Wrist Angle Research Articles

Predicting Shot Accuracy in Badminton Using Quiet Eye Metrics and Neural Networks

This paper presents a novel approach to predicting shot accuracy in badminton by analyzing Quiet Eye (QE) metrics such as QE duration, fixation points, and gaze dynamics. We develop a neural network model that combines visual data from eye-tracking devices with biomechanical data such as body posture and shuttlecock trajectory. Our model is designed to predict shot accuracy, providing insights into the role of QE in performance. The study involved 30 badminton players of varying skill levels from the Chinese Swimming Club in Singapore. Using a combination of eye-tracking technology and motion capture systems, we collected data on QE metrics and biomechanical factors during a series of badminton shots for a total of 750. Key results include: (1) The neural network model achieved 85% accuracy in predicting shot outcomes, demonstrating the potential of integrating QE metrics with biomechanical data. (2) QE duration and onset were identified as the most significant predictors of shot accuracy, followed by racket speed and wrist angle at impact. (3) Elite players exhibited significantly longer QE durations (M = 289.5 ms) compared to intermediate (M = 213.7 ms) and novice players (M = 168.3 ms). (4) A strong positive correlation (r = 0.72) was found between QE duration and shot accuracy across all skill levels. These findings have important implications for badminton training and performance evaluation. The study suggests that QE-based training programs could significantly enhance players’ shot accuracy. Furthermore, the predictive model developed in this study offers a framework for real-time performance analysis and personalized training regimens in badminton. By bridging cognitive neuroscience and sports performance through advanced data analytics, this research paves the way for more sophisticated, individualized training approaches in badminton and potentially other fast-paced sports. Future research directions include exploring the temporal dynamics of QE during matches and developing real-time feedback systems based on QE metrics.

Bayesian inference in arm posture perception.

To configure our limbs in space the brain must compute their position based on sensory information provided by mechanoreceptors in the skin, muscles, and joints. Because this information is corrupted by noise, the brain is thought to process it probabilistically, and integrate it with prior belief about arm posture, following Bayes' rule. Here, we combined computational modeling with behavioral experimentation to test this hypothesis. The model conceives the perception of arm posture as the combination of a probabilistic kinematic chain composed by the shoulder, elbow, and wrist angles, compromised with additive Gaussian noise, with a Gaussian prior about these joint angles. We tested whether the model explains errors in a VR-based posture matching task better than a model that assumes a uniform prior. Human participants were required to align their unseen right arm to a target posture, presented as a visual configuration of the arm in the horizontal plane. Results show idiosyncratic biases in how participants matched their unseen arm to the target posture. We used maximum likelihood estimation to fit the Bayesian model to these observations and estimate key parameters including the prior means and its variance-covariance structure. The Bayesian model including a Gaussian prior explained the response biases and variance much better than a model with a uniform prior. The prior varied across participants, consistent with the idiosyncrasies in arm posture perception, and in alignment with previous behavioral research. Our work clarifies the biases in arm posture perception within a new perspective on the nature of proprioceptive computations.

Ultrasound-Based Grading of Carpal Tunnel Syndrome: A Comparative Study of Cross-Sectional Area and Shear Wave Elastography at Different Wrist Joint Angles.

Carpal Tunnel Syndrome (CTS) is a prevalent neuropathy where accurate diagnosis is crucial for effective treatment planning. This study introduces a novel approach for CTS grading using ultrasound, specifically through the analysis of the cross-sectional area (CSA) and shear wave elastography (SWE) of the median nerve in various wrist positions. Our research involved subjects from outpatient clinics, diagnosed with CTS through Nerve Conduction Studies (NCS), and a control group of healthy individuals. High-frequency ultrasound and SWE measurements were conducted in three wrist positions: straight, 45° extension, and 45° flexion. The key findings revealed significant differences in median nerve CSA and SWE values between the CTS and control groups across all wrist positions, with notable variances in SWE values correlating with wrist positioning. SWE demonstrated enhanced sensitivity and specificity in distinguishing between mild, moderate, and severe CTS, especially at 45° wrist flexion. In contrast, CSA measurements were limited in differentiating between the varying severity stages of CTS. The study concludes that SWE, particularly at 45° wrist flexion, provides a more precise diagnostic benchmark for CTS severity grading than CSA. This advancement in non-invasive diagnostic methodology not only aids in accurate CTS grading but also has significant implications in formulating tailored treatment strategies, potentially reducing the reliance on more invasive diagnostic methods like NCS. This study marks a significant advancement in the ultrasound diagnosis of CTS. It particularly highlights the importance of applying SWE technology across various wrist joint angles, offering a new diagnostic benchmark. This discovery provides data support and additional insights for achieving an early consensus on ultrasound-based grading diagnosis of CTS.

Evaluating Joint Angle Data for Clinical Assessment Using Multidimensional Inverse Kinematics with Average Segment Morphometry.

Movement analysis is a critical tool in understanding and addressing various disabilities associated with movement deficits. By analyzing movement patterns, healthcare professionals can identify the root causes of these alterations, which is essential for preventing, diagnosing, and rehabilitating a broad spectrum of medical conditions, disabilities, and injuries. With the advent of affordable motion capture technologies, quantitative data on patient movement is more accessible to clinicians, enhancing the quality of care. Nonetheless, it is crucial that these technologies undergo rigorous validation to ensure their accuracy in collecting and monitoring patient movements, particularly for remote healthcare services where direct patient observation is not possible. In this study, motion capture technology was used to track upper extremity movements during a reaching task presented in virtual reality. Kinematic data was then calculated for each participant using a scaled dynamic inertial model. The goal was to evaluate the accuracy of joint angle calculations using inverse kinematics from motion capture relative to the typical movement redundancy. Shoulder, elbow, radioulnar, and wrist joint angles were calculated with models scaled using either direct measurements of each individual's arm segment lengths or those lengths were calculated from individual height using published average proportions. The errors in joint angle trajectories calculated using the two methods of model scaling were compared to the inter-trial variability of those trajectories. The variance of this error was primarily within the normal range of variability between repetitions of the same movements. This suggests that arm joint angles can be inferred with good enough accuracy from motion capture data and individual height to be useful for the clinical assessment of motor deficits.

Preliminary Evaluation of New Wearable Sensors to Study Incongruous Postures Held by Employees in Viticulture.

Musculoskeletal Disorders (MSDs) stand as a prominent cause of injuries in modern agriculture. Scientific research has highlighted a causal link between MSDs and awkward working postures. Several methods for the evaluation of working postures, and related risks, have been developed such as the Rapid Upper Limb Assessment (RULA). Nevertheless, these methods are generally applied with manual measurements on pictures or videos. As a consequence, their applicability could be scarce, and their effectiveness could be limited. The use of wearable sensors to collect kinetic data could facilitate the use of these methods for risk assessment. Nevertheless, the existing system may not be usable in the agricultural and vine sectors because of its cost, robustness and versatility to the various anthropometric characteristics of workers. The aim of this study was to develop a technology capable of collecting accurate data about uncomfortable postures and repetitive movements typical of vine workers. Specific objectives of the project were the development of a low-cost, robust, and wearable device, which could measure data about wrist angles and workers' hand positions during possible viticultural operations. Furthermore, the project was meant to test its use to evaluate incongruous postures and repetitive movements of workers' hand positions during pruning operations in vineyard. The developed sensor had 3-axis accelerometers and a gyroscope, and it could monitor the positions of the hand-wrist-forearm musculoskeletal system when moving. When such a sensor was applied to the study of a real case, such as the pruning of a vines, it permitted the evaluation of a simulated sequence of pruning and the quantification of the levels of risk induced by this type of agricultural activity.

Relationship of Kinematic Variables with the Performance of uprise on rings in Men’s Artistic Gymnastics

An investigationwas done to find the relation between selected kinematic variables and theperformance of uprise on rings in men’s artistic gymnastics.The study was conducted on national-levelgymnasts. The data on angular kinematic variables were collected on four different phases of uprise onrings. Linear kinematic variables were identifiedon two different phases of uprise on rings.The angular kinematic variables did not show any significant relationship at the 0.05 level at theDislocation Phase.Duringthe Vertical Line Cross Phasea significant relationship was found between angle atthe ankle andthe hipangle. InKicking and Pulling Phase angle at the left hip joint and the performance of Uprisehasshown a significant relationship.During the Supporting phase angle at the neck and the performance ofUprisewas showing a significant relationship, and also the angle of the left Wrist correlated significantlywith the angle of the Hip.Results also reveal that none of the linear kinematic variables at different Phases of Uprise showed anysignificant relationship at 0.05 level

Optimizing PID control for enhanced stability of a 16‐DOF biped robot during ditch crossing

AbstractThe current research article discusses the design of a proportional–integral–derivative (PID) controller to obtain the optimal gait planning algorithm for a 16‐degrees‐of‐freedom biped robot while crossing the ditch. The gait planning algorithm integrates an initial posture, position, and desired trajectories of the robot's wrist, hip, and foot. A cubic polynomial trajectory is assigned for wrist, hip, and foot trajectories to generate the motion. The foot and wrist joint angles of the biped robot along the polynomial trajectory are obtained by using the inverse kinematics approach. Moreover, the dynamic balance margin was estimated by using the concept of the zero‐moment point. To enhance the smooth motion of the gait planner and reduce the error between two consecutive joint angles, the authors designed a PID controller for each joint of the biped robot. To design a PID controller, the dynamics of the biped robot are essential, and it was obtained using the Lagrange–Euler formulation. The gains, that is, KP, KD, and KI of the PID controller are tuned with nontraditional optimization algorithms, such as particle swarm optimization (PSO), differential evolution (DE), and compared with modified chaotic invasive weed optimization (MCIWO) algorithms. The result indicates that the MCIWO‐PID controller generates more dynamically balanced gaits when compared with the DE and PSO‐PID controllers.

A Novel TCN-LSTM Hybrid Model for sEMG-Based Continuous Estimation of Wrist Joint Angles.

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.

Comparison of Six Sensor Fusion Algorithms with Electrogoniometer Estimation of Wrist Angle in Simulated Work Tasks.

Hand-intensive work is strongly associated with work-related musculoskeletal disorders (WMSDs) of the hand/wrist and other upper body regions across diverse occupations, including office work, manufacturing, services, and healthcare. Addressing the prevalence of WMSDs requires reliable and practical exposure measurements. Traditional methods like electrogoniometry and optical motion capture, while reliable, are expensive and impractical for field use. In contrast, small inertial measurement units (IMUs) may provide a cost-effective, time-efficient, and user-friendly alternative for measuring hand/wrist posture during real work. This study compared six orientation algorithms for estimating wrist angles with an electrogoniometer, the current gold standard in field settings. Six participants performed five simulated hand-intensive work tasks (involving considerable wrist velocity and/or hand force) and one standardised hand movement. Three multiplicative Kalman filter algorithms with different smoothers and constraints showed the highest agreement with the goniometer. These algorithms exhibited median correlation coefficients of 0.75-0.78 for flexion/extension and 0.64 for radial/ulnar deviation across the six subjects and five tasks. They also ranked in the top three for the lowest mean absolute differences from the goniometer at the 10th, 50th, and 90th percentiles of wrist flexion/extension (9.3°, 2.9°, and 7.4°, respectively). Although the results of this study are not fully acceptable for practical field use, especially for some work tasks, they indicate that IMU-based wrist angle estimation may be useful in occupational risk assessments after further improvements.

Evaluation of a cadaveric wrist motion simulator using marker-based X-ray reconstruction of moving morphology.

Surgical intervention is a common option for the treatment of wrist joint arthritis and traumatic wrist injury. Whether this surgery is arthrodesis or a motion preserving procedure such as arthroplasty, wrist joint biomechanics are inevitably altered. To evaluate effects of surgery on parameters such as range of motion, efficiency and carpal kinematics, repeatable and controlled motion of cadaveric specimens is required. This study describes the development of a device that enables cadaveric wrist motion to be simulated before and after motion preserving surgery in a highly controlled manner. The simulator achieves joint motion through the application of predetermined displacements to the five major tendons of the wrist, and records tendon forces. A pilot experiment using six wrists aimed to evaluate its accuracy and reproducibility. Biplanar X-ray videoradiography (BPVR) and X-Ray Reconstruction of Moving Morphology (XROMM) were used to measure overall wrist angles before and after total wrist arthroplasty. The simulator was able to produce flexion, extension, radioulnar deviation, dart thrower's motion and circumduction within previously reported functional ranges of motion. Pre- and post-surgical wrist angles did not significantly differ. Intra-specimen motion trials were repeatable; root mean square errors between individual trials and average wrist angle and tendon force profiles were below 1° and 2 N respectively. Inter-specimen variation was higher, likely due to anatomical variation and lack of wrist position feedback. In conclusion, combining repeatable intra-specimen cadaveric motion simulation with BPVR and XROMM can be used to determine potential effects of motion preserving surgeries on wrist range of motion and biomechanics.

Scapholunate Ligament Reconstruction With Internal Brace Augmentation Techniques for Chronic Scapholunate Dissociation: A Clinical Follow-up Study.

The scapholunate ligament is the most important stabilizer of the scapholunate articulation. The management of chronic irreversible injuries of this ligament in the absence of preexisting arthritis of the wrist joint remains controversial. Recently, surgeons introduced a novel surgical technique using an internal brace (IB). Several biomechanical studies on this technique have been conducted using cadavers; however, very few studies have discussed the results in detail in actual clinical practice. Therefore, herein, we investigated the radiological and functional results of patients who underwent IB augmentation as a treatment for chronic scapholunate dissociation. This retrospective study was conducted from April 2018 to May 2022. Twenty-two patients with chronic scapholunate dissociation were treated using the IB augmentation technique, of whom 17 were followed-up for at least 1 year. Radiological results, including scapholunate distance, scapholunate angle, and radioscaphoid angle, were collected. Furthermore, clinical parameters, such as the visual analog scale (preoperative and at final follow-up), the Disabilities of the Arm, Shoulder, and Hand scores (preoperatively and at 3, 6, and 12 months postoperatively), and Mayo wrist scores (preoperative and at final follow-up), were measured. The scapholunate distance increased significantly in the affected wrist compared to the unaffected wrist, which improved after reconstruction in all wrist positions ( P < 0.05). Compared to the unaffected wrist, the scapholunate angle increased significantly in all positions ( P < 0.05) except for extension ( P = 0.535) and improved after reconstruction in all wrist positions. The radioscaphoid angle significantly increased compared to the angle of the unaffected wrist in all positions ( P < 0.05) except for extension ( P = 0.602) and clenched fist ( P = 0.556). This angle improved after reconstruction in all wrist positions except for extension ( P = 0.900). The visual analog scale score (7-2, preoperatively and at final follow-up) and Mayo wrist score (53-82, preoperatively and at final follow-up) improved after surgery. The Disabilities of the Arm, Shoulder, and Hand scores also improved after surgery (68, 53, 30, 7, preoperatively and at 3, 6, and 12 months postoperatively). This study revealed that scapholunate ligament reconstruction using an autologous tendon and suture tape is a good reconstruction technique that can improve clinical symptoms and radiographic parameters with a shorter operation time and fewer complications than other reconstruction methods.

Comparing the posture and comfort of anaesthesiologists during laryngoscopy and tracheal intubation in the head-elevated laryngoscopy position in supine position and with a 25° backup: A randomised clinical crossover trial.

The head-elevated laryngoscopy position (HELP) and a 25° backup have been proposed to enhance glottic visualisation, yet concerns about ergonomic discomfort hinder their widespread adoption. This study compares the comfort and posture adopted by anaesthesiologists while performing laryngoscopy and tracheal intubation with patients in HELP while in a supine position or with 25° backup. The study included 48 patients aged 18-60 years with normal airways and 12 experienced anaesthesiologists. Patients were randomised into two groups using permuted block randomisation. Anaesthesiologists performed laryngoscopy and intubation in supine HELP and 25° backup HELP positions. Anaesthesiologist's posture was determined by measuring the angles of neck, wrist, elbow, back and knee joints, which were compared using Student's t-test, and subjective comfort assessed on a Likert scale was compared using the Chi-square test. As mentioned by the anaesthesiologist, Cormack- Lehane grading was also noted and compared using a Chi-square test between groups, taking a P value <0.05 as significant. Both positions demonstrated comparable anaesthesiologist posture (P = 0.919) and comfort (P = 0.644). However, the 25° backup HELP positions significantly improved Cormack-Lehane grades, with 68% achieving grade 1 compared to 31% in the supine HELP group (P = 0.012). Haemodynamic stability and tracheal intubation time showed no significant differences between the groups (P = 0.475 and 0.117, respectively), and no complications were reported in either group. Anaesthesiologists' posture and comfort during laryngoscopy and tracheal intubation are similar between supine and 25° backup in patients with easy airways.

Graph-Driven Simultaneous and Proportional Estimation of Wrist Angle and Grasp Force via High-Density EMG.

Myoelectric prostheses are generally unable to accurately control the position and force simultaneously, prohibiting natural and intuitive human-machine interaction. This issue is attributed to the limitations of myoelectric interfaces in effectively decoding multi-degree-of-freedom (multi-DoF) kinematic and kinetic information. We thus propose a novel multi-task, spatial-temporal model driven by graphical high-density electromyography (HD-EMG) for simultaneous and proportional control of wrist angle and grasp force. Twelve subjects were recruited to perform three multi-DoF movements, including wrist pronation/supination, wrist flexion/extension, and wrist abduction/adduction while varying grasp force. Experimental results demonstrated that the proposed model outperformed five baseline models, with the normalized root mean square error of 13.2% and 9.7% and the correlation coefficient of 89.6% and 91.9% for wrist angle and grasp force estimation, respectively. In addition, the proposed model still maintained comparable accuracy even with a significant reduction in the number of HD-EMG electrodes. To the best of our knowledge, this is the first study to achieve simultaneous and proportional wrist angle and grasp force control via HD-EMG and has the potential to empower prostheses users to perform a broader range of tasks with greater precision and control, ultimately enhancing their independence and quality of life.

Distributed sensing along fibers for smart clothing.

Textile sensors transform our everyday clothing into a means to track movement and biosignals in a completely unobtrusive way. One major hindrance to the adoption of "smart" clothing is the difficulty encountered with connections and space when scaling up the number of sensors. There is a lack of research addressing a key limitation in wearable electronics: Connections between rigid and textile elements are often unreliable, and they require interfacing sensors in a way incompatible with textile mass production methods. We introduce a prototype garment, compact readout circuit, and algorithm to measure localized strain along multiple regions of a fiber. We use a helical auxetic yarn sensor with tunable sensitivity along its length to selectively respond to strain signals. We demonstrate distributed sensing in clothing, monitoring arm joint angles from a single continuous fiber. Compared to optical motion capture, we achieve around five degrees error in reconstructing shoulder, elbow, and wrist joint angles.

Adaptive HD-sEMG decomposition: towards robust real-time decoding of neural drive.

Objective. Neural interfacing via decomposition of high-density surface electromyography (HD-sEMG) should be robust to signal non-stationarities incurred by changes in joint pose and contraction intensity.Approach. We present an adaptive real-time motor unit decoding algorithm and test it on HD-sEMG collected from the extensor carpi radialis brevis during isometric contractions over a range of wrist angles and contraction intensities. The performance of the algorithm was verified using high-confidence benchmark decompositions derived from concurrently recorded intramuscular electromyography.Main results. In trials where contraction conditions between the initialization and testing data differed, the adaptive decoding algorithm maintained significantly higher decoding accuracies when compared to static decoding methods.Significance. Using "gold standard" verification techniques, we demonstrate the limitations of filter re-use decoding methods and show the necessity of parameter adaptation to achieve robust neural decoding.

Measurement of 3D Wrist Angles by Combining Textile Stretch Sensors and AI Algorithm.

The wrist is one of the most complex joints in our body, composed of eight bones. Therefore, measuring the angles of this intricate wrist movement can prove valuable in various fields such as sports analysis and rehabilitation. Textile stretch sensors can be easily produced by immersing an E-band in a SWCNT solution. The lightweight, cost-effective, and reproducible nature of textile stretch sensors makes them well suited for practical applications in clothing. In this paper, wrist angles were measured by attaching textile stretch sensors to an arm sleeve. Three sensors were utilized to measure all three axes of the wrist. Additionally, sensor precision was heightened through the utilization of the Multi-Layer Perceptron (MLP) technique, a subtype of deep learning. Rather than fixing the measurement values of each sensor to specific axes, we created an algorithm utilizing the coupling between sensors, allowing the measurement of wrist angles in three dimensions. Using this algorithm, the error angle of wrist angles measured with textile stretch sensors could be measured at less than 4.5°. This demonstrated higher accuracy compared to other soft sensors available for measuring wrist angles.

Wrist position affects muscle fatigue during isometric contractions of wrist flexors: An exploratory study

ObjectiveTo investigate the influence of wrist position and torque level on lower arm flexor muscle fatigue. BackgroundWork-related musculoskeletal health risks at the wrist joint may depend on joint position and torque level, as proposed by ergonomic workplace assessment tools. As empirical data are scarce, muscle fatigue, as proxy of work-related musculoskeletal health risks, can be used to explore this assumption. Method18 healthy participants performed fatiguing isometric wrist flexion contractions in three wrist positions (40° flexion, 0° neutral position, and 40° extension) and torque levels (10, 20, 40% of the maximum voluntary contraction). Electromyographic signs of fatigue were analyzed in the flexor carpi radialis (FCR) and flexor digitorum superficialis (FDS) muscles. ResultsMuscle fatigue was dependent on torque level and wrist position and differed between muscles. Signs of fatigue were more evident at higher torque levels for both muscles. While fatigue signs in FCR were not clearly associated with wrist position, the FDS fatigued more during wrist flexion. An interaction effect between torque level and wrist position was not observed. ConclusionHigher torque levels induce greater signs of local muscle fatigue in wrist flexor muscles, and a 40° wrist flexion triggers fatigue, while 40° wrist extension does not. Our data do not support the assumption of increased risk in greater wrist angles in any direction by prevailing ergonomic risk assessments. Relevance to industryPeople with work-related wrist flexor effort may be at increased risk of musculoskeletal disorders when higher torques are applied and flexed wrist positions are required.

Wrist Guards/Supports in Gymnastics: Are They Helping or Hurting You?

Background: The prevalence of wrist pain among gymnasts ranges from 46% to 79%. To alleviate wrist pain, gymnasts wear wrist guards/supports (WG/S). Purpose: To investigate the effect of WG/S on the wrist joint through joint moment, angles, total joint range of motion (ROM) arc, and ground-reaction force (GRF). Study Design: Controlled laboratory study. Methods: A cross-sectional study design was used to investigate 23 female gymnasts (mean ± SD: age, 12.3 ± 1.5 years; height, 143.4 ± 7.6 cm; mass, 37.7 ± 6.6 kg; body mass index, 18.6 ± 2.9) who performed back handsprings (analyzed by first half [phase 1] and second half [phase 2]) with the following 3 conditions: no WG/S, Skids/Ultimate Wrist Supports (S/UWS), and Tiger Paws (TP). Wrist joint moments, angles, total ROM arc, and GRF were examined by the 3 conditions using analysis of variance with Bonferroni correction and effect size (Cohen d). Results: For mean wrist flexion moment, both S/UWS and TP showed significantly higher values than the no-WG/S condition in landing phase 1 (S/UWS: P = .001, d = 1.30; TP: P = .019, d = 0.87). In angle comparisons in landing phase 1, no WG/S showed greater mean wrist extension angles compared with S/UWS (P = .046; d = 0.80), but no significant differences with TP (P = .096; d = 0.65). Also, in landing phase 1, total ROM arc of the right wrist was greater in the no-WG/S condition compared with S/UWS (P = .018; d = 0.88), but there were no differences with TP (P = .400; d = 0.52). Conclusion: These data show an increased wrist flexion moment using S/UWS and TP compared with the no-WG/S condition in landing phase 1 of back handsprings. Also, increased wrist extension angles and total arc ROM of the right wrist were found in the no-WG/S condition compared with S/UWS, but not with TP in landing phase 1. S/UWS may be helpful to reduce wrist joint angles, specifically wrist extension in landing phase 1, but both S/UWS and TP caused higher wrist flexion joint moment in landing phase 1. There were no differences found in GFG among the three variables. Clinical Relevance: In the first half of the back handspring, wrist guards can limit wrist extension joint angles and total arc ROM; however, an increased wrist flexion moment was found when wrist guards were worn, which may potentially lead to an increased risk of injury. Injury history, especially overuse signs/symptoms, and previous surgery on the wrist joint need to be well considered before the application or use of wrist guards. Also, the amount of time/exposure wearing wrist guards should be carefully controlled in young female gymnasts.

Drift-Free Joint Angle Calculation Using Inertial Measurement Units without Magnetometers: An Exploration of Sensor Fusion Methods for the Elbow and Wrist.

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.

Effects of wrist posture and stabilization on precision grip force production and muscle activation patterns.

Most of the power for generating forces in the fingers arises from muscles located in the forearm. This configuration maximizes finger joint range of motion while minimizing finger mass and inertia. The resulting multiarticular arrangement of the tendons, however, complicates independent control of the wrist and the digits. Actuating the wrist impacts sensorimotor control of the fingers and vice versa. The goal of this study was to systematically investigate interactions between isometric wrist and digit control. Specifically, we examined how the need to maintain a specified wrist posture influences precision grip. Fifteen healthy adults produced maximum precision grip force at 11 different wrist flexion/extension angles, with the arm supported, under two conditions: 1) the participant maintained the desired wrist angle while performing the precision grip and 2) a robot maintained the specified wrist angle. Wrist flexion/extension posture significantly impacted maximum precision grip force (P < 0.001), with the greatest grip force achieved when the wrist was extended 30° from neutral. External wrist stabilization by the robot led to a 20% increase in precision grip force across wrist postures. Increased force was accompanied by increased muscle activation but with an activation pattern similar to the one used when the participant had to stabilize their wrist. Thus, simultaneous wrist and finger requirements impacted performance of an isometric finger task. External wrist stabilization can promote increased precision grip force resulting from increased muscle activation. These findings have potential clinical significance for individuals with neurologically driven finger weakness, such as stroke survivors.NEW & NOTEWORTHY We explored the interdependence between wrist and fingers by assessing the influence of wrist posture and external stabilization on precision grip force generation. We found that maximum precision grip force occurred at an extended wrist posture and was 20% greater when the wrist was Externally Stabilized. The latter resulted from amplification of muscle activation patterns from the Self-Stabilized condition rather than adoption of new patterns exploiting external wrist stabilization.