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This study aimed to validate the automated temporal analysis of countermovement vertical jump (CMJ) using MMPose, a markerless pose estimation framework, by comparing it with the gold-standard 3D marker-based motion capture system. Twelve participants performed five CMJ trials, which were simultaneously recorded using the marker-based system and two smartphone cameras capturing both sides of the body. Key kinematic points, including center of mass (CoM) and toe trajectories, were analyzed to determine jump phases and temporal variables. The agreement between methods was assessed using Bland–Altman analysis, root mean square error (RMSE), and Pearson's correlation coefficient (r), while consistency was evaluated via intraclass correlation coefficient (ICC 3,1) and two-way repeated-measures ANOVA. Cohen's effect size (d) quantified the practical significance of differences. Results showed strong agreement (r > 0.98) with minimal bias and narrow limits of agreement for most variables. The markerless system slightly overestimated jump height and CoM vertical velocity, but ICC values (ICC > 0.91) confirmed strong reliability. Cohen's d values were near zero, indicating trivial differences, and no variability due to recording side was observed. Overall, MMPose proved to be a reliable alternative for in-field CMJ analysis, supporting its broader application in sports and rehabilitation settings. [ABSTRACT FROM AUTHOR]

This article describes a study exploring the expressive and creative potential of dance phrase onsets and endings in interactive dance, using an artistic research approach. After describing the context and background of interactive dance and relevant perceptual issues, the technical setup is presented, both in terms of the performance area, sensors and other hardware, and software. The main part of the article is concerned with the specific movement-sound mappings and their relation to the dancer's movement choices in four different sections in the performance that the project resulted in, entitled Beginnings and Endings - Study I. Subsequently, the process and performance are evaluated, specifically focusing on the performer's perspective. The most interesting points from the evaluation are then discussed with reference to the presented mappings, related movement choices, and relevant research literature. Findings include that the dancer experienced an increased awareness of beginnings and endings in different sections of the performance, that the affordances of different mappings were explored in different ways and to different degrees, and that some of this could be ascribed to a dynamic between liberation and restriction. [ABSTRACT FROM AUTHOR]

Pathological gait in patients with Hakim's disease (HD, synonymous with idiopathic normal-pressure hydrocephalus; iNPH), Parkinson's disease (PD), and cervical myelopathy (CM) has been subjectively evaluated in this study. We quantified the characteristics of upper and lower limb movements in patients with pathological gait. We analyzed 1491 measurements of 1 m diameter circular walking from 122, 12, and 93 patients with HD, PD, and CM, respectively, and 200 healthy volunteers using the Three-Dimensional Pose Tracker for Gait Test. Upper and lower limb movements of 2D coordinates projected onto body axis sections were derived from estimated 3D relative coordinates. The hip and knee joint angle ranges on the sagittal plane were significantly smaller in the following order: healthy > CM > PD > HD, whereas the shoulder and elbow joint angle ranges were significantly smaller, as follows: healthy > CM > HD > PD. The outward shift of the leg on the axial plane was significantly greater, as follows: healthy < CM < PD < HD, whereas the outward shift of the upper limb followed the order of healthy > CM > HD > PD. The strongest correlation between the upper and lower limb movements was identified in the angle ranges of the hip and elbow joints on the sagittal plane. The lower and upper limb movements during circular walking were correlated. Patients with HD and PD exhibited reduced back-and-forth swings of the upper and lower limbs. [ABSTRACT FROM AUTHOR]

Hexapod robots have gained significant attention due to their potential applications in complex terrains and dynamic environments. However, traditional inverse kinematics approaches often face challenges in meeting the precision required for adaptive omnidirectional movement. This work introduces a novel approach to addressing these challenges through the Directed Angular Restitution (DAR) method. The DAR method offers significant innovation by simplifying the calculation of rotational transformations necessary for aligning vectors across different planes, thus enhancing control, stability, and accuracy in robotic applications. Unlike conventional methods, the DAR method extends the range of trigonometric functions and incorporates spin functions to ensure continuous and smooth trajectory tracking. This innovative approach has been rigorously tested on a hexapod robot model, demonstrating superior performance in movement precision and stability. The results confirm that the DAR method provides a robust and scalable solution for the inverse kinematics of hexapod robots, making it a critical advancement for applications in robotics and automation where precise control and adaptability are paramount. [ABSTRACT FROM AUTHOR]

Purpose: Develop a true real‐time implementation of MR signature matching (MRSIGMA) for free‐breathing 3D MRI with sub‐200 ms latency on the Elekta Unity 1.5T MR‐Linac. Methods: MRSIGMA was implemented on an external computer with a network connection to the MR‐Linac. Stack‐of‐stars with partial kz sampling was used to accelerate data acquisition and ReconSocket was employed for simultaneous data transmission. Movienet network computed the 4D MRI motion dictionary and correlation analysis was used for signature matching. A programmable 4D MRI phantom was utilized to evaluate MRSIGMA with respect to a ground‐truth translational motion reference. In vivo validation was performed on patients with pancreatic cancer, where 15 patients were employed to train Movienet and 7 patients to test the real‐time implementation of MRSIGMA. Dice coefficients between real‐time MRSIGMA and a retrospectively computed 4D reference were used to evaluate motion tracking performance. Results: Motion dictionary was computed in under 5 s. Signature acquisition and matching presented 173 ms latency on the phantom and 193 ms on patients. MRSIGMA presented a mean error of 1.3–1.6 mm for all phantom experiments, which was below the 2 mm acquisition resolution along the motion direction. The Dice coefficient over time between MRSIGMA and reference contours was 0.88 ± 0.02 (GTV), 0.87 ± 0.02(duodenum‐stomach), and 0.78 ± 0.02(small bowel), demonstrating high motion tracking performance for both tumor and organs at risk. Conclusion: The real‐time implementation of MRSIGMA enabled true real‐time free‐breathing 3D MRI with sub‐200 ms imaging latency on a clinical MR‐Linac system, which can be used for treatment monitoring, adaptive radiotherapy and dose accumulation mapping in tumors affected by respiratory motion. [ABSTRACT FROM AUTHOR]

This study examined a novel method to create a long and narrow calibrated capture volume for tracking objects. The methodology relies on the reflection of parallel distance-measuring lasers. Images of a board, blocking the lasers as it is moved through the field of interest, were assembled into a virtual calibration fixture. The method accommodates large calibration volumes and can be used with multiple cameras, providing a consistent absolute positional reference that is difficult to achieve with large mechanical calibration boards. This study considered a 17.4 m long tracking volume. A 0.9 m long rod was tracked throughout the calibrated volume where its average tracked length was within 0.2% of its measured length. The speed of balls traveling through the calibrated volume were within 0.1% of independent speed sensors. The average residual error of a ball's tracked trajectory and a polynomial fit was within 1.5 mm. The method shows promise as an efficient means of calibrating large calibration volumes with multiple camera pairs. [ABSTRACT FROM AUTHOR]

Crafting a single, versatile physics-based controller that can breathe life into interactive characters across a wide spectrum of scenarios represents an exciting frontier in character animation. An ideal controller should support diverse control modalities, such as sparse target keyframes, text instructions, and scene information. While previous works have proposed physically simulated, scene-aware control models, these systems have predominantly focused on developing controllers that each specializes in a narrow set of tasks and control modalities. This work presents MaskedMimic, a novel approach that formulates physics-based character control as a general motion inpainting problem. Our key insight is to train a single unified model to synthesize motions from partial (masked) motion descriptions, such as masked keyframes, objects, text descriptions, or any combination thereof. This is achieved by leveraging motion tracking data and designing a scalable training method that can effectively utilize diverse motion descriptions to produce coherent animations. Through this process, our approach learns a physics-based controller that provides an intuitive control interface without requiring tedious reward engineering for all behaviors of interest. The resulting controller supports a wide range of control modalities and enables seamless transitions between disparate tasks. By unifying character control through motion inpainting, MaskedMimic creates versatile virtual characters. These characters can dynamically adapt to complex scenes and compose diverse motions on demand, enabling more interactive and immersive experiences. [ABSTRACT FROM AUTHOR]

Accurate and efficient motion estimation is a crucial component of real-time ultrasound elastography (USE). However, obtaining radiofrequency ultrasound (RF) data in clinical practice can be challenging. In contrast, although B-mode (BM) data is readily available, elastographic data derived from BM data results in sub-optimal elastographic images. Furthermore, existing conventional ultrasound devices (e.g., portable devices) cannot provide elastography modes, which has become a significant obstacle to the widespread use of traditional ultrasound devices. To address the challenges above, we developed a teacher-student guided knowledge distillation for an unsupervised convolutional neural network (TSGUPWC-Net) to improve the accuracy of BM motion estimation by employing a well-established convolutional neural network (CNN) named modified pyramid warping and cost volume network (MPWC-Net). A pre-trained teacher model based on RF is utilized to guide the training of a student model using BM data. Innovations outlined below include employing spatial attention transfer at intermediate layers to enhance the guidance effect of the model. The loss function consists of smoothness of the displacement field, knowledge distillation loss, and intermediate layer loss. We evaluated our method on simulated data, phantoms, and in vivo ultrasound data. The results indicate that our method has higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values in axial strain estimation than the model trained on BM. The model is unsupervised and requires no ground truth labels during training, making it highly promising for motion estimation applications. [ABSTRACT FROM AUTHOR]

This research proposes a sensor for tracking the motion of a human head via optical tactile sensing. It implements the use of a fibrescope a non-metal alternative to a webcam. Previous works have included robotics grippers to mimic the sensory features of human skin, that used monochrome cameras and depth cameras. Tactile sensing has shown advantages in feedback-based interactions between robots and their environment. The methodology in this paper is utilised to track motion of objects in physical contact with these sensors to replace external camera based motion capture systems. Our immediate application is related to detection of human head motion during radiotherapy procedures. The motion was analysed in two degrees of freedom, respective to the tactile sensor (translational in z-axis, and rotational around y-axis), to produce repeatable and accurate results. The movements were stimulated by a robot arm, which also provided ground truth values from its end- effector. The fibrescope was implemented to ensure the device's compatibility with electromagnetic waves. The cameras and the ground truth values were time synchronised using robotics operating systems tools. Image processing methods were compared between grayscale and binary image sequences, followed by motion tracking estimation using deterministic approaches. These included Lukas-Kanade Optical Flow and Simple Blob Detection, by OpenCV. The results showed that the grayscale image processing along with the Lukas- Kanade algorithm for motion tracking can produce better tracking abilities, although further exploration to improve the accuracy is still required. [ABSTRACT FROM AUTHOR]

The integration of Artificial Intelligence (AI) into physical education (PE) represents a transformative shift in how physical learning and performance are approached. This paper explores the multifaceted role of AI in enhancing educational experiences and athletic performance within PE settings. By analyzing various AI technologies, including wearable devices, motion tracking systems, and intelligent coaching applications, the paper highlights how these innovations facilitate personalized learning, improve skill acquisition, and foster student engagement. AI-driven analytics enable educators to tailor fitness programs to individual student needs, promoting optimal physical development and performance enhancement. Moreover, the study examines the potential of AI in data collection and analysis, which aids in monitoring progress and providing real-time feedback to students and instructors. Through a comprehensive review of current literature, the paper identifies key challenges and opportunities presented by AI in PE, including concerns related to privacy, equity in access to technology, and the necessity for educator training. The findings suggest that when effectively implemented, AI not only enhances the learning environment but also empowers educators to better support students in achieving their physical education goals. This review underscores the importance of adopting AI tools in PE curricula to create dynamic, inclusive, and effective learning experiences that prepare students for lifelong physical activity. Ultimately, this paper advocates for ongoing research and collaboration between educators, technologists, and policymakers to fully realize the potential of AI in revolutionizing physical education and improving student outcomes in health and fitness. [ABSTRACT FROM AUTHOR]

In this era of endoscopic surgery, feedback from recorded surgical videos is useful and efficient; therefore, effective methods of obtaining this feedback are needed. We analyzed surgical videos using motion analysis software and verified the usefulness of visualizing and objectively evaluating surgical procedures. We measured the grasping and traction angles of the vascular sheath when using forceps and the trajectory of the forceps tip for the upper pulmonary vein during right upper lobectomy during video‐assisted thoracoscopic surgery performed by three trainers and trainees. Compared with the trainers, the trainees exhibited insufficient traction of the vascular sheath, performed many slow and unnecessary manipulations, and sometimes performed sudden and fast movements. By visualizing the surgical procedures, the trainee will be better able to identify dangerous or futile movements. It may also make it easier to objectively recognize improvements in one's technique. Motion analysis software could allow for efficient surgical education and self‐learning. [ABSTRACT FROM AUTHOR]

Aim: The supine sleeping position in the prevention of sudden infant death syndrome in preterm infants is poorly understood. We aimed to investigate the effect of sleep posture on cardiorespiratory parameters and movement patterns in preterm infants close to discharge. Methods: This observational study included neonates born in 2022 at the University Hospital Schleswig‐Holstein, Lübeck, Germany. Motion sensor data, heart rate, respiratory rate and oxygen saturation were recorded for infants with postconceptional age 35–37 weeks during sleep in the prone and supine positions. Results: We recorded data from 50 infants, born at 31 (24–35) weeks of gestation (mean(range)), aged 5.2 ± 3.7 weeks (mean ± SD), of whom 48% were female. Five typical movement patterns were identified. In the prone position, the percentage of calm, regular breathing was higher and active movement was less frequent when compared to the supine position. The percentage of calm irregular breathing, number of apnoeas, bradycardias, desaturations and vital sign changes were not influenced by position. Conclusion: The prone position seems to be associated with a higher arousal threshold. The supine position appears advantageous for escape from life‐threatening situations such as sudden infant death syndrome. [ABSTRACT FROM AUTHOR]

The emerging field of canine science has been slow in adopting automated approaches for data analysis. However, with the dramatic increase in the volume and complexity of the collected behavioral data, this is now beginning to change. This paper aims to systematize the field of automation in canine science. We provide an examination of current automation processes and pipelines by providing a literature review of state-of-the-art studies applying automation in this field. In addition, via an empirical study with researchers in animal behavior, we explore their perceptions and attitudes toward automated approaches for better understanding barriers for a wider adoption of automation. The insights derived from this research could facilitate more effective and widespread utilization of automation within canine science, addressing current challenges and enhancing the analysis of increasingly complex and voluminous behavioral data. This could potentially revolutionize the field, allowing for more objective and quantifiable assessments of dog behavior, which would ultimately contribute to our understanding of dog-human interactions and canine welfare. [ABSTRACT FROM AUTHOR]

Developing mmWave radar sensors for indoor crowd motion sensing and tracking faces a critical challenge: the scarcity of large-scale, high-quality training data. Traditional human experiments encounter logistical complexities, ethical considerations, and safety issues. Replicating precise human movements across trials introduces noise and inconsistency into the data. To address this, this study proposes a novel solution: a movable platform equipped with a life-size mannequin to generate realistic and diverse data points for mmWave radar training and testing. Unlike human subjects, the platform allows precise control over movements, optimising sensor placement relative to the target object. Preliminary optimisation results reveal that sensor height impacts tracking performance, with an optimal sensor placement above the test subject yields the best results. The results also reveal that the 3D data format outperforms 2D data in accuracy despite having fewer frames. Additionally, analysing height distribution using 3D data highlights the importance of the sensor angle—15° downwards from the horizontal plane. [ABSTRACT FROM AUTHOR]

Conventional maritime communication struggles to provide high data rate services for Internet of Things (IoT) devices due to the variability of maritime environments, making it challenging to ensure consistent connectivity for onboard sensors and devices. To resolve this, we perform mathematical modeling of the maritime channel and compare it with real measurement data. Through the modeled channel, we verify the received beam gain at buoys on the ocean surface. Additionally, leveraging the modeled wave motions, we estimate future angles of the buoy to use the Extended Kalman Filter (EKF) for design beamforming strategies that adapt to the evolving maritime environment over time. We further validate the effectiveness of these strategies by assessing the results from an outage probability perspective. focuses on improving maritime communication by developing a dynamic model of the maritime channel and implementing a Kalman filter-based buoy motion tracking system. This system is designed to enable precise beamforming, a technique used to direct communication signals more accurately. By improving beamforming, the aim is to enhance the quality of communication links, even in challenging maritime conditions like rough seas and varying sea states. In our simulations that consider realistic wave motions, you've observed significant improvements in link quality due to the enhanced beamforming technique. These improvements are particularly notable in environments with high sea states, where communication challenges are typically more pronounced. The progress made in this area is not just a technical achievement; it has broad implications for the future of maritime communication technologies. This paper promises to revolutionize the way we approach communication in maritime environments, paving the way for more reliable and efficient information exchange on the seas. [ABSTRACT FROM AUTHOR]

Patients with motor impairments (e.g., stroke, bone fracture, Parkinson's) are sensitive to the wearing experience of rehabilitation devices, and they often have difficulty accurately positioning them at an accurate position. While solutions involving optical systems or IMUs could potentially help alleviate the issue, they often introduce other challenges such as privacy concerns or discomforting experiences. With the emergence of wearable soft sensors during the last few decades, researchers widely apply soft sensors in rehabilitation to improve the wearing experience. However, these approaches have primarily focused on analyzing the sensor readings to improve accuracy rather than addressing the needs of patients and healthcare providers, and there is a lack of comprehensive design investigation and need assessment based on soft sensor-based rehabilitation systems for motor-impaired patients and their doctors. In this study, we developed an application, RehabFAB, utilizing fabric sensors for rehabilitation purposes. Besides, we evaluated our application and device and investigated the needs of patients and doctors for potential home rehabilitation applications. The investigation was conducted through thematic analysis, correlation analysis and System Usability Scale. The experimental results validated the efficacy, reliability and usability of our approach, with a SUS score of 81.75. In addition, the RehabFAB meets the expectations of motor-impaired patients and medical professionals as a home rehabilitation tool. Our core contributions lie in a thorough evaluation of the needs of motor-impaired patients in order to design a stable and reliable motion-tracking device based on soft sensors for their recovery. [ABSTRACT FROM AUTHOR]

The increasing demand for laparoscopic surgery due to its cosmetic benefits and rapid post-surgery recovery is juxtaposed with a shortage of surgical support staff. This juxtaposition highlights the necessity for improved camera management in laparoscopic procedures, encompassing positioning, zooming, and focusing. Our feasibility study introduces the information and communications technology (ICT) laparoscopy system designed to aid solo laparoscopic surgery. This system tracks a surgeon's body motion using a controller, manipulating an embedded camera to focus on specific surgical areas. It comprises a camera module, a camera movement controller, and a motor within the main body, operating connected wires according to controller commands for camera movement. Surgeon movements are detected by an inertial measurement unit (IMU) sensor, facilitating precise camera control. Additional features include a foot pedal switch for motion tracking, a dedicated trocar for main body stability, and a display module. The system's effectiveness was evaluated using an abdomen phantom model and animal experimentation with a porcine model. The camera responded to human movement within 100 ms, a delay that does not significantly affect procedural performance. The ICT laparoscopy system with advanced motion-tracking technology is a promising tool for solo laparoscopic surgery, potentially improving surgical outcomes and overcoming staff shortages. [ABSTRACT FROM AUTHOR]

Optical mapping is a widely used tool to record and visualize the electrophysiological properties in a variety of myocardial preparations such as Langendorff-perfused isolated hearts, coronary-perfused wedge preparations, and cell culture monolayers. Motion artifact originating from the mechanical contraction of the myocardium creates a significant challenge to performing optical mapping of contracting hearts. Hence, to minimize the motion artifact, cardiac optical mapping studies are mostly performed on non-contracting hearts, where the mechanical contraction is removed using pharmacological excitation-contraction uncouplers. However, such experimental preparations eliminate the possibility of electromechanical interaction, and effects such as mechano-electric feedback cannot be studied. Recent developments in computer vision algorithms and ratiometric techniques have opened the possibility of performing optical mapping studies on isolated contracting hearts. In this review, we discuss the existing techniques and challenges of optical mapping of contracting hearts.

With the refinement and scientificization of sports training, the demand for sports performance analysis in the field of sports has gradually become prominent. In response to the problem of low accuracy and poor real-time performance in human pose estimation during sports, this article focused on volleyball sports and used a combination model of OpenPose and DeepSORT to perform real-time pose estimation and tracking on volleyball videos. First, the OpenPose algorithm was adopted to estimate the posture of the human body region, accurately estimating the coordinates of key points, and assisting the model in understanding the posture. Then, the DeepSORT model target tracking algorithm was utilized to track the detected human pose information in real-time, ensuring consistency of identification and continuity of position between different frames. Finally, using unmanned aerial vehicles as carriers, the YOLOv4 object detection model was used to perform real-time human pose detection on standardized images. The experimental results on the Volleyball Activity Dataset showed that the OpenPose model had a pose estimation accuracy of 98.23%, which was 6.17% higher than the PoseNet model. The overall processing speed reached 16.7 frames/s. It has good pose recognition accuracy and real-time performance and can adapt to various volleyball match scenes.

This study examined the efficacy of an optimized DeepLabCut (DLC) model in motion capture, with a particular focus on the sit-to-stand (STS) movement, which is crucial for assessing the functional capacity in elderly and postoperative patients. This research uniquely compared the performance of this optimized DLC model, which was trained using 'filtered' estimates from the widely used OpenPose (OP) model, thereby emphasizing computational effectiveness, motion-tracking precision, and enhanced stability in data capture. Utilizing a combination of smartphone-captured videos and specifically curated datasets, our methodological approach included data preparation, keypoint annotation, and extensive model training, with an emphasis on the flow of the optimized model. The findings demonstrate the superiority of the optimized DLC model in various aspects. It exhibited not only higher computational efficiency, with reduced processing times, but also greater precision and consistency in motion tracking thanks to the stability brought about by the meticulous selection of the OP data. This precision is vital for developing accurate biomechanical models for clinical interventions. Moreover, this study revealed that the optimized DLC maintained higher average confidence levels across datasets, indicating more reliable and accurate detection capabilities compared with standalone OP. The clinical relevance of these findings is profound. The optimized DLC model's efficiency and enhanced point estimation stability make it an invaluable tool in rehabilitation monitoring and patient assessments, potentially streamlining clinical workflows. This study suggests future research directions, including integrating the optimized DLC model with virtual reality environments for enhanced patient engagement and leveraging its improved data quality for predictive analytics in healthcare. Overall, the optimized DLC model emerged as a transformative tool for biomechanical analysis and physical rehabilitation, promising to enhance the quality of patient care and healthcare delivery efficiency. [ABSTRACT FROM AUTHOR]

Introduction: Treatment of both simple and complex patella fractures is a challenging clinical problem. Although tension band wiring has been the standard of care, it can be associated with high complication rates. The aim of this study was to investigate the biomechanical performance of recently developed lateral rim variable angle locking plates versus tension band wiring used for fixation of simple and complex patella fractures. Materials and methods: Sixteen pairs of human anatomical knees were used to simulate either two-part transverse simple AO/OTA 34-C1 or five-part complex AO/OTA 34-C3 patella fractures by means of osteotomies, with each fracture model created in eight pairs. The complex fracture pattern was characterized by a medial and a lateral proximal fragment, together with an inferomedial, an inferolateral, and an inferior (central distal) fragment mimicking comminution around the distal patellar pole. The specimens with simple fractures were pairwise assigned for fixation with either tension band wiring through two parallel cannulated screws or a lateral rim variable angle locking plate. The knees with complex fractures were pairwise treated with either tension band wiring through two parallel cannulated screws plus circumferential cerclage wiring or a lateral rim variable angle locking plate. Each specimen was tested over 5000 cycles by pulling on the quadriceps tendon, simulating active knee extension and passive knee flexion within the range of 90° flexion to full extension. Interfragmentary movements were captured via motion tracking. Results: For both fracture types, the articular displacements measured between the proximal and distal fragments at the central patella aspect between 1000 and 5000 cycles, together with the relative rotations of these fragments around the mediolateral axis were all significantly smaller following the lateral rim variable angle locked plating compared with tension band wiring, p ≤ 0.01. Conclusions: From a biomechanical perspective, lateral rim variable angle locked plating of both simple and complex patella fractures provides superior construct stability versus tension band wiring under dynamic loading. [ABSTRACT FROM AUTHOR]

This study examined the relation between movement amplitude and tempo during self-paced rhythmic finger tapping to test a preferred velocity account of the preferred tempo construct. Preferred tempo refers to the concept that individuals have preferences for the pace of actions or events in their environment (e.g., the desired pace of walking or tempo of music). The preferred velocity hypothesis proposes that assessments of preferred tempo do not represent a pure time preference independent of spatial movement characteristics, but rather reflects a preference for an average movement velocity, predicting that preferred tempo will depend on movement amplitude. We tested this by having participants first perform a novel spontaneous motor amplitude (SMA) task in which they repetitively tapped their finger at their preferred amplitude without instructions about tapping tempo. Next, participants completed the spontaneous motor tempo (SMT) task in which they tapped their finger at their preferred tempo without instructions about tapping amplitude. Finally, participants completed a target amplitude version of the SMT task where they tapped at their preferred tempo at three target amplitudes (low, medium, and high). Participants (1) produced similar amplitudes and tempi regardless of instructions to produce either their preferred amplitude or preferred tempo, maintaining the same average movement velocity across SMA and SMT tasks and (2) altered their preferred tempo for different target amplitudes in the direction predicted by their estimated preferred velocity from the SMA and SMT tasks. Overall, results show the interdependence of movement amplitude and tempo in tapping assessments of preferred tempo. [ABSTRACT FROM AUTHOR]

Ultrasonic transit time (TT)-based local pulse wave velocity (PWV) measurement is defined as the distance between two beam positions on a segment of common carotid artery (CCA) divided by the TT in the pulse wave propagation. However, the arterial wall motions (AWMs) estimated from ultrasonic radio frequency (RF) signals with a limited number of frames using the motion tracking are typically discrete. In this work, we develop a method involving motion tracking combined with reconstructive interpolation (MTRI) to reduce the quantification errors in the estimated PWs, and thereby improve the accuracy of the TT-based local PWV measurement for CCA. For each beam position, normalized cross-correlation functions (NCCFs) between the reference (the first frame) and comparison (the remaining frames) RF signals are calculated. Thereafter, the reconstructive interpolation is performed in the neighborhood of the NCCFs' peak to identify the interpolation-deduced peak locations, which are more exact than the original ones. According to which, the improved AWMs are obtained to calculate their TT along a segment of the CCA. Finally, the local PWV is measured by applying a linear regression fit to the time-distance result. In ultrasound simulations based on the pulse wave propagation models of young, middle-aged, and elderly groups, the MTRI method with different numbers of interpolated samples was used to estimate AWMs and local PWVs. Normalized root mean squared errors (NRMSEs) between the estimated and preset values of the AWMs and local PWVs were calculated and compared with ones without interpolation. The means of the NRMSEs for the AWMs and local PWVs based on the MTRI method with one interpolated sample decrease from 1.14% to 0.60% and 7.48% to 4.61%, respectively. Moreover, Bland-Altman analysis and coefficient of variation were used to validate the performance of the MTRI method based on the measured local PWVs of 30 healthy subjects. In conclusion, the reconstructive interpolation for the pulse wave estimation improves the accuracy and repeatability of the carotid local PWV measurement. Ultrasonic transit time-based local pulse wave velocity (PWV) measurement is defined as the distance between two beam positions on a segment of common carotid artery (CCA) divided by the transit time of the pulse wave (PW). However, PWs estimated from ultrasonic radio frequency (RF) signals with a limited number of frames using the motion tracking are typically discontinuous. In this work, a method that involves motion tracking combined with reconstructive interpolation (MTRI) is proposed for PW estimation to improve local PWV measurement. For each beam position, normalized cross-correlation functions (NCCFs) between the reference (the first frame) and comparison (the remaining frames) RF signals are calculated. Thereafter, the reconstructive interpolation is performed in the neighborhood of the NCCFs' peak to identify the interpolation-deduced peak locations, which are more exact than the original ones. According to which, the improved PWs are obtained to calculate their transit time along a segment of the CCA. Finally, the local PWV is measured by applying a linear regression fit to the time-distance result. In ultrasound simulations based on the PW propagation models of young, middle-aged, and elderly groups, the MTRI method with different numbers of interpolated samples was used to estimate PWs and local PWVs. Normalized root mean squared errors (NRMSEs) between the estimated and preset values of the PWs and local PWVs were calculated and compared with ones without interpolation. The means of the NRMSEs for the PWs and local PWVs based on the MTRI method with one interpolated sample decrease from 1.14% to 0.60% and 7.48% to 4.61%, respectively. Moreover, Bland-Altman analysis and coefficient of variation were used to validate the performance of the MTRI method based on the measured local PWVs of 30 healthy subjects. In conclusion, the MTRI method can improve the PW estimation and thus afford more accurate local PWV measurement. [ABSTRACT FROM AUTHOR]

Acoustic motion tracking is rapidly evolving with various applications. However, existing approaches still have some limitations. Tracking based on single-frequency continuous wave (CW) faces cumulative errors in tracking and limited accuracy in tracking the absolute location of the target. Tracking based on frequency-modulated continuous wave (FMCW) faces errors introduced by the Doppler and multipath effects. To overcome these limitations, we propose FusionTrack, a novel device-free motion-tracking approach that leverages the fusion of CW and FMCW signals. We eliminate the absolute tracking errors of FMCW-based tracking by compensating for Doppler frequency offsets with the results of CW-based relative tracking. Furthermore, we address the static multipath with down-sampling and filtering and mitigate the dynamic multipath with chirp aggregation. We employ a Kalman filter-based fusion of relative and absolute tracking to enhance accuracy further. We implement FusionTrack on Android smartphones for real-time tracking and perform extensive experiments. The results show that FusionTrack achieves real-time 1D tracking with an accuracy of 1.5 mm, which is 46% better than the existing approaches and extends the 1D tracking range to 2.2 m, which is 3.1× of the existing approaches. FusionTrack also achieves a 2D tracking accuracy of 4.5 mm. [ABSTRACT FROM AUTHOR]

This paper introduces a method for measuring 3D tibiofemoral kinematics using a multi-channel A-mode ultrasound system under dynamic conditions. The proposed system consists of a multi-channel A-mode ultrasound system integrated with a conventional motion capture system (i.e., optical tracking system). This approach allows for the non-invasive and non-radiative quantification of the tibiofemoral joint's six degrees of freedom (DOF). We demonstrated the feasibility and accuracy of this method in the cadaveric experiment. The knee joint's motions were mimicked by manually manipulating the leg through multiple motion cycles from flexion to extension. To measure it, six custom ultrasound holders, equipped with a total of 30 A-mode ultrasound transducers and 18 optical markers, were mounted on various anatomical regions of the lower extremity of the specimen. During experiments, 3D-tracked intra-cortical bone pins were inserted into the femur and tibia to measure the ground truth of tibiofemoral kinematics. The results were compared with the tibiofemoral kinematics derived from the proposed ultrasound system. The results showed an average rotational error of 1.51 ± 1.13° and a translational error of 3.14 ± 1.72 mm for the ultrasound-derived kinematics, compared to the ground truth. In conclusion, this multi-channel A-mode ultrasound system demonstrated a great potential of effectively measuring tibiofemoral kinematics during dynamic motions. Its improved accuracy, nature of non-invasiveness, and lack of radiation exposure make this method a promising alternative to incorporate into gait analysis and prosthetic kinematic measurements later. [ABSTRACT FROM AUTHOR]

Background: Position verification and motion monitoring are critical for safe and precise radiotherapy (RT). Existing approaches to these tasks based on visible light or x‐ray are suboptimal either because they cannot penetrate obstructions to the patient's skin or introduce additional radiation exposure. The low‐cost mmWave radar is an ideal solution for these tasks as it can monitor patient position and motion continuously throughout the treatment delivery. Purpose: To develop and validate frequency‐modulated continuous wave (FMCW) mmWave radars for position verification and motion tracking during RT delivery. Methods: A 77 GHz FMCW mmWave module was used in this study. Chirp Z Transform‐based (CZT) algorithm was developed to process the intermediate frequency (IF) signals. Absolute distances to flat Solid Water slabs and human shape phantoms were measured. The accuracy of absolute distance and relative displacement were evaluated. Results: Without obstruction, mmWave based on the CZT algorithm was able to detect absolute distance within 1 mm for a Solid Water slab that simulated the reflectivity of the human body. Through obstructive materials, the mmWave device was able to detect absolute distance within 5 mm in the worst case and within 3.5 mm in most cases. The CZT algorithm significantly improved the accuracy of absolute distance measurement compared with Fast Fourier Transform (FFT) algorithm and was able to achieve submillimeter displacement accuracy with and without obstructions. The surface‐to‐skin distance (SSD) measurement accuracy was within 8 mm in the anterior of the phantom. Conclusions: With the CZT signal processing algorithm, the mmWave radar is able to measure the absolute distance to a flat surface within 1 mm. But the absolute distance measurement to a human shape phantom is as large as 8 mm at some angles. Further improvement is necessary to improve the accuracy of SSD measurement to uneven surfaces by the mmWave radar. [ABSTRACT FROM AUTHOR]

This research proposes a sensor for tracking the motion of a human head via optical tactile sensing. It implements the use of a fibrescope a non-metal alternative to a webcam. Previous works have included robotics grippers to mimic the sensory features of human skin, that used monochrome cameras and depth cameras. Tactile sensing has shown advantages in feedback-based interactions between robots and their environment. The methodology in this paper is utilised to track motion of objects in physical contact with these sensors to replace external camera based motion capture systems. Our immediate application is related to detection of human head motion during radiotherapy procedures. The motion was analysed in two degrees of freedom, respective to the tactile sensor (translational in z-axis, and rotational around y-axis), to produce repeatable and accurate results. The movements were stimulated by a robot arm, which also provided ground truth values from its end-effector. The fibrescope was implemented to ensure the device’s compatibility with electromagnetic waves. The cameras and the ground truth values were time synchronised using robotics operating systems tools. Image processing methods were compared between grayscale and binary image sequences, followed by motion tracking estimation using deterministic approaches. These included Lukas-Kanade Optical Flow and Simple Blob Detection, by OpenCV. The results showed that the grayscale image processing along with the Lukas-Kanade algorithm for motion tracking can produce better tracking abilities, although further exploration to improve the accuracy is still required.

The emerging field of canine science has been slow in adopting automated approaches for data analysis. However, with the dramatic increase in the volume and complexity of the collected behavioral data, this is now beginning to change. This paper aims to systematize the field of automation in canine science. We provide an examination of current automation processes and pipelines by providing a literature review of state-of-the-art studies applying automation in this field. In addition, via an empirical study with researchers in animal behavior, we explore their perceptions and attitudes toward automated approaches for better understanding barriers for a wider adoption of automation. The insights derived from this research could facilitate more effective and widespread utilization of automation within canine science, addressing current challenges and enhancing the analysis of increasingly complex and voluminous behavioral data. This could potentially revolutionize the field, allowing for more objective and quantifiable assessments of dog behavior, which would ultimately contribute to our understanding of dog-human interactions and canine welfare.

Maintaining the range of motion in repetitive movement tasks is a crucial point since it directly influences the movement rate. Ensuring the movement amplitude can be reliably maintained when motor function is assessed by measuring the maximum movement rate is therefore a key consideration. However, the performed range of motion during such tasks is often not reported. This study aimed to determine whether individuals are able to maintain an intended range of motion during a knee flexion/extension maximum movement rate task in the absence of tactile and visual feedback. Twelve healthy male individuals performed knee flexion/extension at maximum speed for eight 10-s blocks in a 45° arc between 45° and 90°. The range of motion was monitored using a marker system and the movement rate was measured. The performed range of motion was not significantly different from the 45° arc during the task despite a 13.47% decrease in movement rate from the start to the end of the task. Nevertheless, there was only anecdotal evidence of no difference from 45° in most blocks, while on the second and seventh blocks, there was anecdotal evidence of differences in the Bayesian one-sample test. There was also no significant shift in the maximum flexion/extension angles throughout the task. Healthy male individuals were thus able to perform a consistent average predefined knee range of motion in a maximum movement rate task despite decreases in movement rate. This was achieved without constraint-inducing devices during the task, using only basic equipment and verbal feedback. [ABSTRACT FROM AUTHOR]

Objective: Low-cost, portable RGB-D cameras with integrated motion tracking functionality enable easy-to-use 3D motion analysis without requiring expensive facilities and specialized personnel. However, the accuracy of existing systems is insufficient for most clinical applications, particularly when applied to children. In previous work, we developed an RGB-D camera-based motion tracking method and showed that it accurately captures body joint positions of children and young adults in 3D. In this study, the validity and accuracy of clinically relevant motion parameters that were computed from kinematics of our motion tracking method are evaluated in children and young adults. Methods: Twenty-three typically developing children and healthy young adults (5-29 years, 110–189 cm) performed five movement tasks while being recorded simultaneously with a marker-based Vicon system and an Azure Kinect RGB-D camera. Motion parameters were computed from the extracted kinematics of both methods: time series measurements, i.e., measurements over time, peak measurements, i.e., measurements at a single time instant, and movement smoothness. The agreement of these parameter values was evaluated using Pearson’s correlation coefficients r for time series data, and mean absolute error (MAE) and Bland-Altman plots with limits of agreement for peak measurements and smoothness. Results: Time series measurements showed strong to excellent correlations (r-values between 0.8 and 1.0), MAE for angles ranged from 1.5 to 5 degrees and for smoothness parameters (SPARC) from 0.02-0.09, while MAE for distance-related parameters ranged from 9 to 15 mm. Conclusion: Extracted motion parameters are valid and accurate for various movement tasks in children and young adults, demonstrating the suitability of our tracking method for clinical motion analysis. Clinical Impact: The low-cost portable hardware in combination with our tracking method enables motion analysis outside of specialized facilities while providing measurements that are close to those of the clinical gold-standard.

Digital Image Correlation (DIC) has been widely used as a non-contact deformation measurement technique. Nevertheless, its accuracy is greatly affected by the speckle pattern on the specimen. To systematically evaluate how speckle deformability affects the precision of DIC algorithms. In this study, a test dataset of 2D speckle patterns with various prescribed deformation fields was numerically generated, containing two categories of speckles, i.e., the deformable and the non-deformable (rigid) ones. This dataset was used to evaluate the performance of inverse compositional Gauss-Newton (ICGN)-based DIC algorithms with two types of shape function (first-order and second-order), in the different scenarios of the deformation field. The results showed that imaging noise had a significant influence on the DIC algorithm. The first-order shape function (ICGN-1) performed better when tracking the simple linear deformation field. While the second-order shape function (ICGN-2) was proved to perform better on non-linear deformations. Moreover, the deformability of the speckle was found to have an obvious impact on the performance of the DIC algorithm. ICGN-2 could effectively reduce so-called speckle rigidity induced (SRI) error. Conclusively, ICGN-2 should be chosen as priority, because of its feasibility on non-linear deformation fields and speckle rigidity. While in the linear deformation scenarios, ICGN-1 was still a robust and efficient method.

This study aimed to validate the automated temporal analysis of countermovement vertical jump (CMJ) using MMPose, a markerless pose estimation framework, by comparing it with the gold-standard 3D marker-based motion capture system. Twelve participants performed five CMJ trials, which were simultaneously recorded using the marker-based system and two smartphone cameras capturing both sides of the body. Key kinematic points, including center of mass (CoM) and toe trajectories, were analyzed to determine jump phases and temporal variables. The agreement between methods was assessed using Bland–Altman analysis, root mean square error (RMSE), and Pearson’s correlation coefficient (r), while consistency was evaluated via intraclass correlation coefficient (ICC 3,1) and two-way repeated-measures ANOVA. Cohen’s effect size (d) quantified the practical significance of differences. Results showed strong agreement (r > 0.98) with minimal bias and narrow limits of agreement for most variables. The markerless system slightly overestimated jump height and CoM vertical velocity, but ICC values (ICC > 0.91) confirmed strong reliability. Cohen’s d values were near zero, indicating trivial differences, and no variability due to recording side was observed. Overall, MMPose proved to be a reliable alternative for in-field CMJ analysis, supporting its broader application in sports and rehabilitation settings.

Pathological gait in patients with Hakim’s disease (HD, synonymous with idiopathic normal-pressure hydrocephalus; iNPH), Parkinson’s disease (PD), and cervical myelopathy (CM) has been subjectively evaluated in this study. We quantified the characteristics of upper and lower limb movements in patients with pathological gait. We analyzed 1491 measurements of 1 m diameter circular walking from 122, 12, and 93 patients with HD, PD, and CM, respectively, and 200 healthy volunteers using the Three-Dimensional Pose Tracker for Gait Test. Upper and lower limb movements of 2D coordinates projected onto body axis sections were derived from estimated 3D relative coordinates. The hip and knee joint angle ranges on the sagittal plane were significantly smaller in the following order: healthy > CM > PD > HD, whereas the shoulder and elbow joint angle ranges were significantly smaller, as follows: healthy > CM > HD > PD. The outward shift of the leg on the axial plane was significantly greater, as follows: healthy < CM < PD < HD, whereas the outward shift of the upper limb followed the order of healthy > CM > HD > PD. The strongest correlation between the upper and lower limb movements was identified in the angle ranges of the hip and elbow joints on the sagittal plane. The lower and upper limb movements during circular walking were correlated. Patients with HD and PD exhibited reduced back-and-forth swings of the upper and lower limbs.

Hexapod robots have gained significant attention due to their potential applications in complex terrains and dynamic environments. However, traditional inverse kinematics approaches often face challenges in meeting the precision required for adaptive omnidirectional movement. This work introduces a novel approach to addressing these challenges through the Directed Angular Restitution (DAR) method. The DAR method offers significant innovation by simplifying the calculation of rotational transformations necessary for aligning vectors across different planes, thus enhancing control, stability, and accuracy in robotic applications. Unlike conventional methods, the DAR method extends the range of trigonometric functions and incorporates spin functions to ensure continuous and smooth trajectory tracking. This innovative approach has been rigorously tested on a hexapod robot model, demonstrating superior performance in movement precision and stability. The results confirm that the DAR method provides a robust and scalable solution for the inverse kinematics of hexapod robots, making it a critical advancement for applications in robotics and automation where precise control and adaptability are paramount.

Background: CyberKnife treatment for central lung tumors and mediastinal tumors can be difficult to perform with marker less. Purpose: We aimed to evaluate a novel tracheobronchial-based method (ie, tracheobronchial tracking) for the purpose of minimally invasive CyberKnife treatment for central lung and mediastinal tumors. Methods: Five verification plans were created using an in-house phantom. Each plan included five irradiation sessions. The reference plan irradiated and tracked the simulated tumor (using the target tracking volume, TTV). Trachea plans tracked the simulated tracheo-bronchus and irradiated the simulated tumor and included two types of subplans: correlated plans in which the displacement of the simulated tracheobronchial and the simulated tumor were correlated, and non-correlated plans in which these factors were not correlated. Moreover, 15 mm and 25 mm TTVs were evaluated for each plan. The sin waveform and the patient's respiratory waveform were prepared as the respiratory model. Evaluations were performed by calculating the dose difference between the radiophotoluminescent glass dosimeter (RPLD)-generated mean dose values (generated by the treatment planning system, TPS) and the actual absorbed RPLD dose. Statistical analyses were performed to evaluate findings for each plan. Correlation and prediction errors were calculated for each axis of each plan using log files to evaluate tracking accuracy. Results: Dose differences were statistically significant only in comparisons with the non-correlated plan. When evaluated using the sin waveform, the mean values for correlation and prediction errors in each axis and for all plans were less than 0.6 mm and 0.1 mm, respectively. In the same manner, they were less than 1.1 mm and 0.2 mm when evaluated using the patient's respiratory waveform. Conclusion: Our newly-developed tracheobronchial tracking method would be useful in facilitating minimally invasive CyberKnife treatment in certain cases of central lung and mediastinal tumors. [ABSTRACT FROM AUTHOR]

Objective: The clinical applicability of shear wave elasticity imaging (SWEI) has been confounded by its appreciable inter-system variability and unsatisfactory sensitivity. While SWEI relies on plane wave imaging (PWI) to achieve real-time rendering, it has been rarely noticed that PWI can affect SWEI's performance. This work is aimed at demonstrating that the use of coherent plane wave compounding (CPWC) can be a factor causing SWEI's underperformance. Methods: We presented a model to formally describe the slow-time behavior of CPWC in motion tracking. This model reveals that CPWC introduces temporal convolution on the observed motion, making the motion sampling process a low-pass filter (LPF). For validation, shear waves were produced in a phantom in the same way but sampled via PWI using different compounding numbers (CN) and pulse repetition frequencies (PRF), with the obtained signals compared with the inferences drawn from our model. Similar experiments were performed to reconstruct two small targets in the phantom in order to appraise the impact of CPWC on SWEI's sensitivity. Discussion: The validation experiment shows that the measurements match well with the model inferences, which verifies the LPF nature of CPWC. The phantom study also shows that either increasing CN or decreasing PRF can cause the loss of high-frequency motion information, leading to blurred target delineation by SWEI. Conclusion: The convolution effect can help understand the variability of SWEI. Researchers should beware this effect when working on SWEI standardization. Clinicians using SWEI should also be cautious because this effect makes it harder to identify small lesions. [ABSTRACT FROM AUTHOR]

Recently, a new generation of superior clavicle plates was developed featuring the variable-angle locking technology for enhanced screw positioning and a less prominent and optimized plate-to-bone fit design. On the other hand, minifragment plates in dual plating mode have demonstrated promising clinical results. The aim of the current study was to compare the biomechanical competence of single superior plating using the new-generation plate vs. dual plating using low-profile minifragment plates. Sixteen paired human cadaveric clavicles were pairwise assigned to 2 groups for instrumentation with either a superior 2.7-mm variable-angle locking compression plate (group 1), or with one 2.5-mm anterior combined with one 2.0-mm superior matrix mandible plate (group 2). An unstable clavicle shaft fracture (AO/OTA 15.2C) was simulated by means of a 5-mm osteotomy gap. Specimens were cyclically tested to failure under craniocaudal cantilever bending, superimposed with bidirectional torsion around the shaft axis, and monitored via motion tracking. Initial construct stiffness was significantly higher in group 2 (9.28 ± 4.40 N/mm) compared to group 1 (3.68 ± 1.08 N/mm), P =.003. The amplitudes of interfragmentary motions in terms of axial and shear displacement, fracture gap opening and torsion, over the course of 12,500 cycles were significantly higher in group 1 compared to group 2, P ≤.038. Cycles to 2 mm shear displacement were significantly lower in group 1 (22,792 ± 4346) compared to group 2 (27,437 ± 1877), P =.047. From a biomechanical perspective, low-profile 2.5/2.0-mm dual plates could be considered as a useful alternative for diaphyseal clavicle fracture fixation, especially in less common unstable fracture configurations. [ABSTRACT FROM AUTHOR]

Accurate and reliable human motion reconstruction is crucial for creating natural interactions of full-body avatars in Virtual Reality (VR) and entertainment applications. As the Metaverse and social applications gain popularity, users are seeking cost-effective solutions to create full-body animations that are comparable in quality to those produced by commercial motion capture systems. In order to provide affordable solutions though, it is important to minimize the number of sensors attached to the subject's body. Unfortunately, reconstructing the full-body pose from sparse data is a heavily under-determined problem. Some studies that use IMU sensors face challenges in reconstructing the pose due to positional drift and ambiguity of the poses. In recent years, some mainstream VR systems have released 6-degree-of-freedom (6-DoF) tracking devices providing positional and rotational information. Nevertheless, most solutions for reconstructing full-body poses rely on traditional inverse kinematics (IK) solutions, which often produce non-continuous and unnatural poses. In this article, we introduce SparsePoser, a novel deep learning-based solution for reconstructing a full-body pose from a reduced set of six tracking devices. Our system incorporates a convolutional-based autoencoder that synthesizes high-quality continuous human poses by learning the human motion manifold from motion capture data. Then, we employ a learned IK component, made of multiple lightweight feed-forward neural networks, to adjust the hands and feet toward the corresponding trackers. We extensively evaluate our method on publicly available motion capture datasets and with real-time live demos. We show that our method outperforms state-of-the-art techniques using IMU sensors or 6-DoF tracking devices, and can be used for users with different body dimensions and proportions. [ABSTRACT FROM AUTHOR]

Swarming locusts present a quintessential example of animal collective motion. Juvenile locusts march and hop across the ground in coordinated groups called hopper bands. Composed of up to millions of insects, hopper bands exhibit aligned motion and various collective structures. These groups are well-documented in the field, but the individual insects themselves are typically studied in much smaller groups in laboratory experiments. We present, to our knowledge, the first trajectory data that detail the movement of individual locusts within a hopper band in a natural setting. Using automated video tracking, we derive our data from footage of four distinct hopper bands of the Australian plague locust, Chortoicetes terminifera. We reconstruct nearly 200 000 individual trajectories composed of over 3.3 million locust positions. We classify these data into three motion states: stationary, walking and hopping. Distributions of relative neighbour positions reveal anisotropies that depend on motion state. Stationary locusts have high-density areas distributed around them apparently at random. Walking locusts have a low-density area in front of them. Hopping locusts have low-density areas in front and behind them. Our results suggest novel insect interactions, namely that locusts change their motion to avoid colliding with neighbours in front of them. [ABSTRACT FROM AUTHOR]

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder known for its significant heterogeneity and varied symptom presentation. Describing the different subtypes as predominantly inattentive (ADHD–I), combined (ADHD–C), and hyperactive–impulsive (ADHD–H) relies primarily on clinical observations, which can be subjective. To address the need for more objective diagnostic methods, this pilot study implemented a Microsoft Kinect-based Stroop Color–Word Test (KSWCT) with the objective of investigating the potential differences in executive function and motor control between different subtypes in a group of children and adolescents with ADHD. A series of linear mixture modeling were used to encompass the performance accuracy, reaction times, and extraneous movements during the tests. Our findings suggested that age plays a critical role, and older subjects showed improvements in KSWCT performance; however, no significant divergence in activity level between the subtypes (ADHD–I and ADHD–H/C) was established. Patients with ADHD–H/C showed tendencies toward deficits in motor planning and executive control, exhibited by shorter reaction times for incorrect responses and more difficulty suppressing erroneous responses. This study provides preliminary evidence of unique executive characteristics among ADHD subtypes, advances our understanding of the heterogeneity of the disorder, and lays the foundation for the development of refined and objective diagnostic tools for ADHD. [ABSTRACT FROM AUTHOR]

Laparoscopic manipulation of delicate large intra-abdominal organs is a difficult task that needs special training programs to improve the surgeons' dexterity. In this study, the mechanical design of a robotic interface for haptic simulation of largeorgan laparoscopic surgery is described. The designed robot enjoys active active Degree of Freedoms (DOFs), back drivability, low inertia, friction and backlash, and sufficiently large force/moment production capacity. The kinematics of the robot was analyzed and a functional prototype was fabricated for experimental tests. Results indicated that the target workspace was fully covered with no singular points inside. The mechanism was highly isotropic and the torque requirements were in the acceptable range. The trajectory tracking experiments against a 1 kg payload revealed an Root Mean Square (RMS) of 0.9 mm, due to the simplifications of the kinematic model, i.e., not considering the friction and backlash effects. It was concluded that the designed robot could satisfy the mechanical requirements for being used as the robotic interface in a haptic large-organ laparoscopic surgery simulation system. [ABSTRACT FROM AUTHOR]

Basketball games, real-time adjustment of defense strategy according to the changes on the court can greatly improve the team's chance of success in defense and thus win the game. The development of artificial intelligence technology, especially computer vision, provides a technical basis for real-time tracking of players' positions and body postures. In this paper, a player posture estimation algorithm based on local spatial constraints is proposed based on motion tracking technology and deep learning technology. The algorithm is based on the general human body pose estimation algorithm, which locally constrains the picture based on the athlete detection frame, retains only the content related to the athlete in the picture, and then inputs the processed picture into the general human body pose estimation model for pose detection, and finally maps the detected pose back to the original picture to complete the estimation of the athlete's pose. The model is verified to be able to efficiently complete the real-time defensive strategy optimization task by using NBA game videos for testing. [ABSTRACT FROM AUTHOR]

The recognition of human activities from video sequences and their transformation into a machine-readable form is a challenging task, which is the subject of many studies. The goal of this project is to develop an automated method for analyzing, identifying and processing motion capture data into a planning language. This is performed in a cooking scenario by recording the pose of the acting hand. First, predefined side actions are detected in the dataset using classification. The remaining frames are then clustered into main actions. Using this information, the known initial positions and virtual object tracking, a machine-readable planning domain definition language (PDDL) is generated. [ABSTRACT FROM AUTHOR]

Background/Purpose: The surgical fixation of a symphyseal diastasis in partially or fully unstable pelvic ring injuries is an important element when stabilizing the anterior pelvic ring. Currently, open reduction and internal fixation (ORIF) by means of plating represents the gold standard treatment. Advances in percutaneous fixation techniques have shown improvements in blood loss, surgery time, and scar length. Therefore, this approach should also be adopted for treatment of symphyseal injuries. The technique could be important since failure rates, following ORIF at the symphysis, remain unacceptably high. The aim of this biomechanical study was to assess a semi-rigid fixation technique for treatment of such anterior pelvic ring injuries versus current gold standards of plate osteosynthesis. Methods: An anterior pelvic ring injury type III APC according to the Young and Burgess classification was simulated in eighteen composite pelvises, assigned to three groups (n = 6) for fixation with either a single plate, two orthogonally positioned plates, or the semi-rigid technique using an endobutton suture implant. Biomechanical testing was performed in a simulated upright standing position under progressively increasing cyclic loading at 2 Hz until failure or over 150,000 cycles. Relative movements between the bone segments were captured by motion tracking. Results: Initial quasi-static and dynamic stiffness, as well as dynamic stiffness after 100,000 cycles, was not significantly different among the fixation techniques (p ≥ 0.054).). The outcome measures for total displacement after 20,000, 40,000, 60,000, 80,000, and 100,000 cycles were associated with significantly higher values for the suture technique versus double plating (p = 0.025), without further significant differences among the techniques (p ≥ 0.349). Number of cycles to failure and load at failure were highest for double plating (150,000 ± 0/100.0 ± 0.0 N), followed by single plating (132,282 ± 20,465/91.1 ± 10.2 N), and the suture technique (116,088 ± 12,169/83.0 ± 6.1 N), with significantly lower values in the latter compared to the former (p = 0.002) and no further significant differences among the techniques (p ≥ 0.329). Conclusion: From a biomechanical perspective, the semi-rigid technique for fixation of unstable pubic symphysis injuries demonstrated promising results with moderate to inferior behaviour compared to standard plating techniques regarding stiffness, cycles to failure and load at failure. This knowledge could lay the foundation for realization of further studies with larger sample sizes, focusing on the stabilization of the anterior pelvic ring. [ABSTRACT FROM AUTHOR]

Purpose: During reconstructive surgery, knee and hip replacements, and orthognathic surgery, small misalignments in the pose of prosthesis and bones can lead to severe complications. Hence, the translational and angular accuracies are critical. However, traditional image-based surgical navigation lacks orientation data between structures, and imageless systems are unsuitable for cases of deformed anatomy. We introduce an open-source navigation system using a multiple registration approach that can track instruments, implants, and bones to precisely guide the surgeon in emulating a preoperative plan. Methods: We derived the analytical error of our method and designed a set of phantom experiments to measure its precision and accuracy. Additionally, we trained two classification models to predict the system reliability from fiducial points and surface matching registration data. Finally, to demonstrate the procedure feasibility, we conducted a complete workflow for a real clinical case of a patient with fibrous dysplasia and anatomical misalignment of the right femur using plastic bones. Results: The system is able to track the dissociated fragments of the clinical case and average alignment errors in the anatomical phantoms of 1.08 ± 0.68 mm and 1.49 ± 1. 19 ∘ . While the fiducial-points registration showed satisfactory results given enough points and covered volume, we acknowledge that the surface refinement step is mandatory when attempting surface matching registrations. Conclusion: We believe that our device could bring significant advantages for the personalized treatment of complex surgical cases and that its multi-registration attribute is convenient for intraoperative registration loosening cases. [ABSTRACT FROM AUTHOR]