Control Of Hand Movements Research Articles

The Effect of Dry Immersion on the Characteristics of Joystick Control during the Performance of a Visual-Motor Task in Men and Women

A study of the effect of Dry Immersion (DI) on the characteristics of joystick control during a visual-motor task in men and women was conducted. It is shown that in the first days of DI there is a deterioration in the performance of the visual-motor task – an increase in time indicators and a decrease in movement accuracy. By the end of DI, most of the parameters returned to the control level indicating the adaptation of the hand movement control mechanisms to immersion conditions. However, despite the similarity of the effect of DI on changes in the parameters of movement trajectories in men and women, it was shown that both in control and in DI, women performed the presented visual-motor task faster and more accurately due to a longer latency time. In the early days of DI, the characteristics of task performance in women changed less than in men, which indicated a better adaptation of women to the conditions of DI. In the process of adaptation to DI factors, men and women had different strategies for performing visual-motor tasks.

Quantifying Hand Motion Complexity in Simulated Sailing Using Inertial Sensors.

The control of hand movement during sailing is important for performance. To quantify the amount of regularity and the unpredictability of hand fluctuations during the task, the mathematical algorithm Approximate Entropy (ApEn) of the hand acceleration can be used. Approximate Entropy is a mathematical algorithm that depends on the combination of two input parameters including (1) the length of the sequences to be compared (m), and (2) the tolerance threshold for accepting similar patterns between two segments (r). The aim of this study is to identify the proper combinations of 'm' and 'r' parameter values for ApEn measurement in the hand movement acceleration data during sailing. Inertial Measurement Units (IMUs) recorded acceleration data for both the mainsail (non-dominant) and tiller (dominant) hands across the X-, Y-, and Z-axes, as well as vector magnitude. ApEn values were computed for 24 parameter combinations, with 'm' ranging from 2 to 5 and 'r' from 0.10 to 0.50. The analysis revealed significant differences in acceleration ApEn regularity between the two hands, particularly along the Z-axis, where the mainsail hand exhibited higher entropy values (p = 0.000673), indicating greater acceleration complexity and unpredictability. In contrast, the tiller hand displayed more stable and predictable acceleration patterns, with lower ApEn values. ANOVA results confirmed that parameter 'm' had a significant effect on acceleration complexity for both hands, highlighting differing motor control demands between the mainsail and tiller hands. These findings demonstrate the utility of IMU sensors and ApEn in detecting nuanced variations in acceleration dynamics during sailing tasks. This research contributes to the understanding of hand-specific acceleration patterns in sailing and provides a foundation for further studies on adaptive sailing techniques and motor control strategies for both novice and expert sailors.

Reliability of the Hand-Eye Coordination Test among Adults Using a Software: A Longitudinal Follow-up Study

This study aims to determine the reliability of the hand-eye coordination Software. The integrated control of hand and eye movements, as well as the processing of visual information to support attainment and acquisition and the use of hand proprioception to guide the eyes, are known as hand-eye coordination. Thus, this study aims to determine the reliability of the tests, so the research was conducted thrice with an interval of 6-7 days (test-retest). 28 Young Adults (18- 35 years of age) have participated in the study. The analysis includes finger-pointing tasks performed only with the use of Hand-eye coordination software prepared by the Software engineer.In this Software, Visual targets in the form of a ball then appeared on the screen on the left, on the right, or in the center in random order., and participants were asked to point an index finger of the leading hand as rapidly and precisely as possible at all targets on the screen. After touching the target (indicated by its disappearance), the participant immediately placed his/her hand back in the designated starting position (touchpad).Each participant was required to repeat this finger-pointing task. The accuracy value after 1 minute was recorded and the average accuracy value was calculated and used in the analysis A smaller value indicates greater touch accuracy. In addition, the average reaction time (in milliseconds) was also measured. Based on the data analysis, the reliability score is 0.806 (Cronbach’s Alpha), which indicates a high level of internal Consistency.

Proprioceptive acuity for landmarks on the hand and digits.

Previous work using visually guided reaches to localize landmarks on a hidden hand has suggested that proprioceptive acuity for hand targets is low and representation of hand dimensions is highly distorted (e.g., hand width estimated to be 60% wider than actual hand width). We re-examined these issues using a pure proprioceptive task in which 20 blindfolded subjects reached in a single movement without terminal corrections to touch the right index-tip to landmarks of the left hand placed in various locations in 3D space. Subjects were also tested with vision allowed to estimate minimal errors. Based on previous reports of high proprioceptive acuity for some hand landmarks, we hypothesized that the proprioceptive representation of the hand was much less distorted than described previously and that errors were not correlated with target hand location. Mean distance errors in proprioceptively guided reaches to the landmarks averaged less than 3cm and were only 0.5-1.3cm larger than when vision was allowed. Errors were not correlated with hand location in most subjects. Distortions of hand width averaged less than 20% wider than actual width and were not correlated with hand location in most subjects. We conclude that relatively accurate proprioceptive awareness of locations of hand/digit structures and dimensions is available for use in control of hand movements, which are executed largely subconsciously. Studying acuity of proprioception using conscious perceptual tasks and involving vision may not provide accurate measures of proprioceptive acuity as used by the motor system.

Self-Supervised Learning for Intuitive Control of Prosthetic Hand Movements via Sonomyography

Self-Supervised Learning for Intuitive Control of Prosthetic Hand Movements via Sonomyography

Edukasi Pengenalan Warna Melalui Kegiatan Mewarnai untuk Meningkatkan Motorik Halus pada Anak Usia Dini

Early childhood education is crucial in laying the foundation for children's cognitive, emotional, and physical development. A vital aspect of this education is the introduction of colors and the developing of fine motor skills, which can be enhanced through coloring activities. This community service activity aimed to provide color recognition education through coloring activities to improve fine motor skills in early childhood. The targets in this activity are early childhood children (2-5 years old) and BKB cadres at Taman Posyandu (Tapos) Ceria Desa Rejosari, Glagah District, Banyuwangi. The methods used are lecturing, drilling, and mentoring. The results of this activity are that children can recognize, distinguish, and name various colors, children's fine motor skills, such as eye-hand coordination and hand movement control, are improved through coloring activities, and they can express themselves and their ideas through the strokes of color they pour on the given picture. Recognizing colors and developing fine motor skills are crucial foundations for supporting young children in preparing important skills for the following learning stages, such as reading and writing. Coloring activities can become a positive habit, encouraging children to spend time with productive and educational activities.

Simultaneous and Proportional Control of Wrist and Hand Movements Based on a Neural-Driven Musculoskeletal Model.

Human-machine interfaces (HMIs) based on electromyography (EMG) signals have been developed for simultaneous and proportional control (SPC) of multiple degrees of freedom (DoFs). The EMG-driven musculoskeletal model (MM) has been used in HMIs to predict human movements in prosthetic and robotic control. However, the neural information extracted from surface EMG signals may be distorted due to their limitations. With the development of high density (HD) EMG decomposition, accurate neural drive signals can be extracted from surface EMG signals. In this study, a neural-driven MM was proposed to predict metacarpophalangeal (MCP) joint flexion/extension and wrist joint flexion/extension. Ten non-disabled subjects (male) were recruited and tested. Four 64-channel electrode grids were attached to four forearm muscles of each subject to record the HD EMG signals. The joint angles were recorded synchronously. The acquired HD EMG signals were decomposed to extract the motor unit (MU) discharge for estimating the neural drive, which was then used as the input to the MM to calculate the muscle activation and predict the joint movements. The Pearson's correlation coefficient (r) and the normalized root mean square error (NRMSE) between the predicted joint angles and the measured joint angles were calculated to quantify the estimation performance. Compared to the EMG-driven MM, the neural-driven MM attained higher r values and lower NRMSE values. Although the results were limited to an offline application and to a limited number of DoFs, they indicated that the neural-driven MM outperforms the EMG-driven MM in prediction accuracy and robustness. The proposed neural-driven MM for HMI can obtain more accurate neural commands and may have great potential for medical rehabilitation and robot control.

Influence of Dry Immersion on the Characteristics of Cyclic Precise Hand Movements

The characteristics of precise hand movements in Dry Immersion (DI) have been studied. Motor tasks were cyclic single-joint hand movements corresponding to the length and orientation of the presented horizontal or vertical segment and carried out for 5 s with or without visual feedback. The studies were carried out with the participation of 35 test healthy volunteers divided into three groups: control (n = 10), 6-hour DI (n = 11), and 5-day DI (n = 14). In the control group, the test was carried out three times, lying on the couch, imitating the cyclogram of a 6-hour DI—once before DI, in the morning on the day of DI, and in the evening 2 h after the end of exposure. In the 5-day DI, tests were performed once before the start of the DI, on the 1st, 3rd, and 5th days of the DI, and also once after its completion. It is shown that the accuracy of movements in the control group does not depend on the measurement number, while in the experimental groups on the first day of DI there is an increase in the overestimation of the length of horizontal segments and an increase in the error in estimating the direction of vertical segments. The data indicate that DI affects the hand movement control system and can be considered as a suitable Earth model for studying fine movement disorders observed in microgravity.

Decomposition into dynamic features reveals a conserved temporal structure in hand kinematics

The human hand is a unique and highly complex effector. The ability to describe hand kinematics with a small number of features suggests that complex hand movements are composed of combinations of simpler movements. This would greatly simplify the neural control of hand movements. If such movement primitives exist, a dimensionality reduction approach designed to exploit these features should outperform existing methods. We developed a deep neural network to capture the temporal dynamics of movements and demonstrate that the features learned allow accurate representation of functional hand movements using lower-dimensional representations than previously reported. We show that these temporal features are highly conserved across individuals and can interpolate previously unseen movements, indicating that they capture the intrinsic structure of hand movements. These results indicate that functional hand movements are defined by a low-dimensional basis set of movement primitives with important temporal dynamics and that these features are common across individuals.

Grip force as a functional window to somatosensory cognition.

Analysis of grip force signals tailored to hand and finger movement evolution and changes in grip force control during task execution provide unprecedented functional insight into somatosensory cognition. Somatosensory cognition is the basis of our ability to act upon and to transform the physical world around us, to recognize objects on the basis of touch alone, and to grasp them with the right amount of force for lifting and manipulating them. Recent technology has permitted the wireless monitoring of grip force signals recorded from biosensors in the palm of the human hand to track and trace human grip forces deployed in cognitive tasks executed under conditions of variable sensory (visual, auditory) input. Non-invasive multi-finger grip force sensor technology can be exploited to explore functional interactions between somatosensory brain mechanisms and motor control, in particular during learning a cognitive task where the planning and strategic execution of hand movements is essential. Sensorial and cognitive processes underlying manual skills and/or hand-specific (dominant versus non-dominant hand) behaviors can be studied in a variety of contexts by probing selected measurement loci in the fingers and palm of the human hand. Thousands of sensor data recorded from multiple spatial locations can be approached statistically to breathe functional sense into the forces measured under specific task constraints. Grip force patterns in individual performance profiling may reveal the evolution of grip force control as a direct result of cognitive changes during task learning. Grip forces can be functionally mapped to from-global-to-local coding principles in brain networks governing somatosensory processes for motor control in cognitive tasks leading to a specific task expertise or skill. Under the light of a comprehensive overview of recent discoveries into the functional significance of human grip force variations, perspectives for future studies in cognition, in particular the cognitive control of strategic and task relevant hand movements in complex real-world precision task, are pointed out.

Neural control of hand movement.

Neural control of hand movement.

Two Types of Withdraw-to-Eat Movement Related to Food Size in Long-Tailed Macaques (Macaca fascicularis): Insights into the Evolution of the Visual Control of Hand Shaping in Anthropoid Primates

The details of the evolutionary steps in the transition from nonvisual guidance of hand movements for feeding, as displayed by many non-primate species, to visual guidance of hand movements in primates are sparse. Contemporary theory holds that a small-bodied stem primate evolved visual control of the reach to guide a hand to obtain small insects and fruit items from the terminal branches of trees. The subsequent evolution of the visual control of hand and finger shaping movements of the grasp of anthropoids is uncertain. The present study finds that Balinese long-tailed macaques (Macaca fascicularis), video recorded while spontaneously eating at the Sacred Monkey Forest Sanctuary in Ubud in Indonesia, displayed two types of hand movements associated with two types of withdraw movements to place food items in the mouth. Small food items were brought directly to the mouth with hand supination, often with no visual monitoring after grasping. Large food items that protruded from the hand were visually monitored to orient the food item on the initial part of the withdraw but visually disengaged with a head movement and often a blink before the item was placed in the mouth. The results are discussed in relation to the idea that visual information related to orientating food items of varying sizes to an appropriate position in the mouth contributed to the evolution of the visual control of hand shaping skills in anthropoid primates.

Design, Development, and Validation of Hand-Eye Coordination Equipment

The paper provides information about the design, development, and evaluation of hand-eye coordination devices used to test and evaluate hand-eye coordination. Hand-eye coordination is the synchronized control of hand movement with eye movementand the processing of visual input to assist attainment, acquisition, and the use of hand proprioception to guide the eyes. Hand-eye coordination and visual-spatial abilities are essential for a child’s development because they are required not only for practical independence but also for scholastic achievement. This paper outlines the development of a hand-eye coordination device using a specially designed pen (sensor), plates with patterns to trace, and a wooden cabinet to enclose and support the auxiliary components. This is a strong diagnostic in-house development in response to meet the requirements of practitioners looking for an accurate technique of measuring the progress of the hand-eye coordination of the patients. The purpose of the study is to assess the validity and dependability/reliability of the suggested device. The practicing physiotherapists conducted the assessments for children. This device was reliable and can be used by physiotherapists. This development provides portable hand-eye coordination equipment with reliable readings for the assessment of children.

An In Vitro Hand Simulator for Simultaneous Control of Hand and Wrist Movements.

A human hand is a complex biomechanical system, in which bones, ligaments, and musculotendon units dynamically interact to produce seemingly simple motions. A new physiological hand simulator has been developed, in which electromechanical actuators apply load to the tendons of extrinsic hand and wrist muscles to recreate movements in cadaveric specimens in a biofidelic way. This novel simulator simultaneously and independently controls the movements of the wrist (flexion/extension and radio-ulnar deviation) and flexion/extension of the fingers and thumb. Control of these four degrees of freedom (DOF) is made possible by actuating eleven extrinsic muscles of the hand. The coupled dynamics of the wrist, fingers, and thumb, and the over-actuated nature of the human musculoskeletal system make feedback control of hand movements challenging. Two control algorithms were developed and tested. The optimal controller relies on an optimization algorithm to calculate the required tendon tensions using the collective error in all DOFs, and the action-based controller loads the tendons solely based on their actions on the controlled DOFs (e.g., activating all flexors if a flexing moment is required). Both controllers resulted in hand movements with small errors from the reference trajectories ( ); however, the optimal controller achieved this with 16% lower total force. Owing to its simpler structure, the action-based controller was extended to enable feedback control of grip force. This simulator has been shown to be a highly repeatable tool ( N and variations in force and kinematics, respectively) for in vitro analyses of human hand biomechanics.

Rapid and Bihemispheric Reorganization of Neuronal Activity in Premotor Cortex after Brain Injury.

Brain injuries cause hemodynamic changes in several distant, spared areas from the lesion. Our objective was to better understand the neuronal correlates of this reorganization in awake, behaving female monkeys. We used reversible inactivation techniques to “injure” the primary motor cortex, while continuously recording neuronal activity of the ventral premotor cortex in the two hemispheres, before and after the onset of behavioral impairments. Inactivation rapidly induced profound alterations of neuronal discharges that were heterogeneous within each and across the two hemispheres, occurred during movements of either the affected or nonaffected arm, and varied during different phases of grasping. Our results support that extensive, and much more complex than expected, neuronal reorganization takes place in spared areas of the bihemispheric cortical network involved in the control of hand movements. This broad pattern of reorganization offers potential targets that should be considered for the development of neuromodulation protocols applied early after brain injury.SIGNIFICANCE STATEMENT It is well known that brain injuries cause changes in several distant, spared areas of the network, often in the premotor cortex. This reorganization is greater early after the injury and the magnitude of early changes correlates with impairments. However, studies to date have used noninvasive brain imaging approaches or have been conducted in sedated animals. Therefore, we do not know how brain injuries specifically affect the activity of neurons during the generation of movements. Our study clearly shows how a lesion rapidly impacts neurons in the premotor cortex of both hemispheres. A better understanding of these complex changes can help formulate hypotheses for the development of new treatments that specifically target neuronal reorganization induced by lesions in the brain.

C-Hg

Computer-assisted systems can provide efficient and engaging ASD intervention environments for children with Autism Spectrum Disorder (ASD). However, most existing computer-assisted systems target only one skill deficit (e.g., social conversation skills) and ignore the importance of other areas, such as motor skills, that could also impact social interaction. This focus on a single domain may hinder the generalizability of learned skills to real-world scenarios, because the targeted teaching strategies do not reflect that real-world tasks often involve more than one skill domain. The work presented in this article seeks to bridge this gap by developing a Collaborative Haptic-gripper virtual skill training system (C-Hg). This system includes individual and collaborative games that provide opportunities for simultaneously practicing both fine motor skills (hand movement and grip control skills) as well as social skills (communication and collaboration) and investigating how they relate to each other. We conducted a usability study with 10 children with ASD and 10 Typically Developing (TD) children (8–12 years), who used C-Hg to play a series of individual and collaborative games requiring differing levels of motor and communication skill. Results revealed that participant performance significantly improved in both individual and collaborative fine motor skill training tasks, including significant improvements in collaborative manipulations between partners. Participants with ASD were found to conduct more collaborative manipulations and initiate more conversations with their partners in the post collaborative tasks, suggesting more active collaboration and communication of participants with ASD in the collaborative tasks. Results support the potential of our C-Hg system for simultaneously improving fine motor and social skills, with implications for impacts of improved fine motor skills on social outcomes.

The Causal Role of Three Frontal Cortical Areas in Grasping.

Efficient object grasping requires the continuous control of arm and hand movements based on visual information. Previous studies have identified a network of parietal and frontal areas that is crucial for the visual control of prehension movements. Electrical microstimulation of 3D shape-selective clusters in AIP during functional magnetic resonance imaging activates areas F5a and 45B, suggesting that these frontal areas may represent important downstream areas for object processing during grasping, but the role of area F5a and 45B in grasping is unknown. To assess their causal role in the frontal grasping network, we reversibly inactivated 45B, F5a, and F5p during visually guided grasping in macaque monkeys. First, we recorded single neuron activity in 45B, F5a, and F5p to identify sites with object responses during grasping. Then, we injected muscimol or saline to measure the grasping deficit induced by the temporary disruption of each of these three nodes in the grasping network. The inactivation of all three areas resulted in a significant increase in the grasping time in both animals, with the strongest effect observed in area F5p. These results not only confirm a clear involvement of F5p, but also indicate causal contributions of area F5a and 45B in visually guided object grasping.

Simultaneous and proportional control of wrist and hand movements by decoding motor unit discharges in real time

Objective. Surface electromyography (EMG) decomposition techniques can be used to establish human-machine interfacing (HMI), but most investigations are implemented offline due to the computational load of the approach. Here, we generalize the offline decomposition algorithm to identify the motor unit (MU) activities in real time, and we propose a MU-based approach for online simultaneous and proportional control (SPC) of multiple motor tasks. Approach. High-density surface EMG signals recorded from forearm muscles were decomposed into motor unit spike trains (MUSTs) with the proposed decomposition method. The MUSTs were first pooled into clusters in the calibration phase and the cumulative discharges of active MUs in each group were extracted as the control signal for each motor task. Then the subjects were instructed to control a virtual cursor with multiple motor tasks involving grasp and wrist movements. Fifteen able-bodied subjects and two patients with limb deficiency participated in the experiments to validate the proposed control scheme. Main results. On average, over 20 MUSTs were identified in real time with an estimated decomposition accuracy 85%. The cumulative discharge in each pool was highly correlated with the activation of the specific motion (R = 0.93 ± 0.05). Moreover, the proposed MU-based method had superior performance in online tests than conventional myo-control methods based on global EMG features. Significance. These results indicate the feasibility of real-time neural decoding in a non-invasive way. Moreover, the superior performance in online tests proves the potential of the MU-based approach for the SPC, promoting the application of EMG decomposition for HMI systems.

A Novel Device Decoupling Tactile Slip and Hand Motion in Reaching Tasks: The HaptiTrack Device.

Hand reaching is a complex task that requires the integration of multiple sensory information from muscle, joints and the skin, and an internal model of the motor command. Recent studies in neuroscience highlighted the important role of touch for the control of hand movement while reaching for a target. In this article, present a novel device, the HaptiTrack device, to physically decouple tactile slip motion and hand movements. The new device generates precisely controlled 2D motion of a contact plate, measures contact forces, and provides hand and finger tracking through an external tracking system. By means of a control algorithm described in this manuscript, the velocity of tactile slip can be changed independently from the velocity of the hand sliding on the device's surface. Due to these multiple features, the device can be a powerful tool for the evaluation of tactile sense during hand reaching movements in healthy and pathological conditions.

Abnormal motor surround inhibition associated with cortical and deep grey matter involvement in multiple sclerosis

ObjectiveMotor surround inhibition (mSI) is a physiological mechanism that contributes to hand movement control by focusing voluntary movement. Growing evidence suggests that hand movement control is impaired in multiple sclerosis. The aim of the study was to evaluate mSI in MS and to investigate the brain structures involved in mSI in multiple sclerosis. MethodsWe recruited 33 patients and 23 controls. To investigate mSI, we delivered transcranial magnetic single pulses during index finger flexion. Motor evoked potentials were recorded and first dorsal interosseous (“active muscle”) and from the abductor digiti minimi (“surround muscle”). mSI was expressed as the ratio between Motor evoked potentials recorded from the surround muscle during movement and at rest. Participants underwent a magnetic resonance study. ResultsPatients had impaired mSI as compared with controls. Magnetic resonance showed that basal ganglia had smaller volumes and higher mean diffusivity than controls. Impaired mSI correlated with primary motor cortex and basal ganglia involvement in multiple sclerosis. ConclusionAltered mSI in multiple sclerosis is related to cortical and subcortical grey matter involvement. SignificanceOur study provides the first demonstration of a pathophysiological mechanism underlying hand movement control dysfunction in multiple sclerosis. mSI represents a new therapeutic target of multiple sclerosis rehabilitative approaches.