Motor learning in multijoint virtual arm movements with novel kinematics.

Humans move their hands toward precise positions, a skill supported by the coordination of multiple joint movements, even in the presence of inherent redundancy. However, it remains unclear how the central nervous system learns the relationship between redundant joint movements and hand positions when starting from scratch. To address this question, a virtual-arm reaching task was performed in which participants were required to move a cursor corresponding to the hand of a virtual arm to a target. The joint angles of the virtual arm were determined by the heights of the participants' fingers. The results demonstrated that the participants moved the cursor to the target straighter and faster in the late phase than they did in the initial phase of learning. This improvement was accompanied by a reduction in the amount of angular changes in the virtual limb joint, predominantly characterized by an increased reliance on the virtual shoulder joint as opposed to the virtual wrist joint. These findings suggest that the central nervous system selects a combination of multijoint movements that minimize motor effort while learning novel upper-limb kinematics.

Mapping Method of Human Arm Motion Based on Surface Electromyography Signals.

This paper investigates a method for precise mapping of human arm movements using sEMG signals. A multi-channel approach captures the sEMG signals, which, combined with the accurately calculated joint angles from an Inertial Measurement Unit, allows for action recognition and mapping through deep learning algorithms. Firstly, signal acquisition and processing were carried out, which involved acquiring data from various movements (hand gestures, single-degree-of-freedom joint movements, and continuous joint actions) and sensor placement. Then, interference signals were filtered out through filters, and the signals were preprocessed using normalization and moving averages to obtain sEMG signals with obvious features. Additionally, this paper constructs a hybrid network model, combining Convolutional Neural Networks and Artificial Neural Networks, and employs a multi-feature fusion algorithm to enhance the accuracy of gesture recognition. Furthermore, a nonlinear fitting between sEMG signals and joint angles was established based on a backpropagation neural network, incorporating momentum term and adaptive learning rate adjustments. Finally, based on the gesture recognition and joint angle prediction model, prosthetic arm control experiments were conducted, achieving highly accurate arm movement prediction and execution. This paper not only validates the potential application of sEMG signals in the precise control of robotic arms but also lays a solid foundation for the development of more intuitive and responsive prostheses and assistive devices.

A lateralized motor network in order to understand adaptation to visuomotor rotation.

Objective.The functional asymmetry between the two brain hemispheres in language and spatial processing is well documented. However, a description of difference in control between the two hemispheres in motor function is not well established. Our primary objective in this study was to examine the distribution of control in the motor hierarchy and its variation across hemispheres.Approach.We developed a computation model termed the bilateral control network and implemented the same in a neural network framework to be used to replicate certain experimental results. The network consists of a simple arm model capable of making movements in 2D space and a motor hierarchy with separate elements coding target location, estimated position of arm, direction, and distance to be moved by the arm, and the motor command sent to the arm. The main assumption made here is the division of direction and distance coding between the two hemispheres with distance coded in the non-dominant and direction coded in the dominant hemisphere.Main results.With this assumption, the network was able to show main results observed in visuomotor adaptation studies. Importantly it showed decrease in error exhibited by the untrained arm while the other arm underwent training compared to the corresponding naïve arm's performance-transfer of motor learning from trained to the untrained arm. It also showed how this varied depending on the performance variable used-with distance as the measure, the non-dominant arm showed transfer and with direction, dominant arm showed transfer.Significance.Our results indicate the possibility of shared control between the two hemispheres. If indeed found true, this result could have major significance in motor rehabilitation as treatment strategies will need to be designed in order to account for this and can no longer be confined to the arm contralateral to the affected hemisphere.

Changes in Dynamic Mean Ankle Moment Arm in Unimpaired Walking Across Speeds, Ramps, and Stairs.

Understanding the natural biomechanics of walking at different speeds and activities is crucial to develop effective assistive devices for persons with lower-limb impairments. While continuous measures such as joint angle and moment are well-suited for biomimetic control of robotic systems, whole-stride summary metrics are useful for describing changes across behaviors and for designing and controlling passive and semi-active devices. Dynamic mean ankle moment arm (DMAMA) is a whole-stride measure representing the moment arm of the ground reaction impulse about the ankle joint-effectively, how "forefoot-dominated" or "hindfoot-dominated" a movement is. DMAMA was developed as a target and performance metric for semi-active devices that adjust once per stride. However, for implementation in this application, DMAMA must be characterized across various activities in unimpaired individuals. In our study, unimpaired participants walked at "slow," "normal," and "fast" self-selected speeds on level ground and at a normal self-selected speed while ascending and descending stairs and a 5-degree incline ramp. DMAMA measured from these activities displayed a borderline-significant negative sensitivity to walking speed, a significant positive sensitivity to ground incline, and a significant decrease when ascending stairs compared to descending. The data suggested a nonlinear relationship between DMAMA and walking speed; half of the participants had the highest average DMAMA at their "normal" speed. Our findings suggest that DMAMA varies substantially across activities, and thus, matching DMAMA could be a valuable metric to consider when designing biomimetic assistive lower-limb devices.

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.

Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies.

Objective.We analyze and interpret arm and forearm muscle activity in relation with the kinematics of hand pre-shaping during reaching and grasping from the perspective of human synergistic motor control.Approach.Ten subjects performed six tasks involving reaching, grasping and object manipulation. We recorded electromyographic (EMG) signals from arm and forearm muscles with a mix of bipolar electrodes and high-density grids of electrodes. Motion capture was concurrently recorded to estimate hand kinematics. Muscle synergies were extracted separately for arm and forearm muscles, and postural synergies were extracted from hand joint angles. We assessed whether activation coefficients of postural synergies positively correlate with and can be regressed from activation coefficients of muscle synergies. Each type of synergies was clustered across subjects.Main results.We found consistency of the identified synergies across subjects, and we functionally evaluated synergy clusters computed across subjects to identify synergies representative of all subjects. We found a positive correlation between pairs of activation coefficients of muscle and postural synergies with important functional implications. We demonstrated a significant positive contribution in the combination between arm and forearm muscle synergies in estimating hand postural synergies with respect to estimation based on muscle synergies of only one body segment, either arm or forearm (p< 0.01). We found that dimensionality reduction of multi-muscle EMG root mean square (RMS) signals did not significantly affect hand posture estimation, as demonstrated by comparable results with regression of hand angles from EMG RMS signals.Significance.We demonstrated that hand posture prediction improves by combining activity of arm and forearm muscles and we evaluate, for the first time, correlation and regression between activation coefficients of arm muscle and hand postural synergies. Our findings can be beneficial for myoelectric control of hand prosthesis and upper-limb exoskeletons, and for biomarker evaluation during neurorehabilitation.

The control of the arm's equilibrium position.

To generate a force, the brain activates muscles that act like springs to pull the arm toward a new equilibrium position. The equilibrium position (EP) is central to our understanding of the biological control of viscoelastic muscles. Although there is evidence of the EP during the control of limb posture, EPs have not been directly identified when the limb exerts a force against the environment. Here, we asked participants to apply a constant force in one of eight directions against a point-like constraint. This constraint was released abruptly to observe the final position to which the arm converged. Importantly, the same force magnitude was maintained while changing the arm's stiffness by modulating the strength of the hand's power grasp. The final position moved further away from the constraint as the arm became less stiff and was inversely proportional to the arm's stiffness, thereby confirming that the final position was the arm's EP. These results demonstrate how the EP changes with the arm's stiffness to produce a desired force in different directions.NEW & NOTEWORTHY According to numerous theories, the brain controls posture and movement by activating muscles that attract the limb toward a so-called equilibrium position, but the universality of this mechanism has not been shown for different motor behaviors. Here, we show that even when pushing or pulling against the environment, the brain achieves the desired force through an equilibrium position that lies beyond the physical constraint.

Role of arm reaching movement kinematics in friction perception at initial contact with smooth surfaces.

When manipulating objects, humans begin adjusting their grip force to friction within 100 ms of contact. During motor adaptation, subjects become aware of the slipperiness of touched surfaces. Previously, we have demonstrated that humans cannot perceive frictional differences when surfaces are brought in contact with an immobilised finger, but can do so when there is submillimeter lateral displacement or subjects actively make the contact movement. Similarly, in, we investigated how humans perceive friction in the absence of intentional exploratory sliding or rubbing movements, to mimic object manipulation interactions. We used a two-alternative forced-choice paradigm in which subjects had to reach and touch one surface followed by another, and then indicate which felt more slippery. Subjects correctly identified the more slippery surface in 87 ± 8% of cases (mean ± SD; n = 12). Biomechanical analysis of finger pad skin displacement patterns revealed the presence of tiny (<1 mm) localised slips, known to be sufficient to perceive frictional differences. We tested whether these skin movements arise as a result of natural hand reaching kinematics. The task was repeated with the introduction of a hand support, eliminating the hand reaching movement and minimising fingertip movement deviations from a straight path. As a result, our subjects' performance significantly declined (66 ± 12% correct, mean ± SD; n = 12), suggesting that unrestricted reaching movement kinematics and factors such as physiological tremor, play a crucial role in enhancing or enabling friction perception upon initial contact. KEY POINTS: More slippery objects require a stronger grip to prevent them from slipping out of hands. Grip force adjustments to friction driven by tactile sensory signals are largely automatic and do not necessitate cognitive involvement; nevertheless, some associated awareness of grip surface slipperiness under such sensory conditions is present and helps to select a safe and appropriate movement plan. When gripping an object, tactile receptors provide frictional information without intentional rubbing or sliding fingers over the surface. However, we have discovered that submillimeter range lateral displacement might be required to enhance or enable friction sensing. The present study provides evidence that such small lateral movements causing localised partial slips arise and are an inherent part of natural reaching movement kinematics.

Effects of isometric training and R.I.C.E. treatment on the arm muscle performance of swimmers with elbow pain.

The effects of IT and R.I.C.E. treatment on arm muscle performance in overhead athletes with elbow pain (EP) have been partially validated. However, there is a lack of research evidence regarding the efficacy of these two methods on arm muscle performance among swimmers with EP. The aim of this study was to investigate the trends and differences in the effects of IT and R.I.C.E. treatment on arm muscle performance among swimmers with EP. The main outcomes were the time effects and group effects of interventions on muscle voluntary contraction (MVC). Sixty elite freestyle swimmers from Tianjin, China, voluntarily participated in the study and completed a 10-week intervention program. Swimmers with EP in the IT group showed a positive trend in MVC, with an approximately 2% increase, whereas the MVC of subjects in the R.I.C.E. treatment group and control group decreased by approximately 4% and 5%, respectively. In comparison, the effects of the IT intervention on the MVC of the triceps and brachioradialis muscles in swimmers with EP were significant (p = 0.042 < 0.05, p = 0.027 < 0.05). The mean MVC value of the IT group (0.60) was greater than that of the other two groups (0.51, 0.50). IT has a beneficial impact on the MVC performance of the triceps and brachioradialis muscles in swimmers with EP. It is recommended that professionals consider incorporating IT into regular training routines to mitigate the risk of EP issues. Future research should examine the effectiveness of both interventions on hand-grip strength and completion time in 50-m freestyle swim drills in order for swimmers with EP to return to this sport.

Evaluation of antigravitational support levels provided by a passive upper-limb occupational exoskeleton in repetitive arm movements.

Upper-limb occupational exoskeletons to support the workers' upper arms are typically designed to provide antigravitational support. Although typical work activities require workers to perform static and dynamic actions, the majority of the studies in literature investigated the effects of upper-limb occupational exoskeletons in static and quasi-static activities, while only a few works focused on dynamic tasks. This article presents a systematic evaluation of the effects of different levels of antigravitational support (from about 60% to 100% of the arm gravitational load) provided by a passive upper-limb occupational exoskeleton on muscles' activity during repetitive arm movements. The effect of the exoskeleton on muscle activity was evaluated by the comparison of muscle activations with and without the exoskeleton. The average muscle activation was computed considering shoulder full flexion-extension cycles, and sub-movements, namely the arm-lifting (i.e., flexion) and arm-lowering (i.e., extension) movements. Results showed a quasi-linear correlation between antigravitational support and muscle activity reductions, both when considering the full flexion-extension cycle and in the arm-lifting movement (reductions were up to 64 and 61% compared to not wearing the exoskeleton, respectively). When considering the arm-lowering movement, providing antigravitational support close to or higher than 100% of the arm gravitational load led to increased muscle activations of the extensors (up to 127%), suggesting that such an amount of antigravitational support may be not effective for a complete biomechanical load reduction on the shoulder district in dynamic tasks.

A simulation-based study for optimizing proportional-integral-derivative controller gains for different control strategies of an active upper extremity model using experimental data.

This study investigates the effect of PID controller gains, reaction time, and initial muscle activation values on active human model behavior while comparing three different control strategies. The controller gains and reaction delays were optimized using published experimental data focused on the upper extremity. The data describes the reaction of five male subjects in four tests based on two muscle states (relaxed and tensed) and two states of awareness (open and closed eye). The study used a finite element model of the left arm isolated from the Global Human Body Models Consortium (GHBMC) average male simplified occupant model for simulating biomechanical simulations. Major skeletal muscles of the arm were modeled as 1D beam elements and assigned a Hill-type muscle material. Angular position control, muscle length control, and a combination of both were used as a control strategy. The optimization process was limited to 4 variables; three Proportional-Integral-Derivative (PID) controller gains and one reaction delay time. The study assumed the relaxed and tensed condition require distinct sets of controller gains and initial activation and that the closed-eye simulations can be achieved by increasing the reaction delay parameter. A post-hoc linear combination of angle and muscle length control was used to arrive at the final combined control strategy. The premise was supported by variation in the controller gains depending on muscle state and an increase in reaction delay based on awareness. The CORA scores for open-eye relaxed, closed-eye relaxed, open-eye tensed, and closed-eye tensed was 0.95, 0.90, 0.95, and 0.77, respectively using the combined control strategy.

Scalable musculoskeletal model for dynamic simulations of upper body movement.

A musculoskeletal (MSK) model is a valuable tool for assessing complex biomechanical problems, estimating joint torques during motion, optimizing motion in sports, and designing exoskeletons and prostheses. This study proposes an open-source upper body MSK model that supports biomechanical analysis of human motion. The MSK model of the upper body consists of 8 body segments (torso, head, left/right upper arm, left/right forearm, and left/right hand). The model has 20 degrees of freedom (DoFs) and 40 muscle torque generators (MTGs), which are constructed using experimental data. The model is adjustable for different anthropometric measurements and subject body characteristics: sex, age, body mass, height, dominant side, and physical activity. Joint limits are modeled using experimental dynamometer data within the proposed multi-DoF MTG model. The model equations are verified by simulating the joint range of motion (ROM) and torque; all simulation results have a good agreement with previously published research.

Weekly minimum frequency of one maximal eccentric contraction to increase muscle strength of the elbow flexors.

PURPOSE: Our previous study showed that one 3-s maximal eccentric contraction a day performed 5 days a week for 4 weeks (5DW) increased maximal voluntary contraction (MVC) strength of the elbow flexors more than 10%. The present study examined whether muscle strength would still increase when the frequency was reduced to 2 days or 3 days per week. METHODS: Twenty-six healthy young adults were recruited in the present study and placed to two groups (n = 13/group) based on the weekly frequency of the one 3-s maximal eccentric contraction for two (2DW) or three days per week (3DW) for 4 weeks. Changes in MVC-isometric, MVC-concentric, MVC-eccentric torque of the elbow flexors, and muscle thickness of biceps brachii and brachialis (MT) before and after the 4-week training were compared between 2DW and 3DW groups, and also compared to the 5DW group in the previous study. RESULTS: The 2DW group showed no significant changes in MVC torque. Significant (P < 0.05) increases in MVC-concentric (2.5 ± 10.4%) and MVC-eccentric (3.9 ± 4.9%) torque were observed for the 3DW group, but the magnitude of the increase was smaller (P < 0.05) than that presented by the 5DW group (12.8 ± 9.6%, 12.2 ± 7.8%). No significant changes in MT were evident for any of the groups. CONCLUSION: These results suggest that at least three days a week are necessary for the one 3-s maximal eccentric contraction to be effective for increasing muscle strength, and more frequent sessions in a week (e.g., 5 days) appear to induce greater increases in muscle strength.

The effects of separate and simultaneous upper and lower body cycling on cardiorespiratory responses in young men.

BACKGROUND: The aim of the present study was to examine the relative cardiorespiratory and perceptual responses to upper body ergometry, lower body ergometry, and combined upper and lower body ergometry at increasing exercising intensities. METHODS: Eight healthy males between 19 and 30 years of age completed three exercise sessions over seven days that included graded leg ergometry, arm ergometry, and combined arm and leg ergometry in counterbalanced fashion. During leg-only and arm-only sessions, participants exercised at workloads of 0, 32, 64, and 95 W. The combined session involved simultaneous arm and leg ergometry at 0, 32, 64, and 95 W, thus eliciting double the total power output of arm-only and leg-only sessions. RESULTS: At all workloads, oxygen consumption and minute ventilation responses were greater during combined arm and leg exercise than during leg-only or arm-only exercise. However, the pattern of changes in heart rate, systolic blood pressure, rate pressure product, and rating of perceived exertion (RPE) were similar in response to arm-only and combined upper and lower body exercise, despite combined exercise involving double the workload. These cardiorespiratory and perceptual responses were significantly lower during leg-only only exercise. CONCLUSIONS: The results of the study add to limited research comparing physiological and perceptual responses to upper, lower, and combined upper and lower body exercise. The findings highlight heightened cardiorespiratory and perceptual responses to upper body exercise alone or in combination with lower body exercise. Training that combines upper and lower body may create higher power output and elicit greater caloric expenditure while eliciting similar cardiovascular responses as upper body only exercise at moderate and higher intensities.

Limb-specific isometric and isokinetic strength in adults: The potential role of regional bioelectrical impedance analysis-derived phase angle.

BACKGROUND & AIMS: It is not yet known whether regional bioelectrical impedance (BIA) phase angle (PhA) may be informative of different types of strength performed by the lower and upper limbs, independently of lean soft tissue mass (LSTM). Using a sample of healthy adults, we aimed to examine the association and relevance of regional PhA relative to isometric and isokinetic strength of each limb. METHODS: A total of 57 participants (32.7 ± 12.9 years; 24.7 ± 3.5 kg/m2) were included in the present investigation. Regional raw BIA variables were determined using a phase-sensitive BIA device. Dual-energy X-ray absorptiometry was used to evaluate LSTM. Absolute isometric and isokinetic (i.e., 60°/s and 180°/s) strength of each limb (extension and flexion) was assessed using an isokinetic dynamometer and used to calculate relative strength. RESULTS: In absolute strength, only dominant leg PhA was associated with isometric extension strength (ß = 0.283) and isokinetic 180°/s flexion strength (ß = 0.354), regardless of LSTM (p < 0.05). In relative strength, a significant association of regional PhA was found for dominant arm flexion isometric strength (ß = 0.336), and non-dominant arm and dominant leg extension isometric strength (ß = 0.377, ß = 0.565, respectively; p < 0.05), independently of LSTM. Similarly, for isokinetic 180°/s strength, regional PhA significantly explained the variance in the relative strength of both arms and dominant leg (ß = 0.350 to 0.506), regardless of LSTM (p < 0.05). Relative isokinetic 60°/s strength was not consistently associated with regional PhA (p ≥ 0.05). CONCLUSIONS: Regional PhA significantly explained relative (isometric and 180°/s isokinetic strength of both arms and dominant leg), but not absolute muscle strength, independently of regional LSTM. Thus, after accounting for body size, regional PhA seems to have its own characteristics that explain relative strength independently of LSTM.

Physiological and perceptual responses to acute arm cranking with blood flow restriction.

INTRODUCTION: Lower-body aerobic exercise with blood flow restriction (BFR) offers a unique approach for stimulating improvements in muscular function and aerobic capacity. While there are more than 40 reports documenting acute and chronic responses to lower-body aerobic exercise with BFR, responses to upper-body aerobic exercise with BFR are not clearly established. PURPOSE: We evaluated acute physiological and perceptual responses to arm cranking with and without BFR. METHODS: Participants (N = 10) completed 4 arm cranking (6 × 2 min exercise, 1 min recovery) conditions: low-intensity at 40%VO2peak (LI), low-intensity at 40%VO2peak with BFR at 50% of arterial occlusion pressure (BFR50), low-intensity at 40%VO2peak with BFR at 70% of arterial occlusion pressure (BFR70), and high-intensity at 80%VO2peak (HI) while tissue oxygenation, cardiorespiratory, and perceptual responses were assessed. RESULTS: During exercise, tissue saturation for BFR50 (54 ± 6%), BFR70 (55 ± 6%), and HI (54 ± 8%) decreased compared to LI (61 ± 5%, all P < 0.01) and changes in deoxyhemoglobin for BFR50 (11 ± 4), BFR70 (15 ± 6), and HI (16 ± 10) increased compared to LI (4 ± 2, all P < 0.01). During recovery intervals, tissue saturation for BFR50 and BFR70 decreased further and deoxyhemoglobin for BFR50 and BFR70 increased further (all P < 0.04). Heart rate for BFR70 and HI increased by 9 ± 9 and 50 ± 15b/min, respectively, compared to LI (both P < 0.02). BFR50 (8 ± 2, 1.0 ± 1.0) and BFR70 (10 ± 2, 2.1 ± 1.4) elicited greater arm-specific perceived exertion (6-20 scale) and pain (0-10 scale) compared to LI (7 ± 1, 0.2 ± 0.5, all P < 0.05) and pain for BFR70 did not differ from HI (1.7 ± 1.9). CONCLUSION: Arm cranking with BFR decreased tissue saturation and increased deoxyhemoglobin without causing excessive cardiorespiratory strain and pain.

Artificial physics engine for real-time inverse dynamics of arm and hand movement.

Simulating human body dynamics requires detailed and accurate mathematical models. When solved inversely, these models provide a comprehensive description of force generation that considers subject morphology and can be applied to control real-time assistive technology, for example, orthosis or muscle/nerve stimulation. Yet, model complexity hinders the speed of its computations and may require approximations as a mitigation strategy. Here, we use machine learning algorithms to provide a method for accurate physics simulations and subject-specific parameterization. Several types of artificial neural networks (ANNs) with varied architecture were tasked to generate the inverse dynamic transformation of realistic arm and hand movement (23 degrees of freedom). Using a physical model, we generated representative limb movements with bell-shaped end-point velocity trajectories within the physiological workspace. This dataset was used to develop ANN transformations with low torque errors (less than 0.1 Nm). Multiple ANN implementations using kinematic sequences solved accurately and robustly the high-dimensional kinematic Jacobian and inverse dynamics of arm and hand. These results provide further support for the use of ANN architectures that use temporal trajectories of time-delayed values to make accurate predictions of limb dynamics.

Identifying a Upper-Limb Phase-Dependent Variable under Perturbations for Powered Prosthesis Arm Control.

This paper investigates upper-limb kinematic reaching responses during a mechanical perturbation to understand interjoint arm coordination used towards powered prosthesis control development. Common prosthesis arm controllers use electromyography sensors with data-driven models to decode muscle activation signals in controlling prosthesis joint movements. However, these control approaches produce non-natural, discrete movements with no guarantee the controller can react to unexpected disturbances during continuous task motion. Determining a continuous phase-dependent variable for measuring a human's progression during reaching can derive a time-invariant kinematic function to control the prosthesis joint in a natural, continuous manner. A perturbation experimental study was conducted across three participants in evaluating the shoulder and elbow joint kinematics to examine the existence of a phase shift during reaching. Experimental results demonstrated the effects of arm proximal-distal interjoint coordination that validated the proposed mechanical phase variable of the shoulder used in parameterizing elbow joint kinematic for reaching. This could allow for a continuous phase-based control strategy that can handle disturbances to achieve arm reaching in prosthesis control.

A new force profile signal for a convex solution of muscle force estimation from electromyographic signals.

High-Density Surface Electromyography (HD-sEMG) is a non-invasive technique for measuring the electrical activity of a muscle with multiple, closely spaced electrodes. Estimation of muscle force is one of the applications of HD-sEMG. Usually, validating different EMG-Force models entails simple movements limited to laboratory settings. The validity of these models in more ecological conditions, requesting force production over a wide frequency band, remains unknown. In this study, we, therefore, compare the results of force prediction using four different types of input force profiles that can be representative of daily life activities, and we investigate whether the crest factor of these different input signals affects force prediction. For predicting the force from sEMG signals, we used our real-time and convex methods. HD-sEMG signals were recorded with 144 channels from the biceps brachii, brachioradialis, and triceps (long, lateral, and medial head) muscles of 24 healthy subjects during random signal, random phase, Schroeder phase, and minimum crest factor (crestmin) signal. The correlation and coefficient of determination (R2) between measured and predicted forces were calculated for the different force feedback profiles. The crestmin signal showed significantly better results based on statistical tests (P-value < 0.05), with correlation and R2 equal to 0.92±0.03 and 0.86±0.05, respectively. The results demonstrate that the crest factor of input signals is a crucial parameter that can impact the performance of EMG-Force models and must be considered during training.Clinical Relevance- This study demonstrates that lower crest factor multisine force profiles result in improved fitness for force prediction and can be used as an alternative to random signals.

Spatial mapping of posture-dependent resistance to passive displacement of the hypertonic arm post-stroke.

BACKGROUND: Muscles in the post-stroke arm commonly demonstrate abnormal reflexes that result in increased position- and velocity-dependent resistance to movement. We sought to develop a reliable way to quantify mechanical consequences of abnormal neuromuscular mechanisms throughout the reachable workspace in the hemiparetic arm post-stroke. METHODS: Survivors of hemiparetic stroke (HS) and neurologically intact (NI) control subjects were instructed to relax as a robotic device repositioned the hand of their hemiparetic arm between several testing locations that sampled the arm's passive range of motion. During transitions, the robot induced motions at either the shoulder or elbow joint at three speeds: very slow (6°/s), medium (30°/s), and fast (90°/s). The robot held the hand at the testing location for at least 20 s after each transition. We recorded and analyzed hand force and electromyographic activations from selected muscles spanning the shoulder and elbow joints during and after transitions. RESULTS: Hand forces and electromyographic activations were invariantly small at all speeds and all sample times in NI control subjects but varied systematically by transport speed during and shortly after movement in the HS subjects. Velocity-dependent resistance to stretch diminished within 2 s after movement ceased in the hemiparetic arms. Hand forces and EMGs changed very little from 2 s after the movement ended onward, exhibiting dependence on limb posture but no systematic dependence on movement speed or direction. Although each HS subject displayed a unique field of hand forces and EMG responses across the workspace after movement ceased, the magnitude of steady-state hand forces was generally greater near the outer boundaries of the workspace than in the center of the workspace for the HS group but not the NI group. CONCLUSIONS: In the HS group, electromyographic activations exhibited abnormalities consistent with stroke-related decreases in the stretch reflex thresholds. These observations were consistent across repeated testing days. We expect that the approach described here will enable future studies to elucidate stroke's impact on the interaction between the neural mechanisms mediating control of upper extremity posture and movement during goal-directed actions such as reaching and pointing with the arm and hand.