The use of accelerometer bracelets to evaluate arm motor function over a stroke rehabilitation period - an explorative observational study.

BACKGROUND: Assessments of arm motor function are usually based on clinical examinations or self-reported rating scales. Wrist-worn accelerometers can be a good complement to measure movement patterns after stroke. Currently there is limited knowledge of how accelerometry correlate to clinically used scales. The purpose of this study was therefore to evaluate the relationship between intermittent measurements of wrist-worn accelerometers and the patient's progression of arm motor function assessed by routine clinical outcome measures during a rehabilitation period. METHODS: Patients enrolled in in-hospital rehabilitation following a stroke were invited. Included patients were asked to wear wrist accelerometers for 24 h at the start (T1) and end (T2) of their rehabilitation period. On both occasions arm motor function was assessed by the modified Motor Assessment Scale (M_MAS) and the Motor Activity Log (MAL). The recorded accelerometry was compared to M_MAS and MAL. RESULTS: 20 patients were included, of which 18 completed all measurements and were therefore included in the final analysis. The resulting Spearman's rank correlation coefficient showed a strong positive correlation between measured wrist acceleration in the affected arm and M-MAS and MAL values at T1, 0.94 (p < 0.05) for M_MAS and 0.74 (p < 0.05) for the MAL values, and a slightly weaker positive correlation at T2, 0.57 (p < 0.05) for M_MAS and 0.46 - 0.45 (p = 0.06) for the MAL values. However, no correlation was seen for the difference between the two sessions. CONCLUSIONS: The results confirm that the wrist acceleration can differentiate between the affected and non-affected arm, and that there is a positive correlation between accelerometry and clinical measures. Many of the patients did not change their M-MAS or MAL scores during the rehabilitation period, which may explain why no correlation was seen for the difference between measurements during the rehabilitation period. Further studies should include continuous accelerometry throughout the rehabilitation period to reduce the impact of day-to-day variability.

Muscle Synergy during Wrist Movements Based on Non-Negative Tucker Decomposition.

Modular control of the muscle, which is called muscle synergy, simplifies control of the movement by the central nervous system. The purpose of this study was to explore the synergy in both the frequency and movement domains based on the non-negative Tucker decomposition (NTD) method. Surface electromyography (sEMG) data of 8 upper limb muscles in 10 healthy subjects under wrist flexion (WF) and wrist extension (WE) were recorded. NTD was selected for exploring the multi-domain muscle synergy from the sEMG data. The results showed two synergistic flexor pairs, Palmaris longus-Flexor Digitorum Superficialis (PL-FDS) and Extensor Carpi Radialis-Flexor Carpi Radialis (ECR-FCR), in the WF stage. Their spectral components are mainly in the respective bands 0-20 Hz and 25-50 Hz. And the spectral components of two extensor pairs, Extensor Digitorum-Extensor Carpi Ulnar (ED-ECU) and Extensor Carpi Radialis-Brachioradialis (ECR-B), are mainly in the respective bands 0-20 Hz and 7-45 Hz in the WE stage. Additionally, further analysis showed that the Biceps Brachii (BB) muscle was a shared muscle synergy module of the WE and WF stage, while the flexor muscles FCR, PL and FDS were the specific synergy modules of the WF stage, and the extensor muscles ED, ECU, ECR and B were the specific synergy modules of the WE stage. This study showed that NTD is a meaningful method to explore the multi-domain synergistic characteristics of multi-channel sEMG signals. The results can help us to better understand the frequency features of muscle synergy and shared and specific synergies, and expand the study perspective related to motor control in the nervous system.

Association between wrist-worn free-living accelerometry and hand grip strength in middle-aged and older adults.

INTRODUCTION: Wrist-worn activity monitors have seen widespread adoption in recent times, particularly in young and sport-oriented cohorts, while their usage among older adults has remained relatively low. The main limitations are in regards to the lack of medical insights that current mainstream activity trackers can provide to older subjects. One of the most important research areas under investigation currently is the possibility of extrapolating clinical information from these wearable devices. METHODS: The research question of this study is understanding whether accelerometry data collected for 7-days in free-living environments using a consumer-based wristband device, in conjunction with data-driven machine learning algorithms, is able to predict hand grip strength and possible conditions categorized by hand grip strength in a general population consisting of middle-aged and older adults. RESULTS: The results of the regression analysis reveal that the performance of the developed models is notably superior to a simple mean-predicting dummy regressor. While the improvement in absolute terms may appear modest, the mean absolute error (6.32 kg for males and 4.53 kg for females) falls within the range considered sufficiently accurate for grip strength estimation. The classification models, instead, excel in categorizing individuals as frail/pre-frail, or healthy, depending on the T-score levels applied for frailty/pre-frailty definition. While cut-off values for frailty vary, the results suggest that the models can moderately detect characteristics associated with frailty (AUC-ROC: 0.70 for males, and 0.76 for females) and viably detect characteristics associated with frailty/pre-frailty (AUC-ROC: 0.86 for males, and 0.87 for females). CONCLUSIONS: The results of this study can enable the adoption of wearable devices as an efficient tool for clinical assessment in older adults with multimorbidities, improving and advancing integrated care, diagnosis and early screening of a number of widespread diseases.

Illusory Directional Sensation Induced by Asymmetric Vibrations Influences Sense of Agency and Velocity in Wrist Motions.

Illusory directional sensations are generated through asymmetric vibrations applied to the fingertips and have been utilized to induce upper-limb motions in the rehabilitation and training of patients with visual impairment. However, its effects on motor control remain unclear. This study aimed to verify the effects of illusory directional sensations on wrist motion. We conducted objective and subjective evaluations of wrist motion during a motor task, while inducing an illusory directional sensation that was congruent or incongruent with wrist motion. We found that, when motion and illusory directional sensations were congruent, the sense of agency for motion decreased. This indicates an induction sensation of the hand being moved by the illusion. Interestingly, although no physical force was applied to the hand, the angular velocity of the wrist was higher in the congruent condition than that in the no-stimulation condition. The angular velocity of the wrist and electromyography signals of the agonist muscles were weakly positively correlated, suggesting that the participants may have increased their wrist velocity. In other words, the congruence between the direction of motion and illusory directional sensation induced the sensation of the hand being moved, even though the participants' wrist-motion velocity increased. This phenomenon can be explained by the discrepancy between the sensation of active motion predicted by the efferent copy, and that of actual motion caused by the addition of the illusion. The findings of this study can guide the design of novel rehabilitation methods.

A machine-learning method isolating changes in wrist kinematics that identify age-related changes in arm movement.

Normal aging often results in an increase in physiological tremors and slowing of the movement of the hands, which can impair daily activities and quality of life. This study, using lightweight wearable non-invasive sensors, aimed to detect and identify age-related changes in wrist kinematics and response latency. Eighteen young (ages 18-20) and nine older (ages 49-57) adults performed two standard tasks with wearable inertial measurement units on their wrists. Frequency analysis revealed 5 kinematic variables distinguishing older from younger adults in a postural task, with best discrimination occurring in the 9-13 Hz range, agreeing with previously identified frequency range of age-related tremors, and achieving excellent classifier performance (0.86 AUROC score and 89% accuracy). In a second pronation-supination task, analysis of angular velocity in the roll axis identified a 71 ms delay in initiating arm movement in the older adults. This study demonstrates that an analysis of simple kinematic variables sampled at 100 Hz frequency with commercially available sensors is reliable, sensitive, and accurate at detecting age-related increases in physiological tremor and motor slowing. It remains to be seen if such sensitive methods may be accurate in distinguishing physiological tremors from tremors that occur in neurological diseases, such as Parkinson's Disease.

Development and Evaluation of a Hybrid Measurement System to Determine the Kinematics of the Wrist.

Optical Motion Capture Systems (OMCSs) are considered the gold standard for kinematic measurement of human movements. However, in situations such as measuring wrist kinematics during a hairdressing activity, markers can be obscured, resulting in a loss of data. Other measurement methods based on non-optical data can be considered, such as magneto-inertial measurement units (MIMUs). Their accuracy is generally lower than that of an OMCS. In this context, it may be worth considering a hybrid system [MIMU + OMCS] to take advantage of OMCS accuracy while limiting occultation problems. The aim of this work was (1) to propose a methodology for coupling a low-cost MIMU (BNO055) to an OMCS in order to evaluate wrist kinematics, and then (2) to evaluate the accuracy of this hybrid system [MIMU + OMCS] during a simple hairdressing gesture. During hair cutting gestures, the root mean square error compared with the OMCS was 4.53° (1.45°) for flexion/extension, 5.07° (1.30°) for adduction/abduction, and 3.65° (1.19°) for pronation/supination. During combing gestures, they were significantly higher, but remained below 10°. In conclusion, this system allows for maintaining wrist kinematics in case of the loss of hand markers while preserving an acceptable level of precision (<10°) for ergonomic measurement or entertainment purposes.

A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.

BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals from the same joint remains challenging due to their similar brain spatial distribution. NEW METHOD: We designed experiments involving three motor imagery tasks-wrist extension, wrist flexion, and wrist abduction-with six participants. Based on this, a single-joint multi-task motor imagery EEG signal recognition method using Empirical Wavelet Decomposition and Multi-Kernel Extreme Learning Machine is proposed. This method employs Empirical Wavelet Decomposition (EWT) for modal decomposition, screening, and reconstruction of raw EEG signals, feature extraction using Common Spatial Patterns (CSP), and classification using Multi-Kernel Extreme Learning Machine (MKELM). RESULTS: After EWT processing, differences in time and frequency characteristics between EEG signals of different classes were enhanced, with the MKELM model achieving an average recognition accuracy of 91.93 %. COMPARISON WITH OTHER METHODS AND CONCLUSIONS: We compared EWT with Empirical Mode Decomposition (EMD), Variational Mode Decomposition (VMD), Local Mean Decomposition (LMD), and Wavelet Packet Decomposition (WPD). The results showed that the differences between various types of EEG signals processed by EWT were the most pronounced. The MKELM model outperformed traditional machine learning models such as Extreme Learning Machine (ELM), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Linear Discriminant Analysis (LDA) in terms of recognition performance, and also exhibited faster training speeds than deep learning models such as Bayesian Convolutional Neural Network (BCNN) and Attention-based Dual-scale Fusion Convolutional Neural Network (ADFCNN). In summary, the proposed method provides a new approach for achieving finer Brain-Computer Interface commands.

A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature.

The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.

An OpenSim-Based Closed-Loop Biomechanical Wrist Model for Subject-Specific Pathological Tremor Simulation.

OBJECTIVE: A pathological tremor (PT) is an involuntary rhythmic movement of varying frequency and amplitude that affects voluntary motion, thus compromising individuals' independence. A comprehensive model incorporating PT's physiological and biomechanical aspects can enhance our understanding of the disorder and provide valuable insights for therapeutic approaches. This study aims to build a biomechanical model of pathological tremors using OpenSim's realistic musculoskeletal representation of the human wrist with two degrees of freedom. METHODS: We implemented a Matlab/OpenSim interface for a forward dynamics simulation, which allows for the modeling, simulation, and design of a physiological H∞ closed-loop control. This system replicates pathological tremors similar to those observed in patients when their arm is extended forward, the wrist is pronated, and the hand is subject to gravity forces. The model was individually tuned to five subjects (four Parkinson's disease patients and one diagnosed with essential tremor), each exhibiting distinct tremor characteristics measured by an inertial sensor and surface EMG electrodes. Simulation agreement with the experiments for EMGs, central frequency, joint angles, and angular velocities were evaluated by Jensen-Shannon divergence, histogram centroid error, and histogram intersection. RESULTS: The model emulated individual tremor statistical characteristics, including muscle activations, frequency, variability, and wrist kinematics, with greater accuracy for the four Parkinson's patients than the essential tremor. CONCLUSION: The proposed model replicated the main statistical features of subject-specific wrist tremor kinematics. SIGNIFICANCE: Our methodology may facilitate the design of patient-specific rehabilitation devices for tremor suppression, such as neural prostheses and electromechanical orthoses.

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.

Novel near E-Field Topography Sensor for Human-Machine Interfacing in Robotic Applications.

This work investigates a new sensing technology for use in robotic human-machine interface (HMI) applications. The proposed method uses near E-field sensing to measure small changes in the limb surface topography due to muscle actuation over time. The sensors introduced in this work provide a non-contact, low-computational-cost, and low-noise method for sensing muscle activity. By evaluating the key sensor characteristics, such as accuracy, hysteresis, and resolution, the performance of this sensor is validated. Then, to understand the potential performance in intention detection, the unmodified digital output of the sensor is analysed against movements of the hand and fingers. This is done to demonstrate the worst-case scenario and to show that the sensor provides highly targeted and relevant data on muscle activation before any further processing. Finally, a convolutional neural network is used to perform joint angle prediction over nine degrees of freedom, achieving high-level regression performance with an RMSE value of less than six degrees for thumb and wrist movements and 11 degrees for finger movements. This work demonstrates the promising performance of this novel approach to sensing for use in human-machine interfaces.

Exploration of outcome measures for assessing orthotic intervention in upper extremity peripheral nerve injuries: 2 case reports.

In upper extremity peripheral nerve injuries, orthotic intervention has been used as a valuable device to restore function. However, there is lacking evidence to support it. The purpose of this study was to explore the application of body function's outcome measures for orthotic intervention evaluation in patients with peripheral nerve injury. Two participants sustaining a peripheral nerve injury who underwent orthotic intervention were assessed: subject 1 was a 25-year-old man with ulnar and median nerve injury presenting with a composite claw; subject 2, a 28-year-old man with radial nerve injury presenting with a dropped wrist. Strength, range of motion, and electromyography were measured in 2 conditions: wearing the orthosis and without it. The Jamar, Pinch Gauge, a 3D motion capture system (Optitrack-NaturalPoint), and surface electromyography (Trigno Wireless System, Delsys) were the chosen instruments. Both subjects presented differences in grip and pinch strength. In both tasks, subject 1 reached higher wrist extension while wearing the orthosis. Subject 2 reached higher wrist extension and radial deviation while wearing the orthosis. There were marked differences in both tasks for subject 2, especially the maintenance of wrist extension when wearing the orthosis. Electromyographic assessment showed higher root-mean-square values for all muscles, in both tasks for subject 1. For subject 2, a higher root-mean-square value was found for flexor carpi ulnaris during the execution of task 1 wearing the orthosis. Outcome measures of body function can quantify the impact of orthotic intervention in patients sustaining peripheral nerve injury, and therefore, they are feasible for evaluating it.

ExoMechHand prototype development and testing with EMG signals for hand rehabilitation.

Rehabilitation is a major requirement to improve the quality of life and mobility of patients with disabilities. The use of rehabilitative devices without continuous supervision of medical experts is increasing manifold, mainly due to prolonged therapy costs and advancements in robotics. Due to ExoMechHand's inexpensive cost, high robustness, and efficacy for participants with median and ulnar neuropathies, we have recommended it as a rehabilitation tool in this study. ExoMechHand is coupled with three different resistive plates for hand impairment. For efficacy, ten unhealthy subjects with median or ulnar nerve neuropathies are considered. After twenty days of continuous exercise, three subjects showed improvement in their hand grip, range of motion of the wrist, or range of motion of metacarpophalangeal joints. The condition of the hand is assessed by features of surface-electromyography signals. A Machine-learning model based on these features of fifteen subjects is used for staging the condition of the hand. Machine-learning algorithms are trained to indicate the type of resistive plate to be used by the subject without the need for examination by the therapist. The extra-trees classifier came out to be the most effective algorithm with 98% accuracy on test data for indicating the type of resistive plate, followed by random-forest and gradient-boosting with accuracies of 95% and 93%, respectively. Results showed that the staging of hand condition could be analyzed by sEMG signal obtained from the flexor-carpi-ulnaris and flexor-carpi-radialis muscles in subjects with median and ulnar neuropathies.

Motor cortex retains and reorients neural dynamics during motor imagery.

The most prominent characteristic of motor cortex is its activation during movement execution, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioural and imaging studies, it is unknown how the specific activity patterns and temporal dynamics in motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people who retain some residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population activity into three orthogonal subspaces, where one was similarly active during both action and imagery, and the others were active only during a single task type-action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamic features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by reorienting the components related to motor output and/or feedback into a unique, output-null imagery subspace.

Time-varying changes in median nerve deformation and position in response to quantified pinch and grip forces.

The ability of the median nerve (MN) to adapt in response to altered carpal tunnel conditions is important to mitigate compressive stress on the nerve. We assessed changes in MN deformation and position throughout the entire time course of hand force exertions. Fourteen right-handed participants ramped up force from 0% to 50% of maximal voluntary force (MVF) before ramping force back down in three different hand force exertion tasks (pulp pinch, chuck pinch, power grip). Pinch and grip forces were measured with a digital dynamometer, which were time synchronized with transverse carpal tunnel images obtained via ultrasound. Ultrasound images were extracted in 10% increments between 0% and 50% MVF while ramping force up (loading phase) and down (unloading phase). MN deformation and position relative to the flexor digitorum superficialis tendon of the long finger were assessed in concert. During loading, the nerve became more circular while displacing dorsally and ulnarly. These changes primarily occurred at the beginning of the hand force exertions while ramping force up from 0% to 20%, with very little change between 20% and 50% MVF. Interestingly, deformation and position changes during loading were not completely reversed during unloading while ramping force down. These findings indicate an initial reorganization of carpal tunnel structures. Mirrored changes in nerve deformation and position may also reflect strain-related characteristics of adjoining subsynovial connective tissue. Regardless, time-varying changes in nerve deformation and position appear to be an important accommodative mechanism in the healthy carpal tunnel in response to gripping and pinching tasks.

Pathophysiology of sex difference in refractoriness in lateral epicondylitis: Biomechanical study of wrist torque.

Eccentric contractions of the wrist extensors worsen lateral epicondylitis (LE), whose pathophysiology may involve sex differences in wrist torque. This study aimed to investigate sex differences in wrist torque in patients with LE. The wrist extension and flexion torques of 22 patients with LE (11 males and 11 females) were measured. Maximum muscle output over time was measured for 20 s, initial torque was defined as muscle strength, and the degree of eccentric contraction was quantified and defined as the eccentric contraction index (ECI). The affected/unaffected side ratio of the wrist extensor, extensor/flexor ratio of muscle strength, and affected/unaffected side difference of ECI between sexes were statistically analyzed. Furthermore, correlations between wrist extensor torque, ECI, and Visual Analog Scale of pain during the examination were evaluated. Females were found to display lower affected/unaffected side ratios of the wrist extensor and wrist extension/flexion ratios for the affected side, compared with males; however, no differences were found in the wrist extension/flexion ratios for the unaffected side in both sexes. Additionally, females presented with larger differences between the affected and unaffected sides in the ECI. Based on correlations between wrist torques, ECI, and pain, females tended to suppress muscle output to prevent pain from eccentric contraction of wrist extensors more than males, which would induce an imbalance in muscle strength of the wrist extensors and flexors. This imbalance may result in chronic eccentric contraction of the wrist extensors with gripping, exacerbating LE.

Muscle redistribution technique for expressing motion intention in patients with wrist-level amputation.

This study reports the preliminary results of a technique for redistributing muscles at the wrist in the stump of hand amputees by suturing the tendons to the dermis. The technique has the potential to improve control of hand prostheses by detecting movement intentions.

Effects of Type II Diabetes on Proprioception during a Reach to Pinch Task.

Older adults with type II diabetes (T2D) are at risk of developing nerve disorders that result in functional impairment. Most work in proprioceptive dysfunction in older adults with T2D has focused on functional deficits of the lower limb. The purpose of this study was to examine proprioceptive effects of T2D on the upper limb in older adults. Kinematic performance of a reach-to-pinch action toward a virtual target was assessed in a T2D group (60+ years old with T2D) and a healthy age- and sex-matched control group. Tactile and vibratory thresholds did not differ between T2D and controls. Task accuracy via mean pinch location was significantly worse for persons with T2D (pwT2D) with differences in wrist extension/flexion (ex/fl), wrist abduction/adduction (ab/ad), 1st carpometacarpal (CMC) ab/ad, 2nd metacarpophalangeal (MCP2) ex/fl, MCP2 ab/ad, and digit 1 and hand transport trajectories. Group differences persisted with consideration of body mass index; sex differences in task accuracy emerged. Findings indicate that proprioception of the upper extremity is altered in pwT2D such that they exhibit a unique aperture position and aiming strategy during a reach-to-pinch action. These findings characterize functional sensorimotor impairment of the upper limb in pwT2D with respect to workspaces without visual or tactile feedback.

Hand and distal joint tremor are most coherent with the activity of elbow flexors and wrist extensors in persons with essential tremor.

Essential tremor (ET) affects millions of people. Although frontline treatment options (medication, deep brain stimulation, and focused ultrasound ablation) have provided significant relief, many patients are unsatisfied with the outcomes. Peripheral suppression techniques, such as injections of botulinum toxin or sensory electrical stimulation of muscles, are gaining popularity, but could be optimized if the muscles most responsible for a patient's tremor were identified. The purpose of this study was to quantify the relationship between the activity in various upper limb muscles and the resulting tremor in patients with ET. Surface electromyogram (sEMG) from the 15 major superficial muscles of the upper limb and displacement of the hand and upper limb joints were recorded from 22 persons with ET while they performed kinetic and postural tasks representative of activities of daily living. We calculated the peak coherence (frequency-dependent correlation) in the tremor band (4-8 Hz) between the sEMG of each muscle and the displacement in each major degree of freedom (DOF). Averaged across subjects with ET, the highest coherence was found between elbow flexors (particularly biceps brachii and brachioradialis) and the distal DOF (forearm, wrist, and hand motion), and between wrist extensors (extensor carpi radialis and ulnaris) and the same distal DOF. These coherence values represent the upper bound on the proportion of the tremor caused by each muscle. We conclude that, without further information, elbow flexors and wrist extensors should be among the first muscles considered for peripheral suppression techniques in persons with ET.NEW & NOTEWORTHY We characterized the relationships between activity in upper limb muscles and tremor in persons with essential tremor using coherence, which provides an upper bound on the proportion of the tremor due to each muscle. Averaged across subjects and various tasks, tremor in the hand and distal joints was most coherent with elbow flexors and wrist extensors. We conclude that, without further information, these muscle groups should be among the first considered for peripheral suppression techniques.

Investigating the relationship between pain level and grip and wrist muscles strength in individuals with lateral epicondylitis: is pain a barrier to strength assessment?

PURPOSE: This study was carried out to examine the relationship between rest, activity, and nighttime pain and grip and isokinetic muscle strength of the wrist muscles in individuals with lateral epicondylitis. METHODS: Fifty-six sedentary individuals aged between 18 and 65 years diagnosed with unilateral lateral epicondylitis volunteered to participate in the study. The level of rest, activity, and nighttime pain was evaluated with visual analog scale (VAS). The grip strengths of both arms were evaluated by averaging a maximum of three grip strength measurements using a hand dynamometer. The strength of both wrist flexor and extensor muscles were evaluated with isokinetic dynamometer at angular velocities of 60 and 180°/s with five and 15 concentric repetitions respectively. RESULTS: There was no significant relationship found between the affected side's grip strength and isokinetic muscle strength with rest, activity and nighttime pain (all P > 0.05). However, there was a difference observed between the affected and unaffected side in grip strength and isokinetic strength measurements of all wrist muscles (all P < 0.05); the unaffected side values were found to be higher. CONCLUSION: The result of this study found no correlation between the stated level of pain and the true muscle strength in the affected hand. In line with these findings, we think that assessments involving strength can be made in other musculoskeletal problems where pain is present. However, the findings may not reflect the true muscle strength which will tend to be underrated.