SCNN (without an autoencoder). Moreover, the TCNN mitigates the issue of declining learning performance with increasing network depth, as observed in the SCNN model. These results prove the robustness of the TCNN in classifying breathing patterns despite using a significantly smaller number of parameters and computations compared to state-of-the-art classification models. [ABSTRACT FROM AUTHOR]

Introduction: Widespread use of smartphone applications has opened new perspectives for home Blood Pressure monitoring based on mobile health (mHealth) technologies. Patient engagement has been dubbed 'the silver bullet of the century'. Aim: The aim was to identify the impact of engagement in patients with blood pressure using mHealth. Methods: This scoping review was conducted in accordance with the Ark0sey and O'Malley framework. Database: Pubmed, CINAHL, Scopus and PsycInfo. This review considered both qualitative and quantitative primary searches. We excluded articles belonging to grey literature, secondary literature and paediatric setting. Between September and November 2023, the review was carried out. Results: A total of 569 documents were retrieved from the four databases. After the deduplication process, five articles were removed. The selection process based on titles and abstracts included 133 records. Ten studies were selected and analysed. The reviewers identified the following themes: device type and mobile applications, engagement, blood pressure control, health behaviours and hypertension knowledge. Self-management using digital technologies in the home is strongly linked to engagement, reduction and control of Blood Pressure, improved health practices and increased knowledge of hypertension. Healthcare interventions using IT platforms have had a significant impact on the health outcomes of patients diagnosed with hypertension. Conclusions: The review findings suggest the value of these technologies in improving patient engagement and, consequently, adherence to antihypertensive treatment and achieving blood pressure control rates, potentially reducing cardiovascular risk. [ABSTRACT FROM AUTHOR]

With the rapid development of novel smart electronics, there is an increasing demand for consumer electronic products that possess high performance, light weight and flexibility. However, traditional rigid silicon-based devices struggle to meet the specific requirements of fields such as wearable devices and electronic skins. Two-dimensional (2D) materials have garnered significant attention in the emerging electronics industry due to their excellent optoelectronic properties, making the flexible transparent 2D-based optoelectronic devices become a forefront research area in cutting-edge technology. This paper provides a detailed introduction to the key components of flexible transparent 2D optoelectronic devices, including 2D materials, transparent electrodes, and flexible transparent substrates/dielectric layers. It comprehensively discusses the wideranging applications of devices, such as flexible transparent transistors, photodetectors, sensors, and capacitors for wearable electronics, transparent smart displays, and medical monitoring. Finally, it summarizes the current challenges and development prospects of flexible transparent 2D optoelectronic devices. With the continuous innovation and development of materials science, nanotechnology, and manufacturing processes, it is believed that flexible transparent electronic technology will become more mature and reliable, bringing greater convenience and possibilities to human life. [ABSTRACT FROM AUTHOR]

Introduction: People with Parkinson's Disease (PD) show abnormal gait patterns compromising their independence and quality of life. Among all gait alterations due to PD, reduced step length, increased cadence, and decreased ground-reaction force during the loading response and push-off phases are the most common. Wearable biofeedback technologies offer the possibility to provide correlated single or multi-modal stimuli associated with specific gait events or gait performance, hence promoting subjects' awareness of their gait disturbances. Moreover, the portability and applicability in clinical and home settings for gait rehabilitation increase the efficiency in the management of PD. The Wearable Vibrotactile Bidirectional Interface (BI) is a biofeedback device designed to extract gait features in real-time and deliver a customized vibrotactile stimulus at the waist of PD subjects synchronously with specific gait phases. The aims of this study were to measure the effect of the BI on gait parameters usually compromised by the typical bradykinetic gait and to assess its usability and safety in clinical practice. Methods: In this case series, seven subjects (age: 70.4 ± 8.1 years; H&Y: 2.7 ± 0.3) used the BI and performed a test on a 10-meter walkway (10mWT) and a two-minute walk test (2MWT) as pre-training (Pre-trn) and post-training (Post-trn) assessments. Gait tests were executed in random order with (Bf) and without (No-Bf) the activation of the biofeedback stimulus. All subjects performed three training sessions of 40 min to familiarize themselves with the BI during walking activities. A descriptive analysis of gait parameters (i.e., gait speed, step length, cadence, walking distance, double-support phase) was carried out. The 2-sided Wilcoxon sign-test was used to assess differences between Bf and No-Bf assessments (p < 0.05). Results: After training subjects improved gait speed (Pre-trn_No-Bf: 0.72(0.59,0.72) m/sec; Post-trn_Bf: 0.95(0.69,0.98) m/sec; p = 0.043) and step length (Pre-trn_No-Bf: 0.87(0.81,0.96) meters; Post-trn_Bf: 1.05(0.96,1.14) meters; p = 0.023) using the biofeedback during the 10mWT. Similarly, subjects' walking distance improved (Pre-trn_No-Bf: 97.5 (80.3,110.8) meters; Post-trn_Bf: 118.5(99.3,129.3) meters; p = 0.028) and the duration of the double-support phase decreased (Pre-trn_No-Bf: 29.7(26.8,31.7) %; Post-trn_Bf: 27.2(24.6,28.7) %; p = 0.018) during the 2MWT. An immediate effect of the BI was detected in cadence (Pre-trn_No-Bf: 108(103.8,116.7) step/min; Pre-trn_Bf: 101.4(96.3,111.4) step/min; p = 0.028) at Pre-trn, and in walking distance at Post-trn (Post-trn_No-Bf: 112.5(97.5,124.5) meters; Post-trn_Bf: 118.5(99.3,129.3) meters; p = 0.043). SUS scores were 77.5 in five subjects and 80.3 in two subjects. In terms of safety, all subjects completed the protocol without any adverse events. Conclusion: The BI seems to be usable and safe for PD users. Temporal gait parameters have been measured during clinical walking tests providing detailed outcomes. A short period of training with the BI suggests improvements in the gait patterns of people with PD. This research serves as preliminary support for future integration of the BI as an instrument for clinical assessment and rehabilitation in people with PD, both in hospital and remote environments. Trial registration: The study protocol was registered (DGDMF.VI/P/I.5.i.m.2/2019/1297) and approved by the General Directorate of Medical Devices and Pharmaceutical Service of the Italian Ministry of Health and by the ethics committee of the Lombardy region (Milan, Italy). [ABSTRACT FROM AUTHOR]

BACKGROUND: This study aims to implement a set of wearable technologies to record and analyze the surgeon's physiological and ergonomic parameters during the performance of conventional and robotic-assisted laparoscopic surgery, comparing the ergonomics and stress levels of surgeons during surgical procedures. METHODS: This study was organized in two different settings: simulator tasks and experimental model surgical procedures. The participating surgeons performed the tasks and surgical procedures in both laparoscopic and robotic-assisted surgery in a randomized fashion. Different wearable technologies were used to record the surgeons' posture, muscle activity, electrodermal activity and electrocardiography signal during the surgical practice. RESULTS: The simulator study involved six surgeons: three experienced (>100 laparoscopic procedures performed; 36.33 ± 13.65 years old) and three novices (<100 laparoscopic procedures; 29.33 ± 8.39 years old). Three surgeons of different surgical specialties with experience in laparoscopic surgery (>100 laparoscopic procedures performed; 37.00 ± 5.29 years old), but without experience in surgical robotics, participated in the experimental model study. The participating surgeons showed an increased level of stress during the robotic-assisted surgical procedures. Overall, improved surgeon posture was obtained during robotic-assisted surgery, with a reduction in localized muscle fatigue. CONCLUSIONS: A set of wearable technologies was implemented to measure and analyze surgeon physiological and ergonomic parameters. Robotic-assisted procedures showed better ergonomic outcomes for the surgeon compared to conventional laparoscopic surgery. Ergonomic analysis allows us to optimize surgeon performance and improve surgical training. [ABSTRACT FROM AUTHOR]

Hydrogel is a research hotspot in the field of polymer materials and has great application value in many fields, such as wearable devices. However, the mechanical properties of hydrogel limit its application range. As a natural biopolymer, sodium alginate (SA) has good biocompatibility, but SA hydrogels lack toughness and cannot meet the requirements of strain sensors. In this work, guar gum (GG) is used to enhance the toughness of SA hydrogels so that it can be used to prepare wearable devices. Scanning electron microscopy was used for morphological and structural studies, and Fourier transform infrared spectroscopy was used for cross-linking characterization. The results show that the SA/GG hydrogels prepared by the one-pot method have good tensile properties, and the wearable devices assembled based on them have good stimulus responsiveness, long-term operational stability and excellent water retention. Among them, the SA/GG-2 composite hydrogel has the most excellent comprehensive performance, with the maximum stress and strain reaching 36.5 kPa and 7.3%, and the water retention of the assembled sensors reaching more than 98%, and the resistance and capacitance change rate reaching more than 25%. The SA/GG composite hydrogel has a potential application prospect in the field of wearable devices. [ABSTRACT FROM AUTHOR]

In recent years, wearable e-skin has emerged as a prominent technology with a wide range of applications in healthcare, health surveillance, human–machine interface, and virtual reality. Inspired by the properties of human skin, arrayed wearable e-skin is a novel technology that offers multifunctional sensing capabilities. It can detect and quantify various stimuli, mimicking the human somatosensory system, and record a wide range of physical and physiological parameters in real time. By combining flexible electronic device units with a data acquisition system, specific functional sensors can be distributed in targeted areas to achieve high sensitivity, resolution, adjustable sensing range, and large-area expandability. This review provides a comprehensive overview of recent advances in wearable e-skin technology, including its development status, types of applications, power supply methods, and prospects for future development. The emphasis of current research is on enhancing the sensitivity and stability of sensors, improving the comfort and reliability of wearable devices, and developing intelligent data processing and application algorithms. This review aims to serve as a scientific reference for the intelligent development of wearable e-skin technology. [ABSTRACT FROM AUTHOR]

In recent years, the market for wearable devices has been rapidly growing, with much of the demand for health management. These devices are equipped with numerous sensors that detect inertial measurements, electrocardiograms, photoplethysmography signals, and more. Utilizing the collected data enables the monitoring and analysis of the user's health status in real time. With the proliferation of wearable devices, research on applications such as human activity recognition, anomaly detection, and disease prediction has advanced by combining these devices with deep learning technology. Analyzing heart rate variability and activity data, for example, enables the early detection of an abnormal health status and prompt, appropriate medical interventions. Much of the current research focuses on short-term predictions, but adopting a long-term perspective is essential for further development of wearable devices and deep learning. Continuously recording user behavior, anomalies, and physical information and collecting and analyzing data over an extended period will enable more accurate disease predictions and lifestyle guidance based on individual habits and physical conditions. Achieving this requires the integration of wearable devices with medical records. A system needs to be created to integrate data collected by wearable devices with medical records such as electronic health records in collaboration with medical facilities like hospitals and clinics. Overcoming this challenge will enable optimal health management and disease prediction for each user, leading to a higher quality of life. [ABSTRACT FROM AUTHOR]

This paper aims to discuss the implementation of data analysis and information management for elderly nursing care from a data-driven perspective. It addresses the current challenges of in-home caregivers, providing a basis for decision making in analyzing nursing service content and evaluating job performance. The characteristics of caregivers' activities were analyzed during the design of a wearable device-wearing scheme and a sensor data collection system. XGBoost, SVM, and Random Forest models were used in the experiments, with the Cuckoo search algorithm employed to optimize the XGBoost model parameters. Based on the control group experiment, it was confirmed that the XGBoost model, after adjusting the parameters using the Cuckoo search algorithm, exhibited better recognition performance than the SVM and RandomForest models, and the accuracy reached 0.9438. Wearable devices present high recognition accuracy in caregiver activity recognition research, which greatly improves the inspection of caregivers' work and further promotes the completion of services. This study actively explores the applications of information technology and artificial intelligence theory to address practical problems and effectively promote the digitalization and intelligent development of the elderly nursing care industry. [ABSTRACT FROM AUTHOR]

Objective To evaluate the sensitivity, specificity and accuracy of smart wearable devices in identifying atrial fibrillation (AF). Methods We selected 410 patients who had undergone 24-hour ambulatory electrocardiography (AECG) monitoring; they wore smart wearable devices during the same period. A comparison was made between the consistency of the two examination methods for detecting AF; the sensitivity, specificity and accuracy of smart wearable devices were assessed. Results With a sensitivity of 99. 31%, specificity of 81. 48%, accuracy rate of 95. 41%, and a Kappa value of 0. 83, smart wearable devices showed a relatively strong consistency with AECG monitoring in the detection rate of AF. Conclusion Smart wearable devices are convenient to use with high compliance of patients. They are highly accurate in automatically detecting AF, which facilitates promoting daily and family-based AF screening. [ABSTRACT FROM AUTHOR]

We propose the use of a specially designed polyurethane foam with a plateau region in its mechanical characteristics—where stress remains nearly constant during deformation—between the electromyography (EMG) electrode and clothing to suppress motion artifacts in EMG measurement. Wearable EMG devices are receiving attention for monitoring muscle weakening due to aging. However, daily EMG measurement has been challenging due to motion artifacts caused by changes in the contact pressure between the bioelectrode and the skin. Therefore, this study aims to measure EMG signals in daily movement environments by controlling the contact pressure using polyurethane foam between the bioelectrode on the clothing and the skin. Through mechanical calculations and finite element method simulations of the polyurethane foam's effect, we clarified that the characteristics of the polyurethane foam significantly influence contact pressure control and that the contact pressure is adjustable through the polyurethane foam thickness. The optimization of the design successfully controlled the contact pressure between the bioelectrode and skin from 1.0 kPa to 2.0 kPa, effectively suppressing the motion artifact in EMG measurement. [ABSTRACT FROM AUTHOR]

AbstractEvidence indicates haptic stimulation can effectively evoke emotions and can be utilized in communication technologies’ design. Due to the impact of culture on people’s tactile behaviours and lack of research in West Asian cultures, this study aims to investigate the impact of affective haptics in Persian users. Using a wearable prototype, a test is conducted on 78 users to evaluate the arousal and valence level of their 4 emotions (anger, happiness, relaxed and sadness) when exposed to text messages with and without haptic stimulation and to see if they can recognise the stimuli with given haptic patterns. A semi-focused interview is also done to evaluate the results further with qualitative feedbacks. Results show vibro-tactile stimuli increase the arousal level and reduce the valence level of the emotions; however, vibrotactile stimuli cannot convey the desired valence level as they cannot render the tactile patterns related to each emotion properly. [ABSTRACT FROM AUTHOR]

Tin‐based perovskite solar cells (TPSCs) have received increasing attention due to their low toxicity, high theoretical efficiency, and potential applications as wearable devices. However, the inherent fast and uncontrollable crystallization process of tin‐based perovskites results in high defect density in the film. Meanwhile, when fabricated into flexible devices, the prepared perovskite film exhibits inevitable brittleness and high Young's modulus, seriously weakening the mechanical stability. In this work, we design and synthesize a cross‐linkable fullerene, thioctic acid functionalized C60 fulleropyrrolidinium iodide (FTAI), which has multiple interactions with perovskite components and can finely regulate the crystallization quality of perovskite film. The obtained perovskite film shows an increased grain size and a more matched energy level with the electron transport material, effectively improving the carrier extraction efficiency. The FTAI‐based rigid device achieves a champion efficiency of 14.91 % with enhanced stability. More importantly, the FTAI located at the perovskite grain boundaries could spontaneously cross‐link during the perovskite annealing process, which effectively improves the conductivity and elasticity of grain boundaries, thereby giving the film excellent bending resistance. Finally, the FTAI‐based wearable device yields a record efficiency of 12.35 % and displays robust bending durability, retaining about 90 % of the initial efficiency after 10,000 bending times. [ABSTRACT FROM AUTHOR]

Tin‐based perovskite solar cells (TPSCs) have received increasing attention due to their low toxicity, high theoretical efficiency, and potential applications as wearable devices. However, the inherent fast and uncontrollable crystallization process of tin‐based perovskites results in high defect density in the film. Meanwhile, when fabricated into flexible devices, the prepared perovskite film exhibits inevitable brittleness and high Young's modulus, seriously weakening the mechanical stability. In this work, we design and synthesize a cross‐linkable fullerene, thioctic acid functionalized C60 fulleropyrrolidinium iodide (FTAI), which has multiple interactions with perovskite components and can finely regulate the crystallization quality of perovskite film. The obtained perovskite film shows an increased grain size and a more matched energy level with the electron transport material, effectively improving the carrier extraction efficiency. The FTAI‐based rigid device achieves a champion efficiency of 14.91 % with enhanced stability. More importantly, the FTAI located at the perovskite grain boundaries could spontaneously cross‐link during the perovskite annealing process, which effectively improves the conductivity and elasticity of grain boundaries, thereby giving the film excellent bending resistance. Finally, the FTAI‐based wearable device yields a record efficiency of 12.35 % and displays robust bending durability, retaining about 90 % of the initial efficiency after 10,000 bending times. [ABSTRACT FROM AUTHOR]

Long COVID, or post‐acute sequelae of COVID‐19 (PASC), represents a complex condition with persistent symptoms following SARS‐Cov‐2 infection. The symptoms include fatigue, dyspnoea, cognitive impairment, decreased quality of life in variable levels of severity. Potential mechanisms behind long COVID include vascular damage, immune dysregulation and viral persistence. Diagnosing long COVID involves medical evaluation by multidisciplinary team and assessment of persistent symptoms with scoring systems in development. Treatment strategies are symptom‐focused, encompassing multidisciplinary care, rehabilitation and tailored exercise programmes. Pulmonary rehabilitation, an effective and critical component of long COVID management, has shown promise, particularly for patients with respiratory symptoms such as dyspnoea. These programmes, which combine exercise, breathing techniques, education and psychological support, improve symptoms, quality of life and overall recovery. Innovative technologies, such as telemedicine, wearable devices, telerehabilitation, are transforming long COVID management. Telemedicine facilitates consultations and interventions, eliminating healthcare access barriers. Wearable devices enable remote and continuous monitoring of patients during their rehabilitation activities. Telerehabilitation has proven to be safe and feasible and to have high potential for COVID‐19 recovery. This review provides a concise overview of long COVID, encompassing its definition, prevalence, mechanisms, clinical manifestations, diagnosis and management approaches. It emphasizes the significance of multidisciplinary approach in diagnosis and treatment of long COVID, with focus on pulmonary rehabilitation and innovative technology advances to effectively address the management of long COVID. [ABSTRACT FROM AUTHOR]

Objective: This project aims to develop a wearable device to suppress both the essential and resting tremor and investigate its effectiveness. Materials and Methods: This study details the development and assessment of a wearable device for upper extremity tremors. The wearable device underwent a comprehensive design and a prototype was produced with a 3D-printer. To refine the functionality of the prototype, a motor that mimics tremor was attached to a 3D-printed prototype. Then, the printed prototype was applied to the hand model, and tested its effectiveness for tremor suppressing. The wearable device was further investigated on patients with essential tremor and Parkinson's disease seeking treatment at Neurology Clinics. We recorded the tremor data and processed and visualized the recorded data by using the MatLab (version R2021a, MathWorks Inc., USA) software. Results: The wearable device effectively decreased the tremors both during the simulation phase and the patient testing phase. The data from the wearable device revealed a notable decrease in the amplitude of the tremor. This decrease signifies an achievement of tremor suppression. Conclusion: The prototype of the wearable device signifies a remarkable efficacy in tremor supression. It holds promise for being a potential solution to alleviate the tremor symptoms of essential tremor and Parkinson's disease patients. [ABSTRACT FROM AUTHOR]

Introduction: Although the use of application (app)s and wearable devices supporting diabetes treatment has spread rapidly in recent years, evidence of their impact, especially in combination of them, is limited. TOMOCO™ is a lifestyle improvement support app that features interactive virtual conversations according to the programmed algorithm guiding users toward their goals of lifestyle improvement. We hypothesized that TOMOCO™ in combination with Fitbit, which accurately tracks users' activity level, would encourage people with type 2 diabetes mellitus (T2DM) to change their lifestyles and improve their glycated hemoglobin (HbA1c) levels without changes in conventional therapy. Thus, we performed the present study to explore the effectiveness of this combination in Japanese participants with T2DM who had not achieved their glycemic targets. Methods: In this single-arm exploratory study, participants with T2DM used the TOMOCO™ and Fitbit in addition to the conventional diet/exercise therapy and anti-diabetic drug for 12 weeks. They were provided with feedback/advice by health care providers based on the TOMOCO™ and Fitbit records. The primary endpoint was the change in HbA1c from baseline to the end of the observation period. Data were expressed as mean ± standard deviation. Results: Fifty-nine (96.7%) of the 61 participants (male, 42 [71.2%]; age, 60.1 ± 8.7 years; HbA1c level, 7.48 ± 0.37% at screening) completed the study. At the end of the observation period, the HbA1c was significantly reduced (− 0.41 ± 0.41%, p < 0.001). This trend was consistent across the preselected patient characteristics, including sex, age, and body mass index. However, it was more pronounced in the participants with earlier stages of behavioral changes defined by the transtheoretical model at baseline. Conclusions: The unique features of TOMOCO™ in combination with Fitbit, together with conventional therapy, may promote a healthy lifestyle and thus contribute to improving HbA1c in people with T2DM. Clinical Trial Registration: jRCT1070220007. [ABSTRACT FROM AUTHOR]

Today age of advancement one of the fastest growing fields of the technology is wearable electronics and device. In the recent advancement the wearable devices for on and off body communication is going expeditiously. For the wearable wireless communication, wearable antennas are mostly used due to its compact size, self powered, light weight, low profile, portable wireless communication and sensing. This paper throws light on wearable antennas for on body and off body communication including their applications, advantages and disadvantages. A comparative study is conducted on designing of different on body and off body wearable antennas and parameters of designed antenna such as their size, shape, gain, SAR have been compared and analyzed. In this paper also discussed the impact of the wearable antenna on human body and impact of human body on antenna. [ABSTRACT FROM AUTHOR]

Computer vision (CV)-based systems using cameras and recognition algorithms offer touchless, cost-effective, precise, and versatile hand tracking. These systems allow unrestricted, fluid, and natural movements without the constraints of wearable devices, gaining popularity in human–system interaction, virtual reality, and medical procedures. However, traditional CV-based systems, relying on stationary cameras, are not compatible with mobile applications and demand substantial computing power. To address these limitations, we propose a portable hand-tracking system utilizing the Leap Motion Controller 2 (LMC) mounted on the head and controlled by a single-board computer (SBC) powered by a compact power bank. The proposed system enhances portability, enabling users to interact freely with their surroundings. We present the system's design and conduct experimental tests to evaluate its robustness under variable lighting conditions, power consumption, CPU usage, temperature, and frame rate. This portable hand-tracking solution, which has minimal weight and runs independently of external power, proves suitable for mobile applications in daily life. [ABSTRACT FROM AUTHOR]

In this study, we propose a low-cost piezoelectric flexible pressure sensor fabricated on Kapton® (Kapton™ Dupont) substrate by using aluminum nitride (AlN) thin film, designed for the monitoring of the respiration rate for a fast detection of respiratory anomalies. The device was characterized in the range of 15–30 breaths per minute (bpm), to simulate moderate difficult breathing, borderline normal breathing, and normal spontaneous breathing. These three breathing typologies were artificially reproduced by setting the expiratory to inspiratory ratios (E:I) at 1:1, 2:1, 3:1. The prototype was able to accurately recognize the breath states with a low response time (~35 ms), excellent linearity (R2 = 0.997) and low hysteresis. The piezoelectric device was also characterized by placing it in an activated carbon filter mask to evaluate the pressure generated by exhaled air through breathing acts. The results indicate suitability also for the monitoring of very weak breath, exhibiting good linearity, accuracy, and reproducibility, in very low breath pressures, ranging from 0.09 to 0.16 kPa. These preliminary results are very promising for the future development of smart wearable devices able to monitor different patients breathing patterns, also related to breathing diseases, providing a suitable real-time diagnosis in a non-invasive and fast way. [ABSTRACT FROM AUTHOR]

Objective This study aimed to investigate the intensity of the physical work of workers with typical tasks in railway tunnel construction in order to provide support for scientifically monitoring workers' health. Methods From July to August 2022, 24 workers with different tasks(3 electric welders, 7 erectors, 4 waterproofers, and 10 steel bar workers)were recruited in tunnel construction site. Their physical activities were recorded for 24-hours for 3 - 5 consecutive days using the energy consumption meter on the dominant wrist. The intensity of physical work was estimated based on counts per minute, energy consumption, and metabolic equivalent. One -way ANOVA tests were used to compare differences in the intensity of physical work among different workers. Results Finally, 23 workers completed the investigation. Except for the maximum counts, significant statistical differences were detected in total counts, average counts, and counts per minute among the waterproofers, steel bar workers, electric welders, and erecters (P < 0.05). Particularly, the activity meter value of waterproofing workers was the largest (P < 0.05). The energy expenditure per unit time for the four types of work was (1 303.0 ± 78.5), (760.8 ± 24.5), (554.8 ± 91.4) and (521.9 ± 30.4) kcals (1 kcal = 4.184 kJ), and the differences between the groups were statistically significant (F = 5.72, P = 0.006); the metabolic equivalents were (2.89 ± 0.22), (2.57 ± 0.39), (1.81 ± 0.07) and (1.70 ± 0.27) METs, respectively. The differences between the groups were statistically significant (F = 6.99, P = 0.002). Conclusions The intensity of physical work varied greatly among workers with different tasks in railway tunnel construction. The intensity of physical work of the waterproofers was equivalent to Level Ⅲ(heavy intensity), while Level Ⅱ (medium intensity)was for the other workers. The manager in tunnel construction should pay attention to the differences in intensity of physical work among workers with different tasks, reasonably set labor quotas, and allocate human resources for protecting workers' physical and mental health. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF) is the most common arrhythmia and may easily lead to various complications. Therefore, precision medical methods are needed to identify and enhance AF detection to achieve early diagnosis and treatment. Artificial intelligence-based wearable devices are of great value for the screening and management of AF patients. This article reviews the relevant literature on recent applications of such devices for AF screening. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF) is one of the most common arrhythmias. It is characterized by concealment, paroxysmal nature, complexity, and high mortality and disability rate; the prevalence rate of AF is on the rise. The new emergence of artificial intelligence technology breaks through the limitations of traditional methods of AF screening, showing unique advantages and broad application prospects in the screening, diagnosis and prediction of AF. Intelligent wearable devices have higher feasibility, specificity and sensitivity in the screening of AF, with high cost-effectiveness in clinical application. [ABSTRACT FROM AUTHOR]