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Manual wheelchair propulsion represents a repetitive and constraining task, which leads mainly to the development of joint injury in spinal cord-injured people. One of the main reasons is the load sustained by the shoulder joint during the propulsion cycle. Moreover, the load at the shoulder joint is highly correlated with the force and moment acting at the handrim level. The main objective of this study is related to the estimation of handrim reactions forces and moments during wheelchair propulsion using only a single inertial measurement unit per hand. Two approaches are proposed here: Firstly, a method of identification of a non-linear transfer function based on the Hammerstein–Wiener (HW) modeling approach was used. The latter represents a typical multi-input single output in a system engineering modeling approach. Secondly, a specific variant of recurrent neural network called BiLSTM is proposed to predict the time-series data of force and moments at the handrim level. Eleven subjects participated in this study in a linear propulsion protocol, while the forces and moments were measured by a dynamic platform. The two input signals were the linear acceleration as well the angular velocity of the wrist joint. The horizontal, vertical and sagittal moments were estimated by the two approaches. The mean average error (MAE) shows a value of 6.10 N and 4.30 N for the horizontal force for BiLSTM and HW, respectively. The results for the vertical direction show a MAE of 5.91 N and 7.59 N for BiLSTM and HW, respectively. Finally, the MAE for the sagittal moment varies from 0.96 Nm (BiLSTM) to 1.09 Nm for the HW model. The approaches seem similar with respect to the MAE and can be considered accurate knowing that the order of magnitude of the uncertainties of the dynamic platform was reported to be 2.2 N for the horizontal and vertical forces and 2.24 Nm for the sagittal moments. However, it should be noted that HW necessitates the knowledge of the average force and patterns of each subject, whereas the BiLSTM method do not involve the average patterns, which shows its superiority for time-series data prediction. The results provided in this study show the possibility of measuring dynamic forces acting at the handrim level during wheelchair manual propulsion in ecological environments. [ABSTRACT FROM AUTHOR]

This paper reviews how multifunctioning joints produce highly agile limbs in animals with lessons for robotics. One of the key reasons why animals are so fast and agile is that they have multifunctioning joints in their limbs. The multifunctioning joints lead to a high degree of compactness which then leads to a host of benefits such as low mass, low moment of inertia and low drag. This paper presents three case studies of multifunctioning joints—the human wrist joint, knee joint and foot joints—in order to identify how multifunctioning is achieved and what lessons can be learned for robotics. It also reviews the multifunctioning nature of muscle which plays an important role in joint actuation. A key finding is that multifunctioning is achieved through various means: multiple degrees of freedom, multifunctioning parts, over-actuation and reconfiguration. In addition, multifunctioning is achieved through highly sophisticated layouts with high levels of integration and fine-tuning. Muscle also makes an important contribution to animal agility by performing multiple functions including providing shape, protection and heat. The paper reviews progress in achieving multifunctioning in robot joints particularly for the wrist, knee and foot. Whilst there has been some progress in creating multifunctioning robotic joints, there is still a large gap between the performance of animal and robotic joints. There is an opportunity to improve the agility of robots by using multifunctioning to reduce the size and mass of robotic joints. [ABSTRACT FROM AUTHOR]

Surface electromyography (sEMG) offers a novel method in human–machine interactions (HMIs) since it is a distinct physiological electrical signal that conceals human movement intention and muscle information. Unfortunately, the nonlinear and non-smooth features of sEMG signals often make joint angle estimation difficult. This paper proposes a joint angle prediction model for the continuous estimation of wrist motion angle changes based on sEMG signals. The proposed model combines a temporal convolutional network (TCN) with a long short-term memory (LSTM) network, where the TCN can sense local information and mine the deeper information of the sEMG signals, while LSTM, with its excellent temporal memory capability, can make up for the lack of the ability of the TCN to capture the long-term dependence of the sEMG signals, resulting in a better prediction. We validated the proposed method in the publicly available Ninapro DB1 dataset by selecting the first eight subjects and picking three types of wrist-dependent movements: wrist flexion (WF), wrist ulnar deviation (WUD), and wrist extension and closed hand (WECH). Finally, the proposed TCN-LSTM model was compared with the TCN and LSTM models. The proposed TCN-LSTM outperformed the TCN and LSTM models in terms of the root mean square error (RMSE) and average coefficient of determination (R2). The TCN-LSTM model achieved an average RMSE of 0.064, representing a 41% reduction compared to the TCN model and a 52% reduction compared to the LSTM model. The TCN-LSTM also achieved an average R2 of 0.93, indicating an 11% improvement over the TCN model and an 18% improvement over the LSTM model. [ABSTRACT FROM AUTHOR]

Our study presents a novel design for a cable-driven robotic arm, emphasizing low cost, low inertia movement, and long-term cable durability. The robotic arm shares similar specifications with the UR5 robotic arm, featuring a total of six degrees of freedom (DOF) distributed in a 1:1:1:3 ratio at the arm base, shoulder, elbow, and wrist, respectively. The three DOF at the wrist joints are driven by a cable system, with heavy motors relocated from the end-effector to the shoulder base. This repositioning results in a lighter cable-actuated wrist (weighing 0.8 kg), which enhances safety during human interaction and reduces the torque requirements for the elbow and shoulder motors. Consequently, the overall cost and weight of the robotic arm are reduced, achieving a payload-to-body weight ratio of 5:8.4 kg. To ensure good positional repeatability, the shoulder and elbow joints, which influence longer moment arms, are designed with a direct-drive structure. To evaluate the design's performance, tests were conducted on loading capability, cable durability, position repeatability, and manipulation. The tests demonstrated that the arm could manipulate a 5 kg payload with a positional repeatability error of less than 0.1 mm. Additionally, a novel cable tightener design was introduced, which served dual functions: conveniently tightening the cable and reducing the high-stress concentration near the cable locking end to minimize cable loosening. When subjected to an initial cable tension of 100 kg, this design retained approximately 80% of the load after 10 years at a room temperature of 24 °C. [ABSTRACT FROM AUTHOR]

Ultrasound imaging (US) is being increasingly used to aid in the diagnosis of entrapment neuropathies. This study aims to evaluate the shear modulus and cross-sectional area (CSA) of the median nerve in patients with carpal tunnel syndrome (CTS). A total of 35 patients with CTS participated in the study. CSA and shear modulus testing were performed in shear wave elastography (SWE) mode in five positions of the right and left radiocarpal joints (intermediate position 0°, 45° of extension, maximum extension, 45° of flexion, and maximum flexion). There were significant side-to-side differences in the median nerve shear modulus at each wrist position as compared to the asymptomatic side. There were significant side-to-side differences in the median nerve CSA at each wrist position as compared to the asymptomatic side. Shear modulus increases in patients with CTS at different angular positions of flexion and extension of the radiocarpal joint. In individuals with CTS, the CSA of the median nerve is greater on the symptomatic side compared to the asymptomatic side. The CSA decreases in positions of maximum extension and 45° of flexion and in maximum flexion relative to the resting position. [ABSTRACT FROM AUTHOR]

Radial nerve palsies present a challenging clinical scenario, often leading to substantial functional impairment. This study focuses on evaluating the outcomes of tendon transfer surgeries in patients with post-traumatic radial nerve injuries. The radial nerve, vital for upper limb movements, faces various etiologies, such as trauma, compression, or idiopathy. Patients with radial nerve palsy encounter difficulties in daily activities, emphasizing the need for effective management strategies. The research introduces a novel evaluation protocol, aiming to comprehensively assess tendon transfer outcomes. This protocol incorporates functional movements of wrist and finger joints, encompassing both objective and subjective parameters. The retrospective study includes eleven patients treated between 2010 and 2022, with a minimum follow-up of one year post-surgery. Tendon transfers demonstrated positive results. The evaluation protocol covers a wide range of parameters, including wrist and finger mobility, thumb function, grip strength, and patient satisfaction. The results indicate successful restoration of motor function, with an average grip strength of 70% compared to the healthy arm. The proposed evaluation protocol facilitates standardized and reproducible assessment, minimizing subjective errors in clinical evaluations. Despite the study's limitations, such as a relatively small sample size, the findings underscore the effectiveness of tendon transfers in treating radial nerve palsies. The introduced evaluation scheme provides a comprehensive and reproducible approach to assess outcomes, contributing to the global standardization of tendon transfer assessments in radial nerve injuries. [ABSTRACT FROM AUTHOR]

Background and Objectives: Non-specific chronic wrist pain is wrist pain that occurs without a specific cause, such as trauma, and may limit the range of motion of the joints of the wrist and hand, affecting muscle strength, grip strength, and function. This study aimed to determine the effects of grip-strengthening exercises combined with wrist stability training on pain and function in patients with non-specific chronic wrist pain. Materials and Methods: The subjects of the study were 31 patients with wrist pain. To determine the effect of grip-strengthening exercises combined with wrist stability training, 15 participants participated in grip-strengthening exercises combined with wrist stability training and 16 control subjects participated. The experimental group participated in wrist-stability training. Grip-strengthening exercises combined with wrist stability training were performed for 20 min/day twice a week for 4 weeks, and relaxation massage and conservative physical therapy were performed for 20 min/day twice a week for 4 weeks. The control group received relaxation massage and conservative physical therapy for 40 min/day twice a week for 4 weeks. A visual pain scale was used to evaluate the degree of pain before and after treatment, and a patient-rated wrist evaluation was used to evaluate wrist function. Results: The results showed that the visual score significantly decreased in the time effect before and after the intervention in both groups (p < 0.001), patient-rated wrist evaluation significantly decreased (p < 0.001), and grip strength and muscle strength significantly increased (p < 0.001). The results of this study showed that grip-strengthening exercises combined with wrist stability training were effective in improving pain, function, grip strength, and muscle strength in patients with non-specific chronic wrist pain. Conclusions: Grip-strengthening exercises combined with wrist stability training can be used as an effective intervention method to improve pain, function, grip strength, and muscle strength, emphasizing the need for wrist exercise interventions in patients with non-specific chronic wrist pain in the future. [ABSTRACT FROM AUTHOR]

Introduction: The scapholunate interosseous ligament is pivotal for wrist stability, and its impairment can result in instability and joint degeneration. This study explores the application of real-time MRI for dynamic assessment of the scapholunate joint during wrist motion with the objective of determining its diagnostic value in efficacy in contrast to static imaging modalities. Materials and Methods: Ten healthy participants underwent real-time MRI scans during wrist ab/adduction and fist-clenching maneuvers. Measurements were obtained at proximal, medial, and distal landmarks on both dynamic and static images with statistical analyses conducted to evaluate the reliability of measurements at each landmark and the concordance between dynamic measurements and established static images. Additionally, inter- and intraobserver variabilities were evaluated. Results: Measurements of the medial landmarks demonstrated the closest agreement with static images and exhibited the least scatter. Distal landmark measurements showed a similar level of agreement but with increased scatter. Proximal landmark measurements displayed substantial deviation, which was accompanied by an even greater degree of scatter. Although no significant differences were observed between the ab/adduction and fist-clenching maneuvers, both inter- and intraobserver variabilities were significant across all measurements. Conclusions: This study highlights the potential of real-time MRI in the dynamic assessment of the scapholunate joint particularly at the medial landmark. Despite promising results, challenges such as measurement variability need to be addressed. Standardization and integration with advanced image processing methods could significantly enhance the accuracy and reliability of real-time MRI, paving the way for its clinical implementation in dynamic wrist imaging studies. [ABSTRACT FROM AUTHOR]

Various conditions, including traffic accidents, sports injuries, and neurological disorders, can impair human wrist movements, underscoring the importance of effective rehabilitation methods. Robotic devices play a crucial role in this regard, particularly in wrist rehabilitation, given the complexity of the human wrist joint, which encompasses three degrees of freedom: flexion/extension, pronation/supination, and radial/ulnar deviation. This paper provides a comprehensive review of wrist rehabilitation devices, employing a methodological approach based on primary articles sourced from PubMed, ScienceDirect, Scopus, and IEEE, using the keywords "wrist rehabilitation robot" from 2007 onwards. The findings highlight a diverse array of wrist rehabilitation devices, systematically organized in a tabular format for enhanced comprehension. Serving as a valuable resource for researchers, this paper enables comparative analyses of robotic wrist rehabilitation devices across various attributes, offering insights into future advancements. Particularly noteworthy is the integration of serious games with simplified wrist rehabilitation devices, signaling a promising avenue for enhancing rehabilitation outcomes. These insights lay the groundwork for the development of new robotic wrist rehabilitation devices or to make improvements to existing prototypes incorporating a forward-looking approach to improve rehabilitation outcomes. [ABSTRACT FROM AUTHOR]

Upper limb functionality is essential to perform activities of daily living. It is critical to investigate neurorehabilitation therapies in order to improve upper limb functionality in post-stroke patients. This paper presents a soft-robotic bilateral system to provide rehabilitation therapy for hand and wrist joints. A sensorized glove that tracks finger and wrist joint movements is worn on the healthy limb, which guides the movement of the paretic limb. The input of sensors from the healthy limb is provided to the soft robotic exoskeleton attached to the paretic limb to mimic the motion. A proportional derivative flow-based control algorithm is used to perform bilateral therapy. To test the feasibility of the developed system, two different applications are performed experimentally: (1) Wrist exercise with a dumbbell, and (2) Object pick-and-place task. The initial tests of the developed system verified its capability to perform bilateral therapy. [ABSTRACT FROM AUTHOR]

Climbing is a fast-growing sport, with one of the most common injuries being a rupture of the finger flexor tendon pulley. The strain on pulleys increases as finger joints flex. However, to our knowledge, no study has conducted a kinematic analysis of climbers' fingers. Thus, this study aimed to examine finger kinematics during typical climbing tasks. Eleven elite climbers performed a sequence of four climbing moves, which were recorded by an optical motion capture system. Participants used crimp, half-crimp, and open-hand grips for three trials each, with the fourth condition involving campusing using any grip except crimp. Mean proximal interphalangeal joint (PIP) flexion during the holding phase was 87° (SD 12°), 70° (14°) and 39° (27°) for the crimp, half-crimp and open-hand grip, respectively. Hence, inter-individual PIP flexion ranges overlap between different gripping conditions. Two different movement patterns emerged in the open-hand grip, possibly influenced by the use of the little finger, leading to varying degrees of flexion in the middle and ring fingers. Avoiding little finger usage in the open-hand grip may reduce load during pulley rupture rehabilitation. The implications of PIP joint angle variability on individual pulley injury risk or prevention warrant further investigation. Motion capture proved effective for understanding finger kinematics during climbing and could guide future studies on pulley injury risk factors. [ABSTRACT FROM AUTHOR]

Manipulators are multi-rigid-body systems composed of multiple moving joints. During movement, the Coriolis force, centrifugal force, and gravity of the system undergo significant changes. The last three degrees of freedom (DOFs) of the wrist joint of a manipulator control the end attitude. Improving the command tracking accuracy of the wrist joint is a key challenge in controlling the end attitude of manipulators. In this study, a dynamics model of the mechanical arm–wrist joint is established based on the Lagrange method. An adaptive continuous robust integral of the sign of the error (ARISE) controller is designed using the reverse step method. Additionally, a linear extended state observer (LESO) is employed to estimate the time-varying interference existing in the system and compensate for it in the designed control rate. The stability of the Lyapunov function and the boundedness of the observer are proven. The proposed control method for the wrist joint is compared with other controllers on an experimental platform of multi-DOF hydraulic manipulators. The results demonstrate that the proposed method improves the control performance of hydraulic manipulators. The application of this method offers a new strategy and idea for achieving high-performance tracking control in hydraulic manipulators. [ABSTRACT FROM AUTHOR]

Multi-degree-of-freedom piezoelectric motors have the advantages of high torque and resolution, simple structure, and direct drive, which are widely used in robot wrist joints, deep-sea mechanisms, medical equipment, and space mechanisms. To solve the problems of high force/torque coupling degree and ball low stator and rotor bonding strength of the traditional traveling wave type three-degree-of-freedom piezoelectric spherical motor, a new structure of ball-hinged piezoelectric spherical motor is proposed. Through coordinate transformation and force analysis, the driven mathematical model of the spherical motor is given. The model shows that the three degrees of freedom of the motor are coupled with each other. According to the mathematical model of the spherical motor, the mechanical properties of the motor are analyzed by the computer simulation. The results show that the stalling torque coefficient kt has a linear relationship with the friction coefficient ε and the stator preload Fc, has a nonlinear relationship with the stator radius R and the rotor radius r, and increases with the increase of R and decreases with the increase of r. The no-load speed of motor ωn is not related to the friction coefficient ε and the stator preload Fc, and increases with the increase of R and decreases with the increase of r. The anisotropic characteristics of torque and speed of a spherical motor are further analyzed, which lays a theoretical foundation for the drive control of a spherical motor. [ABSTRACT FROM AUTHOR]

Although several previous studies on laterality of upper limb motor control have reported functional differences, this conclusion has not been agreed upon. It may be conjectured that the inconsistent results were caused because upper limb motor control was observed in multi-joint tasks that could generate different inter-joint motor coordination for each arm. Resolving this, we employed a single wrist joint tracking task to reduce the effect of multi-joint dynamics and examined the differences between the dominant and non-dominant hands in terms of motor control. Specifically, we defined two sections to induce feedback (FB) and feedforward (FF) controls: the first section involved a visible target for FB control, and the other section involved an invisible target for FF control. We examined the differences in the position errors of the tracer and the target. Fourteen healthy participants performed the task. As a result, we found that during FB control, the dominant hand performed better than the non-dominant hand, while we did not observe significant differences in FF control. In other words, in a single-joint movement that is not under the influence of the multi-joint coordination, only FB control showed laterality and not FF control. Furthermore, we confirmed that the dominant hand outperformed the non-dominant hand in terms of responding to situations that required a change in control strategy. [ABSTRACT FROM AUTHOR]

This review article presents an in-depth examination of research and development in the fields of rehabilitation, assistive technologies, and humanoid robots. It focuses on parallel robots designed for human body joints with three degrees of freedom, specifically the neck, shoulder, wrist, hip, and ankle. A systematic search was conducted across multiple databases, including Scopus, Web of Science, PubMed, IEEE Xplore, ScienceDirect, the Directory of Open Access Journals, and the ASME Journal. This systematic review offers an updated overview of advancements in the field from 2012 to 2023. After applying exclusion criteria, 93 papers were selected for in-depth review. This cohort included 13 articles focusing on the neck joint, 19 on the shoulder joint, 22 on the wrist joint, 9 on the hip joint, and 30 on the ankle joint. The article discusses the timeline and advancements of parallel robots, covering technology readiness levels (TRLs), design, the number of degrees of freedom, kinematics structure, workspace assessment, functional capabilities, performance evaluation methods, and material selection for the development of parallel robotics. It also examines critical technological challenges and future prospects in rehabilitation, assistance, and humanoid robots. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is an exam widely adopted to monitor cerebral activities regarding external stimuli, and its signals compose a nonlinear dynamical system. There are many difficulties associated with EEG analysis. For example, noise can originate from different disorders, such as muscle or physiological activity. There are also artifacts that are related to undesirable signals during EEG recordings, and finally, nonlinearities can occur due to brain activity and its relationship with different brain regions. All these characteristics make data modeling a difficult task. Therefore, using a combined approach can be the best solution to obtain an efficient model for identifying neural data and developing reliable predictions. This paper proposes a new hybrid framework combining stacked generalization (STACK) ensemble learning and a differential-evolution-based algorithm called Adaptive Differential Evolution with an Optional External Archive (JADE) to perform nonlinear system identification. In the proposed framework, five base learners, namely, eXtreme Gradient Boosting, a Gaussian Process, Least Absolute Shrinkage and Selection Operator, a Multilayer Perceptron Neural Network, and Support Vector Regression with a radial basis function kernel, are trained. The predictions from all these base learners compose STACK's layer-0 and are adopted as inputs of the Cubist model, whose hyperparameters were obtained by JADE. The model was evaluated for decoding the electroencephalography signal response to wrist joint perturbations. The variance accounted for (VAF), root-mean-squared error (RMSE), and Friedman statistical test were used to validate the performance of the proposed model and compare its results with other methods in the literature, including the base learners. The JADE-STACK model outperforms the other models in terms of accuracy, being able to explain around, as an average of all participants, 94.50% and 67.50% (standard deviations of 1.53 and 7.44, respectively) of the data variability for one step ahead and three steps ahead, which makes it a suitable approach to dealing with nonlinear system identification. Also, the improvement over state-of-the-art methods ranges from 0.6% to 161% and 43.34% for one step ahead and three steps ahead, respectively. Therefore, the developed model can be viewed as an alternative and additional approach to well-established techniques for nonlinear system identification once it can achieve satisfactory results regarding the data variability explanation. [ABSTRACT FROM AUTHOR]

Joint angles of the lower extremities have been calculated using gyroscope and accelerometer measurements from inertial measurement units (IMUs) without sensor drift by leveraging kinematic constraints. However, it is unknown whether these methods are generalizable to the upper extremity due to differences in motion dynamics. Furthermore, the extent that post-processed sensor fusion algorithms can improve measurement accuracy relative to more commonly used Kalman filter-based methods remains unknown. This study calculated the elbow and wrist joint angles of 13 participants performing a simple ≥30 min material transfer task at three rates (slow, medium, fast) using IMUs and kinematic constraints. The best-performing sensor fusion algorithm produced total root mean square errors (i.e., encompassing all three motion planes) of 6.6°, 3.6°, and 2.0° for the slow, medium, and fast transfer rates for the elbow and 2.2°, 1.7°, and 1.5° for the wrist, respectively. [ABSTRACT FROM AUTHOR]

Essex-Lopresti injuries are characterized by injuries to the proximal radio-ulnar joint, the distal radio-ulnar joint, and the interosseous membrane. This can lead to osteoarthritis, impaction syndrome, or instability. If all three structures are injured and lead to instability, the situation is almost unmanageable and many times ends in a one-bone forearm. In this article, we demonstrate a new way to reconstruct the proximal and distal radio-ulnar joint with two patient-specific coupled prostheses. These have been developed with the biomechanical conditions of the forearm in mind, where there are very large forces between the bones. As a result, we are able to present a patient previously severely restricted in the use of his hand and arm via a splint that compressed the forearm, who is now able to perform everyday activities and even light sports, such as badminton, without pain. [ABSTRACT FROM AUTHOR]

In this work, we evaluate the relationship between human manipulability indices obtained from motion sensing cameras and a variety of muscular factors extracted from surface electromyography (sEMG) signals from the upper limb during specific movements that include the shoulder, elbow and wrist joints. The results show specific links between upper limb movements and manipulability, revealing that extreme poses show less manipulability, i.e., when the arms are fully extended or fully flexed. However, there is not a clear correlation between the sEMG signals' average activity and manipulability factors, which suggests that muscular activity is, at least, only indirectly related to human pose singularities. A possible means to infer these correlations, if any, would be the use of advanced deep learning techniques. We also analyze a set of EMG metrics that give insights into how muscular effort is distributed during the exercises. This set of metrics could be used to obtain good indicators for the quantitative evaluation of sequences of movements according to the milestones of a rehabilitation therapy or to plan more ergonomic and bearable movement phases in a working task. [ABSTRACT FROM AUTHOR]

Automation of wrist rotations in upper limb prostheses allows simplification of the human–machine interface, reducing the user's mental load and avoiding compensatory movements. This study explored the possibility of predicting wrist rotations in pick-and-place tasks based on kinematic information from the other arm joints. To do this, the position and orientation of the hand, forearm, arm, and back were recorded from five subjects during transport of a cylindrical and a spherical object between four different locations on a vertical shelf. The rotation angles in the arm joints were obtained from the records and used to train feed-forward neural networks (FFNNs) and time-delay neural networks (TDNNs) in order to predict wrist rotations (flexion/extension, abduction/adduction, and pronation/supination) based on the angles at the elbow and shoulder. Correlation coefficients between actual and predicted angles of 0.88 for the FFNN and 0.94 for the TDNN were obtained. These correlations improved when object information was added to the network or when it was trained separately for each object ( 0.94 for the FFNN, 0.96 for the TDNN). Similarly, it improved when the network was trained specifically for each subject. These results suggest that it would be feasible to reduce compensatory movements in prosthetic hands for specific tasks by using motorized wrists and automating their rotation based on kinematic information obtained with sensors appropriately positioned in the prosthesis and the subject's body. [ABSTRACT FROM AUTHOR]

Comparison across somatosensory domains, important for clinical and scientific goals, requires prior calibration of impairment severity. Provided test score distributions are comparable across domains, valid comparisons of impairment can be made by reference to score locations in the corresponding distributions (percentile rank or standardized scores). However, this is often not the case. Test score distributions for tactile texture discrimination (n = 174), wrist joint proprioception (n = 112), and haptic object identification (n = 98) obtained from pooled samples of stroke survivors in rehabilitation settings were investigated. The distributions showed substantially different forms, undermining comparative calibration via percentile rank or standardized scores. An alternative approach is to establish comparable locations in the psychophysical score ranges spanning performance from just noticeably impaired to maximally impaired. Several simulation studies and a theoretical analysis were conducted to establish the score distributions expected from completely insensate responders for each domain. Estimates of extreme impairment values suggested by theory, simulation and observed samples were consistent. Using these estimates and previously discovered values for impairment thresholds in each test domain, comparable ranges of impairment from just noticeable to extreme impairment were found. These ranges enable the normalization of the three test scales for comparison in clinical and research settings. [ABSTRACT FROM AUTHOR]

The hand and wrist are among the most common anatomical areas involved in rheumatic diseases, especially seropositive and seronegative rheumatoid arthritis (RA) and psoriatic arthritis (PsA). The purpose of this study was to identify the most differentiating radiographic characteristics of PsA, seropositive RA, and seronegative RA, particularly in the early stages. A retrospective analysis of radiographic hand findings was performed on 180 seropositive RA patients (29 males, 151 females, mean age at the point of acquisition of the analyzed radiograph of 53.4 y/o, SD 12.6), 154 PsA patients (45 males, 109 females, age median of 48.1 y/o, SD 12.4), and 36 seronegative RA patients (4 males, 32 females, age median of 53.1 y/o, SD 17.1) acquired during the period 2005–2020. Posterior–anterior and Nørgaard views were analyzed in all patients. The radiographs were evaluated for three radiographic findings: type of symmetry (asymmetric/bilateral/changes in corresponding joint compartments/'mirror-image' symmetry), anatomic location (e.g., wrist, metacarpophalangeal (MCP), proximal interphalangeal (PIP), distal interphalangeal (DIP) joints), and type of lesions (e.g., juxta-articular osteoporosis, bone cysts, erosions, proliferative bone changes). The study showed that symmetric distribution of lesions defined as 'lesions present in corresponding compartments' was more suggestive of seropositive or seronegative RA than PsA. Lesions affecting the PIP joints, wrist, or styloid process of the radius; juxta-articular osteoporosis, joint space narrowing, joint subluxations, or dislocations were more common in patients with seropositive RA than in those with PsA, whereas DIP joints' involvement and proliferative bone changes were more likely to suggest PsA than seropositive RA. Lesions in PIP, MCP, and wrist joints, as well as erosions, advanced bone damage, joint subluxations, dislocations, and joint space narrowing, were more common in seropositive RA patients than in seronegative RA patients. The ulnar styloid was more commonly affected in seronegative RA patients than in PsA patients. The study confirmed that types of bone lesions and their distribution in the hands and wrists can be useful in differentiating seropositive RA from PsA and suggests that seronegative RA varies in radiological presentation from seropositive RA and PsA. [ABSTRACT FROM AUTHOR]

Background: This study assesses the variability of the palmar radiocarpal artery (PRCA), dorsal carpal branch of the ulnar artery (DCBUA), and anterior interosseous artery (AIA) in superselective catheter angiographies of the wrist (SCAW). Methods: Secondary analysis of consecutive SCAW (2009–2011). Measurements of the distances of the PRCA to the midface of the radiocarpal joint, the DCBUA to the styloid process of the ulnar, and maximum diameters of PRCA, DCBUA, and AIA. Results: Seven female and ten male patients (mean 35 years) received SCAW. All patients suffered from Kienbock's disease. The mean distance from the PRCA to the radiocarpal joint was 7.9 ± 2.3 mm and the distance from the DCBUA to the styloid process of the ulna was 29.6 ± 13.6 mm. The mean maximum diameter of the PRCA was 0.6 ± 0.2 mm, that of the DCBUA was 1.1 ± 0.4 mm, and that of the AIA 1.2 ± 0.3 mm. In six cases (35%), all three arteries contributed to the PRCA; in eight cases (47%), the radial and AIA; in two cases (12%), the radial and ulnar artery; and in one case (6%), only the radial artery contributed. Conclusions: SCAW are feasible to assist in preoperative planning. Os pisiforme transfer with DCBUA might be the best choice for a vascular bone graft in Kienbock's disease. [ABSTRACT FROM AUTHOR]

sEMG-based pattern recognition commonly assumes a limited number of target categories, and the classifiers often predict each target category depending on probability. In wrist rehabilitation training, the patients may make movements that do not belong to the target category unconsciously. However, most pattern recognition methods can only identify limited patterns and are prone to be disturbed by abnormal movement, especially for wrist joint movements. To address the above the problem, a sEMG-based rejection method for unrelated movements is proposed to identify wrist joint unrelated movements using center loss. In this paper, the sEMG signal collected by the Myo armband is used as the input of the sEMG control method. First, the sEMG signal is processed by sliding signal window and image coding. Then, the CNN with center loss and softmax loss is used to describe the spatial information from the sEMG image to extract discriminative features and target movement recognition. Finally, the deep spatial information is used to train the AE to reject unrelated movements based on the reconstruction loss. The results show that the proposed method can realize the target movements recognition and reject unrelated movements with an F-score of 93.4% and a rejection accuracy of 95% when the recall is 0.9, which reveals the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this research, a new remote rehabilitation system was developed that integrates an IoT-based connected robot intended for wrist and forearm rehabilitation. In fact, the mathematical model of the wrist and forearm joints was developed and integrated into the main controller. The proposed new rehabilitation protocol consists of three main sessions: the first is dedicated to the extraction of the passive components of the dynamic model of wrist–forearm biomechanics while the active components are extracted in the second session. The third session consists of performing continuous exercises using the determined dynamic model of the forearm–wrist joints, taking into account the torque generated by muscle fatigue. The main objective of this protocol is to determine the state level of the affected wrist and above all to provide a dynamic model in which the torque generated by the robot and the torque supplied by the patient are combined, taking into account the constraints of fatigue. A Support Vector Machine (SVM) classifier is designed for the estimation of muscle fatigue based on the features extracted from the electromyography (EMG) signal acquired from the patient. The results show that the developed rehabilitation system allows a good progression of the joint's range of motion as well as the resistive-active torques. [ABSTRACT FROM AUTHOR]

Standard industrial robotic manipulators use well-established high performing technologies. However, such manipulators do not guarantee a safe Human–Robot Interaction (HRI), limiting their usage in industrial and medical applications. This paper proposes a novel local path planner for spherical wrist manipulators to control the execution of tasks where the manipulator number of joints is redundant. Such redundancy is used to optimize robot motion and dexterity. We present an intuitive parametrization of the end-effector (EE) angular motion, which decouples the rotation of the third joint of the wrist from the rest of the angular motions. Manipulator EE motion is controlled through a decentralized linear system with closed-loop architecture. The local planner integrates a novel collision avoidance strategy based on a potential repulsive vector applied to the EE. Contrary to classic potential field approaches, the collision avoidance algorithm considers the entire manipulator surface, enhancing human safety. The local path planner is simulated in three generic scenarios: (i) following a periodic reference, (ii) a random sequence of step signal references, and (iii) avoiding instantly introduced obstacles. Time and frequency domain analysis demonstrated that the developed planner, aside from better parametrizing redundant tasks, is capable of successfully executing the simulated paths (max error = 0.25°) and avoiding obstacles. [ABSTRACT FROM AUTHOR]

The number of blood flow restriction (BFR) training practitioners is rapidly increasing, so understanding the safety issues associated with limb occlusion is strongly needed. The present study determined the effect of BFR by an inflatable cuff worn around the arm on the wrist joint position sense (JPS) in healthy recreational athletes. In the prospective randomized, double-blind placebo control study, sixty healthy right-handed recreational athletes aged x = 22.93 ± 1.26 years were assigned to groups of equal size and gender rates: BFR, placebo, and control. The active wrist JPS was assessed in two separate sessions using an isokinetic dynamometer. The first assessment was performed with no cuffs. In the second session, a cuff with a standardized pressure was worn on the examined limb in the BFR group. In the placebo group, the cuff was uninflated. A between-session comparison in each group of collected angular errors expressed in degrees was carried out. The angular error in the BFR group was larger during the second measurement than the first one (p = 0.011–0.336). On the contrary, in the placebo (p = 0.241–0.948) and control (p = 0.093–0.904) groups, the error value in the second session was comparable or smaller. It was determined that BFR by an inflatable cuff around the arm impairs the wrist position sense. Hence, BFR training should be performed with caution. [ABSTRACT FROM AUTHOR]

With advances in new materials and technologies, there has been increasing research focused on flexible sensors. However, in most flexible pressure sensors made using new materials, it is challenging to achieve high detection sensitivity across a wide pressure range. Although traditional silicon-based sensors have good performance, they are not formable and, because of their rigidity and brittleness, they are not suitable for fitting with soft human skin, which limits their application in wearable devices to collect various signals. Silicon nanomembranes are ultra-thin, flexible materials with excellent piezoresistive properties, and they can be applied in various fields, such as in soft robots and flexible devices. In this study, we developed a flexible pressure sensor based on the use of silicon nanomembranes (with a thickness of only 340 nm) as piezoresistive units, which were transferred onto a flexible polydimethylsiloxane (PDMS) substrate. The flexible pressure sensor operated normally in the range of 0–200 kPa, and the sensitivity of the sensor reached 0.0185 kPa−1 in the low-pressure range of 0–5 kPa. In the high-pressure range of 5–200 kPa, the sensitivity of the sensor was maintained at 0.0023 kPa−1. The proposed sensor exhibited a fast response and excellent long-term stability and could recognize human movements, such as the bending of fingers and wrist joints, while maintaining a stable output. Thus, the developed flexible pressure sensor has promising applications in body monitoring and wearable devices. [ABSTRACT FROM AUTHOR]

The present study attempted to define the three-dimensional (3D) locations of reference points and standard measures of the distal radius of a normal wrist joint. One hundred wrists from 50 males and 50 females who matched the age distribution (19–95 years old, mean: 56.0 years old) were evaluated. Computed tomography (CT) images of normal wrist joints acquired for comparison with the affected side were used. The absence of a previous history and complaints in the unaffected wrist was confirmed in an interview and with medical records. Three-dimensional images of the distal radius were reconstructed using the data obtained from CT scans. The site at which the major axis of the radial diaphysis contacted the distal radius joint surface was defined as the origin. The 3D coordinates of reference points for the radial styloid process (1), sigmoid notch volar edge (2), and sigmoid notch dorsal edge (3) as well as the barycenter for the joint surface and joint surface area were evaluated. A slope of the line connecting coordinates 1–2 in the coronal plane was evaluated as the 3D radial inclination (3DRI) and that connecting coordinates 2–3 in the sagittal plane as the 3D palmar tilt (3DPT). Each measurement value was compared between males and females. The positions of each reference point from the origin were as follows: (1) 14.2 ± 1.3/12.6 ± 1.1 mm for the distal-palmar-radial position; (2) 19.3 ± 1.3/16.9 ± 1.3 mm for the proximal-palmar-ulnar position; (3) 15.6 ± 1.4/14.1 ± 0.9 mm for the proximal-dorsal-ulnar position; and (barycenter) 4.1 ± 0.7/3.7 ± 0.7 mm for the proximal-volar-ulnar position for males and females, respectively. The areas of the radius articular surface were 429.0 ± 67.9/347.6 ± 44.6 mm2 for males and females, respectively. The 3DRI and 3DPT were 24.2 ± 4.0/25.7 ± 3.1° and 10.9 ± 5.1/13.2 ± 4.4° for males and females, respectively. Significant differences were observed in all measurement values between males and females (p < 0.01). The reference points and measured values obtained in the present study will serve as criteria for identifying the dislocation direction and reduction conditions of distal radius fractures in 3D images. [ABSTRACT FROM AUTHOR]

Featured Application: The findings described in this paper could be treated as recommendations in a physical therapy program for DMD patients that focus on defining conditions along with the weight (light or heavy) that could give better muscle response in rehabilitation of DMD patients. (1) Background: This study presents a new method for the motion quantitative analysis of Duchenne muscular dystrophy patients (DMD) performing functional tasks in clinical conditions. (2) Methods: An experimental study was designed to define how different levels of external mass (light and heavy) influence the performance of the upper limbs of a tested DMD and reference subject (RS) during horizontal movements (level of the waist) under natural conditions (NC) and passive manipulator conditions (PMC); the kinematic data and muscle activity of four chosen superficial muscles (EMG) were recorded. (3) Results: A piecewise linear multi-regression analysis revealed high statistically significant results (R2 ≥ 0.75) between the tested muscle activities and kinematic data in the tested DMD patient and RS. These results were used to define whether the neural control of the four tested muscles (processed EMG data) was correlated more with the displacement of the wrist joint or the center of mass of the tested upper limb while performing functional tests with a given external weight in a horizontal plane under NC or PMC. (4) Conclusions: The proposed approach can be used to estimate the contributions of the tested muscles to patients' motion performance and define whether this contribution is correlated with the kinematics or dynamics of the tested arm. [ABSTRACT FROM AUTHOR]

De La Pava Panche et al. [[4]] estimated directed phase-amplitude interactions from EEG data through kernel-based phase transfer entropy. Therefore, signal processing techniques have been applied to cancel artifacts and reduce noise, increasing the signal quality for subsequent analysis. Electrocardiogram (ECG), electrodermal activity (EDA), and electromyogram (EMG) signals were considered. [Extracted from the article]

We investigated the effect of arm pivot joints that are typically used during haptic exploration by evaluating four joints of the human arm (metacarpophalangeal joint of the index finger, wrist, elbow, and shoulder joints). Using a virtual stiffness discrimination task, a four-session psychophysical experiment was conducted with 38 participants (25 male and 13 female); each session was conducted with one of the four joints as the pivot joint during haptic exploration. The participants were asked to judge the stiffness of the top surface of two computer-generated cylinders by determining the stiffer one while using their dominant hand's index finger. A two-alternative forced-choice procedure was employed by assigning one cylinder a constant stiffness value of 1.0 N/mm (standard side) and the remaining cylinder a variable stiffness value (comparison side). Using a custom-made stylus for the Geomagic TouchTM (3D Systems, Inc., Rock Hill, SC, USA) haptic interface, the participants were able to feel the stiffness of these virtual surfaces only with their index fingers. It was observed that the average Weber fraction monotonically decreased as the pivot joint shifted toward the torso (i.e., a shift from the metacarpophalangeal joint to the shoulder joint); this decrease was not statistically significant, which suggests that the selection of the pivot joint was not a determining factor for the sensitivity to discriminate stiffness. In general, the palpation speed and force exerted by the participants on the standard side during the haptic exploration showed a tendency to increase when the pivot joint shifted toward the torso; the difference in average palpation speed and force across the pivot joints was not statistically significant. [ABSTRACT FROM AUTHOR]

This paper presents an assisted upper limb rehabilitation robot (ULRR) for patients who have experienced stroke who are in the middle and late stages of rehabilitation and have certain muscle strength. The ULRR can complete adduction and abduction motion of the shoulder joint (SJ) in the frontal plane in one step, which can save time and improve the efficiency of rehabilitation training. Based on the principles of ergonomics and rehabilitation medicine, the freedom degree of the upper limb and the motion range of each joint are determined, and the structure of the shoulder, the elbow, and the wrist joint of ULRR are designed. The kinematics model of the robot is established, and the kinematics equations are derived. Meanwhile, the simulation analysis and the workspace analysis of the robot are carried out, and the different movement forms of SJ adduction and abduction are compared and analyzed. Then, the trajectory of the robot is planned to complete the act of drinking water. Finally, an experimental platform is built to complete the ULRR to help participants complete the experiments of drinking water and active training. The experiments verify that the robot is suitable for rehabilitation tasks. [ABSTRACT FROM AUTHOR]

The wrist joint plays a vital role in activities of daily living. Clinical applications, e.g., therapeutic planning, prosthesis design, and wrist biomechanical analysis, require a detailed understanding of wrist maneuvers and motion. The lack of soft tissue information, motion analysis on limited carpal bones, etc., restrain the investigation of wrist kinematics. In this study, we established 3D models of carpal bones with their cartilages, and revealed the helical axes (HA) of all eight carpal bones for the first time. Both left and right hands at different positions of flexion-extension (FE) and radial-ulnar deviation (RUD) from five subjects were in-vivo imaged through a magnetic resonance imaging device. We segmented all of the bones, including cartilage information in the wrist joint, after which we explored the kinematics of all carpal bones with the HA method. The results showed that the HA of all carpal bones for FE bounded tightly and was mainly located slightly above the radius. During the RUD, carpal bones in the distal row rotated along with wrist movement while the scaphoid, lunate, and triquetrum primarily flexed and extended. Further results reported that the carpal bones translated greater in RUD than in FE. With the generation of more delicate wrist models and thorough investigations of carpal motion, a better understanding of wrist kinematics was obtained for further pathologic assessment and surgical treatment. [ABSTRACT FROM AUTHOR]

As the Internet of Things becomes more and more mainstream, sensors are widely used in the field of motion monitoring. In this paper, we propose a lightweight and sensitive triboelectric nanogenerator (LS-TENG) consisting of transparent polytetrafluoroethylene (PTFE) and polyamide (PA) films as triboelectric layers, polydimethylsiloxane (PDMS) as support layer, and copper foil as electrode. LS-TENG can be attached to the joints of the human body, and the mechanical energy generated by human motion is converted into electric energy based on the triboelectric effect, thus realizing self-power supply. LS-TENG can monitor the angle changes in elbow and wrist joints when athletes pull the loop and actively generate the output voltage as a sensing signal, which is convenient for coaches to monitor the quality of athletes' hitting in real time. In addition, LS-TENG can also be used as a power supply for other wireless electronic devices, which facilitates the construction and transmission of large motion data and opens up a new development direction for the field of motion monitoring. [ABSTRACT FROM AUTHOR]

This paper addresses the design, fabrication and control of Fabric Inflatable Soft Actuators (FISAs) for driving Soft Wearable Devices (SWD) for rehabilitation or assistance tasks. FISAs are integrated by a set of pneumatic chambers made of 200D TPU-nylon that create bending-extending motions using a modular assembly that allow FISAs to adapt them to any size of limb or easily replace them. Regarding FISAs fabrication, a self-hand manufacturing approach has been used for cutting, sewing, and joining them. Additionally, to evaluate FISAs operation, a Soft Exo-Sleeve called MOSAR system was manufactured to achieve elbow motion. To control their inflation-deflation process in real-time, proportional and solenoid valves have been implemented along with a Proportional-Derivative (PD) control strategy that has been embedded in the NUCLEO-STM32F767ZI™ board with rapid control prototyping. Preliminary experiments about FISA performance on the MOSAR system were carried out to measure the inflation-deflation time, Range of Motion (ROM), and output force when elbow flexion-extension occurred in a dummy limb. The results have demonstrated FISAs functionality above the exosuit since they were able to lift 1 kg with flexion of 130 ° in 5 s using 50 psi. Therefore, FISAs represent a feasible choice for semicircular motions in other joints such as the wrist, hand, or knee, no matter age, limb, or size, only the number of FISAs must be adjusted on the MOSAR system. [ABSTRACT FROM AUTHOR]

Almost half of the patients surveyed report impaired function of the upper limbx and handx after stroke. The effect of the passive trunk and shoulder stabilization on the recovery of coordinated hand movement is unclear. This study examined whether passive stabilization of the trunk and shoulder could improve the functional state of the hands after various types of strokes. It is an observational prospective cohort study conducted at the Rehabilitation Clinic in two parallel groups of patients with four different types of strokes (hemorrhagic and ischemic of the brain, similar to the cerebellum). A total of 120 patients were analyzed. Patients were examined in various positions: sitting without a backrest with the upper limb adjacent to the body, supine with the upper limb perpendicular to the body, and supine with the arm stabilized in relation to the patient's body. Hand Tutor devices and a hand dynamometer were used for the measurements. The frequency and maximum range of motion as well as the grip strength were measured in three different positions of the trunk and upper limb. Passive stabilization of the trunk and shoulder showed more statistically significant differences in Group II. In group II, both in patients after hemorrhagic stroke (wrist Hz p = 0.019; wrist ROM p = 0.005; Hz F5 p = 0.021; Hz F4 p = 0.016; Hz F3 p = 0.019; Hz F2 p = 0.021) and ischemic stroke (p = 0.001 for wrist Hz, wrist ROM, Hz F from 5 to F2; and ROM F1; ROM F3 p = 0.009; ROM F2 p = 0.010), and hemorrhagic cerebellum, improvement of parameters was observed. Stabilization of the upper limb and passive stabilization of the trunk improved the frequency and range of movements in the radiocarpal joint and in the fingers of patients after stroke, regardless of the type of stroke. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic analysis of the ParReEx multibody mechanism, which has been designed for human wrist joint rehabilitation. The starting point of the research is a virtual prototype of the ParReEx multibody mechanism. This model is used to simulate the dynamics of the multibody mechanism using ADAMS in three simulation scenarios: (a) rigid kinematic elements without friction in joints, (b) rigid kinematic elements with friction in joints, and (c) kinematic elements as deformable solids with friction in joints. In all three cases, the robot is used by a virtual patient in the form of a mannequin. Results such as the connecting forces in the kinematic joints and the torques necessary to operate the ParReEx robot modules are obtained by dynamic simulation in MSC.ADAMS. The torques obtained by numerical simulation are compared with those obtained experimentally. Finite element structural optimization (FEA) of the flexion/extension multibody mechanism module is performed. The results demonstrate the operational safety of the ParReEx multibody mechanism, which is structurally capable of supporting the external loads to which it is subjected. [ABSTRACT FROM AUTHOR]

The electromyography bridge (EMGB) plays an important role in promoting the recovery of wrist joint function in stroke patients. We investigated the effects of the EMGB on promoting the recovery of upper limb function in hemiplegia. Twenty-four stroke patients with wrist dorsal extension dysfunction were recruited. Participants were randomized to undergo EMGB treatment or neuromuscular electrical stimulation (NMES). Treatments to wrist extensors were conducted for 25 min, twice a day, 5 days per week, for 1 month. Outcome measures: active range of motion (AROM) of wrist dorsal extension; Fugl-Meyer assessment for upper extremity (FMA-UE); Barthel index (BI); and muscle strength of wrist extensors. After interventions, patients in the NMES group had significantly greater improvement in the AROM of wrist dorsal extension at the 4th week and 1st month follow-up (p < 0.05). However, patients in the EMGB group had a statistically significant increase in AROM only at the follow-up assessment. No significant differences were observed in the AROM between the EMGB group and the NMES group (p > 0.05). For secondary outcomes in the EMGB group, compared to baseline measurements, FMA-UE, BI, extensor carpi radialis and extensor carpi ulnaris muscle strength were significantly different as early as the 4th week (p < 0.05). The muscle strength of the extensor digitorum communis muscle showed significant differences at the follow-up (p < 0.05). There were no statistically significant differences between patients in the two groups in any of the parameters evaluated (p > 0.05). The combination of EMGB or NMES with conventional treatment had similar effects on the improvement of the hemiplegic upper limb as assessed by wrist dorsal extension, FMA-UE, and activities of daily living. The improvement in both groups was maintained until 1 month after the intervention. [ABSTRACT FROM AUTHOR]

Bio-inspired transverse brachiation robots mimic the movement of human climbers as they traverse along ledges on a vertical wall. The constraints on the locomotion of these robots differ considerably from those of conventional brachiation robots due primarily to the need for robust hand-eye coordination. This paper describes the development of a motion control strategy for a brachiation robot navigating between wall ledges positioned on a level plane or at different elevations. We based our robot on a four-link arm-body-tail system performing a four-phase movement, including a release phase, body reversal phase, swing-up phase, and grasping phase. We designed a gripper that uses passive wrist joint motion to grasp the ledge during the tail swing. We also developed a dynamic model by which to coordinate the swing-up movement, define the phase switching conditions, and time the grasping action of the grippers. In experiments, the robot proved highly effective in traversing between wall ledges of the same or different elevations. [ABSTRACT FROM AUTHOR]

The carpal bones are eight small bones with irregularities and high curvature on their surfaces. The 3D model of the carpal bone serves as the foundation of further clinical applications, e.g., wrist kinematic behavior. However, due to the limitation of the Magnetic Resonance Imaging (MRI) technique, reconstructed carpal bone models are discretely undersampled, which has dramatic stair-step effects and leads to abnormal meshes on edges or surfaces, etc. Our study focuses on determining the viability of various smoothing techniques for a carpal model reconstructed by in vivo gathered MR images. Five algorithms, namely the Laplacian smoothing algorithm, the Laplacian smoothing algorithm with pre-dilation, the scale-dependent Laplacian algorithm, the curvature flow algorithm, and the inverse distance algorithm, were chosen for evaluation. The assessment took into account the Relative Volume Difference and the Hausdorff Distance as well as the surface quality and the preservation of morphological and morphometric properties. For the five algorithms, we analyzed the Relative Volume Difference and the Hausdorff Distance for all eight carpal bones. Among all the algorithms, the scale-dependent Laplacian method processed the best result regarding surface quality and the preservation of morphological and morphometric properties. Based on our extensive examinations, the scale-dependent Laplacian algorithm is suitable for the undersampled carpal bone model with small volume and large curvature. [ABSTRACT FROM AUTHOR]

Recently, many muscle synergy-based human motion prediction models and algorithms have been proposed. In this study, the muscle synergies extracted from electromyography (EMG) data were used to construct a musculoskeletal model (MSM) to predict the joint angles of the wrist, thumb, index finger, and middle finger. EMG signals were analyzed using independent component analysis to reduce signal noise and task-irrelevant artifacts. The weights of each independent component (IC) were converted into a heat map related to the motion pattern and compared with human anatomy to find a different number of ICs matching the motion pattern. Based on the properties of the MSM, non-negative matrix factorization was used to extract muscle synergies from selected ICs that represent the extensor and flexor muscle groups. The effects of these choices on the prediction accuracy was also evaluated. The performance of the model was evaluated using the correlation coefficient (CC) and normalized root-mean-square error (NRMSE). The proposed method has a higher prediction accuracy than those of traditional methods, with an average CC of 92.0% and an average NRMSE of 10.7%. [ABSTRACT FROM AUTHOR]

In this study, three different musculoskeletal modeling approaches were compared to each other. The objective was to show the possibilities in the case of a simple mechanical model of the wrist, using a simple multi-body-simulation (MBS) model, and using a more complex and patient-specific adaptable wrist joint MBS model. Musculoskeletal modeling could be a useful alternative, which can be practiced as a non-invasive approach to investigate body motion and internal loads in a wide range of conditions. The goal of this study was the introduction of computer-based modelling of the physiological wrist with (MBS-) models focused on the muscle and joint forces acting on the wrist. [ABSTRACT FROM AUTHOR]

The human wrist joint is an elegant mechanism. The wrist allows the positioning and orienting of the hand to the forearm. The computational modeling of the human hand, especially of the wrist joint, can reveal important information about biomechanical mechanisms and provide the basis for its dysfunction and pathologies. For instance, this could be used for therapy planning in total wrist arthroplasty (TWA). In this study, different optimization methods and sensitivity analyses of anatomical parameters for musculoskeletal modeling were presented. Optimization includes finding the best available value of an objective function, including a variety of different types of objective functions. In the simplest case, optimization consists of maximizing or minimizing a function by systematically choosing input values from within an allowed set and computing the value of the function. Optimization techniques are used in many facets, such as the model building of joints or joint systems such as the wrist. The purpose of this study is to show the variability and influence of the included information for modeling, investigating the biomechanical function and load situation of the joint in representative scenarios. These possibilities to take them into account by an optimization and seem essential for the application of computational modeling to joint pathologies. [ABSTRACT FROM AUTHOR]

The second figure in Eschweiler et al. [[1]] provides an overview of the six muscles acting only in the wrist and not in the finger joints (flexor carpi radialis, palmaris longus, flexor carpi ulnaris, extensor carpi radialis longus, extensor carpi radialis brevis and extensor carpi ulnaris: the "wrist muscles") with regard to their size as well as their moment arms. Thus, the role of the flexor pollicis longus, extensor pollicis longus, extensor pollicis brevis, flexor digitorum profundus, extensor digiti minimi and extensor indicis should also be presented and discussed [[2]]. In addition to the six "wrist muscles", the three finger muscles (flexor digitorum superficialis, extensor digitorum and abductor pollicis longus) and their actions are also reported in the accompanying text, suggesting that finger muscles act on the wrist joint, too. [Extracted from the article]

The aim of this paper is to investigate technological advancements made to a robotic tele-ultrasound system for musculoskeletal imaging, the MSK-TIM (Musculoskeletal Telerobotic Imaging Machine). The hardware was enhanced with a force feedback sensor and a new controller was introduced. Software improvements were developed which allowed the operator to access ultrasound functions such as focus, depth, gain, zoom, color, and power Doppler controls. The device was equipped with Wi-Fi network capability which allowed the master and slave stations to be positioned in different locations. A trial assessing the system to scan the wrist was conducted with twelve participants, for a total of twenty-four arms. Both the participants and radiologist reported their experience. The images obtained were determined to be of satisfactory quality for diagnosis. The system improvements resulted in a better user and patient experience for the radiologist and participants. Latency with the VPN configuration was similar to the WLAN in our experiments. This research explores several technologies in medical telerobotics and provides insight into how they should be used in future. This study provides evidence to support larger-scale trials of the MSK-TIM for musculoskeletal imaging.

Increasing age is related to a decrease in independence of movement and with this decrease comes falls, millions of falls occur every year and the most affected people are the older adults. These falls usually have a big impact on health and independence of the older adults, as well as financial impact on the health systems. Thus, many studies have developed fall detectors from several types of sensors. Previous studies related to the creation of fall detection systems models use only one dataset that usually has a small number of samples. Training and testing machine learning models in this small scope: (i) yield overoptimistic classification rates, (ii) do not generalize to real-life situations and (iii) have very high rate of false positives. Given this, the proposal of this research work is the creation of a new dataset that encompasses data from three different datasets, with more than 1300 fall samples and 28 K negative samples. Our new dataset includes a standard way of adding samples, which allow the future addition of other data sources. We evaluate our dataset by using classic cost-sensitive Machine Leaning methods that deal with class imbalance. For the training and validation of this model, a set of temporal and frequency features were extracted from the raw data of an accelerometer and a gyroscope using a sliding window of 2 s with an overlap of 50%. We study the generalization properties of each dataset, by testing on the other datasets and also the performance of our new dataset. The model showed a good ability to distinguish between activities of daily living and falls, achieving a recall of 90.57%, a specificity of 96.91% and an Area Under the Receiver Operating Characteristic curve (AUC-ROC) value of 98.85% against the combination of three datasets.

Most of the established gait evaluation methods use inertial sensors mounted in the lower limb area (tibias, ankles, shoes). Such sensor placement gives good results in laboratory conditions but is hard to apply in everyday scenarios due to the sensors' fragility and the user's comfort. The paper presents an algorithm that enables translation of the inertial signal measurements (acceleration and angular velocity) registered with a wrist-worn sensor to signals, which would be obtained if the sensor was worn on a tibia or a shoe. Four different neural network architectures are considered for that purpose: Dense and CNN autoencoders, a CNN-LSTM hybrid, and a U-Net-based model. The performed experiments have shown that the CNN autoencoder and U-Net can be successfully applied for inertial signal translation purposes. Estimating gait parameters based on the translated signals yielded similar results to those obtained based on shoe-sensor signals.