Muscle activation patterns and kinetics of human index finger movements

Finger Kinematics during Human Hand Grip and Release

A bionic robotic hand can perform many movements similar to a human hand. However, there is still a significant gap in manipulation between robot and human hands. It is necessary to understand the finger kinematics and motion patterns of human hands to improve the performance of robotic hands. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hands of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a larger dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Additionally, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by the PIP joint. Regarding the finger sequence, the thumb started to move before the four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided a kinematic reference for the design of robotic hands and thus contributes to its development.

Modulation of finger muscle activation patterns across postures is coordinated across all muscle groups

Successful grasp requires that grip forces be properly directed between the fingertips and the held object. Changes in digit posture significantly affect the mapping between muscle force and fingertip force. Joint torques must subsequently be altered to maintain the desired force direction at the fingertips. Our current understanding of the roles of hand muscles in force production remains incomplete, as past studies focused on a limited set of postures or force directions. To thoroughly examine how hand muscles adapt to changing external (force direction) and internal (posture) conditions, activation patterns of six index finger muscles were examined with intramuscular electrodes in 10 healthy subjects. Participants produced submaximal isometric forces in each of six orthogonal directions at nine different finger postures. Across force directions, participants significantly altered activation patterns to accommodate postural changes in the interphalangeal joint angles but not changes in the metacarpophalangeal joint angles. Modulation of activation levels of the extrinsic hand muscles, particularly the extensors, were as great as those of intrinsic muscles, suggesting that both extrinsic and intrinsic muscles were involved in creating the desired forces. Despite considerable between-subject variation in the absolute activation patterns, principal component analysis revealed that participants used similar strategies to accommodate the postural changes. The changes in muscle coordination also helped increase joint impedance in order to stabilize the end-point force direction. This effect counteracts the increased signal-dependent motor noise that arises with greater magnitude of muscle activation as interphalangeal joint flexion is increased. These results highlight the role of the extrinsic muscles in controlling fingertip force direction across finger postures.NEW & NOTEWORTHY We examined how hand muscles adapt to changing external (force direction) and internal (posture) conditions. Muscle activations, particularly of the extrinsic extensors, were significantly affected by postural changes of the interphalangeal, but not metacarpophalangeal, joints. Joint impedance was modulated so that the effects of the signal-dependent motor noise on the force output were reduced. Comparisons with theoretical solutions showed that the chosen activation patterns occupied a small portion of the possible solution space, minimizing the maximum activation of any one muscle.

Predictive value of metacarpophalangeal stabilization tests for simulated ulnar nerve lesion measured by a sensor glove

STUDY DESIGN

A within-subject research design was used in this study. The difference of the range of motion (ROM) with and without ulnar nerve block was analyzed.

INTRODUCTION

For the clinical evaluation of the functional effects of ulnar nerve palsy at the hand the relevance of clinical tests is in discussion.

PURPOSE OF THE STUDY

The aim of the study was to evaluate the predictive value of 2 clinical tests for a simulated ulnar nerve lesion by motion analysis with a sensor glove.

METHODS

In 28 healthy subjects, dynamic measurements of the finger joints were performed by a sensor glove with and without ulnar nerve block at the wrist. In the 0° metacarpophalangeal (MCP) stabilization test, the subjects were asked to stabilize the MCP joints actively in 0° while moving the interphalangeal joints, whereas at the 90° MCP stabilization test, the subjects stabilized the MCP joints actively in the 90° position.

RESULTS

In the 0° MCP stabilization test, no remarkable changes of the ROM were found at the MCP joints; at the proximal interphalangeal joints 2-5, the ROM decreased with ulnar nerve block, significantly at the index, middle, and ring fingers (P < .05). In the 90° MCP stabilization test, the average ROM of the MCP joints 2-5 significantly increased with ulnar nerve block (P < .05), whereas at the PIP joints, the average ROM decreased (P < .05).

DISCUSSION

The 90° MCP stabilization test had a high predictive value for the discrimination between healthy subjects and subjects with a simulated peripheral ulnar nerve lesion.

CONCLUSIONS

The results could be relevant for the determination of the functional effect of ulnar nerve palsy and the quantification of clawing in hand rehabilitation.

LEVEL OF EVIDENCE

II.

Effects of task dynamics on coordination of the hand muscles and their adaptation to targeted muscle assistance

Dynamic characteristics of a manual task can affect the control of hand muscles due to the difference in biomechanical/physiological characteristics of the muscles and sensory afferents in the hand. We aimed to examine the effects of task dynamics on the coordination of hand muscles, and on the motor adaptation to external assistance. Twenty-four healthy subjects performed one of the two types of a finger extension task, isometric dorsal fingertip force production (static) or isokinetic finger extension (dynamic). Subjects performed the tasks voluntarily without assistance, or with a biomimetic exotendon providing targeted assistance to their extrinsic muscles. In unassisted conditions, significant between-task differences were found in the coordination of the extrinsic and intrinsic hand muscles, while the extrinsic muscle activities were similar between the tasks. Under assistance, while the muscle coordination remained relatively unaffected during the dynamic task, significant changes in the coordination between the extrinsic and intrinsic muscles were observed during the static task. Intermuscular coherence values generally decreased during the static task under assistance, but increased during the dynamic task (all p-values < 0.01). Additionally, a significant change in the task dynamics was induced by assistance only during static task. Our study showed that task type significantly affect coordination between the extrinsic and intrinsic hand muscles. During the static task, a lack of sensory information from musculotendons and joint receptors (more sensitive to changes in length/force) is postulated to have resulted in a neural decoupling between muscles and a consequent isolated modulation of the intrinsic muscle activity.

The Biomechanical Basis of the Claw Finger Deformity: A Computational Simulation Study

PURPOSE

Claw finger deformity occurs during attempted finger extension in patients whose intrinsic finger muscles are weakened or paralyzed by neural impairments. The deformity is generally not acutely present after intrinsic muscle palsy. The delayed onset, with severity progressing over time, suggests soft tissue changes that affect the passive biomechanics of the hand exacerbate and advance the deformity. Clinical interventions may be more effective if such secondary biomechanical changes are effectively addressed. Using a computational model, we simulated these altered soft tissue biomechanical properties to quantify their effects on coordinated finger extension.

METHODS

To evaluate the effects of maladaptive changes in soft tissue biomechanical properties on the development and progression of the claw finger deformity after intrinsic muscle palsy, we completed 45 biomechanical simulations of cyclic index finger flexion and extension, varying the muscle excitation level, clinically relevant biomechanical factors, and wrist position. We evaluated to what extent (1) increased joint laxity, (2) decreased mechanical advantage of the extensors about the proximal interphalangeal joint, and (3) shortening of the flexor muscles contributed to the development of claw finger deformity in an intrinsic-minus hand model.

RESULTS

Of the mechanisms studied, shortening (or contracture) of the extrinsic finger flexors was the factor most associated with the development of claw finger deformity in simulation.

CONCLUSIONS

These simulations suggest that adaptive shortening of the extrinsic finger flexors is required for the development of claw finger deformity. Increased joint laxity and decreased extensor mechanical advantage only contributed to the severity of the deformity in simulations when shortening of the flexor muscles was present.

CLINICAL RELEVANCE

In both the acute and chronic stages of intrinsic finger paralysis, maintaining extrinsic finger flexor length should be an area of focus in rehabilitation to prevent formation of the claw finger deformity and achieve optimal outcomes after surgical interventions.

Experimental and theoretical study of velocity fluctuations during slow movements in humans

Moving smoothly is generally considered as a higher-order goal of motor control and moving jerkily as a witness of clumsiness or pathology, yet many common and well-controlled movements (e.g., tracking movements) have irregular velocity profiles with widespread fluctuations. The origin and nature of these fluctuations have been associated with the operation of an intermittent process but in fact remain poorly understood. Here we studied velocity fluctuations during slow movements, using combined experimental and theoretical tools. We recorded arm movement trajectories in a group of healthy participants performing back-and-forth movements at different speeds, and we analyzed velocity profiles in terms of series of segments (portions of velocity between 2 minima). We found that most of the segments were smooth (i.e., corresponding to a biphasic acceleration) and had constant duration irrespective of movement speed and linearly increasing amplitude with movement speed. We accounted for these observations with an optimal feedback control model driven by a staircase goal position signal in the presence of sensory noise. Our study suggests that one and the same control process can explain the production of fast and slow movements, i.e., fast movements emerge from the immediate tracking of a global goal position and slow movements from the successive tracking of intermittently updated intermediate goal positions. NEW & NOTEWORTHY We show in experiments and modeling that slow movements could result from the brain tracking a sequence of via points regularly distributed in time and space. Accordingly, slow movements would differ from fast movement by the nature of the guidance and not by the nature of control. This result could help in understanding the origin and nature of slow and segmented movements frequently observed in brain disorders.

Assessing Finger Joint Biomechanics by Applying Equal Force to Flexor Tendons In Vitro Using a Novel Simultaneous Approach

Background

The flexor digitorum superficialis (FDS) and flexor digitorum profundus (FDP) are critical for finger flexion. Although research has recently focused on these tendons’ coactivity, their contributions in different tasks remain unclear. This study created a novel simultaneous approach to investigate the coactivity between the tendons and to clarify their contributions in different tasks.

Methods

Ten human cadaveric hands were mounted on our custom frame with the FDS and FDP of the third finger looped through a mechanical pulley connected to a force transducer. Joint range of motion, tendon excursion and loading force were recorded during individual joint motion and free joint movement from rest to maximal flexion. Each flexor tendon’s moment arm was then calculated.

Results

In individual motions, we found that the FDP contributed more than the FDS in proximal interphalangeal (PIP) joint motion, with an overall slope of 1.34 and all FDP-to-FDS excursion (P/S) ratios greater than 1.0 with force increase. However, the FDP contributed less than the FDS in metacarpophalangeal (MCP) joint motion, with an overall slope of 0.95 and P/S ratios smaller than 1.0 throughout the whole motion except between 1.9% and 13.1% force. In free joint movement, the FDP played a greater role than the FDS, with an overall ratio of 1.37 and all P/S ratios greater than 1.0.

Conclusions

The new findings include differences in finger performance and excursion amounts between the FDS and FDP throughout flexion. Such findings may provide the basis for new hand models and treatments.

Decoding upper limb residual muscle activity in severe chronic stroke

Objective

Stroke is a leading cause of long-term motor disability. Stroke patients with severe hand weakness do not profit from rehabilitative treatments. Recently, brain-controlled robotics and sequential functional electrical stimulation allowed some improvement. However, for such therapies to succeed, it is required to decode patients' intentions for different arm movements. Here, we evaluated whether residual muscle activity could be used to predict movements from paralyzed joints in severely impaired chronic stroke patients.

Methods

Muscle activity was recorded with surface-electromyography (EMG) in 41 patients, with severe hand weakness (Fugl-Meyer Assessment [FMA] hand subscores of 2.93 ± 2.7), in order to decode their intention to perform six different motions of the affected arm, required for voluntary muscle activity and to control neuroprostheses. Decoding of paretic and nonparetic muscle activity was performed using a feed-forward neural network classifier. The contribution of each muscle to the intended movement was determined.

Results

Decoding of up to six arm movements was accurate (>65%) in more than 97% of nonparetic and 46% of paretic muscles.

Interpretation

These results demonstrate that some level of neuronal innervation to the paretic muscle remains preserved and can be used to implement neurorehabilitative treatments in 46% of patients with severe paralysis and extensive cortical and/or subcortical lesions. Such decoding may allow these patients for the first time after stroke to control different motions of arm prostheses through muscle-triggered rehabilitative treatments.

Balancing the excitability of M1 circuitry during movement observation without overt replication

Although observation of a movement increases the excitability of the motor system of the observer, it does not induce a motor replica. What is the mechanism for replica suppression? We performed a series of experiments, involving a total of 66 healthy humans, to explore the excitability of different M1 circuits and the spinal cord during observation of simple movements. Several strategies were used. In the first and second experimental blocks, we used several delay times from movement onset to evaluate the time-course modulation of the cortico-spinal excitability (CSE), and its potential dependency on the duration of the movement observed; in order to do this single pulse transcranial magnetic stimulation (TMS) over M1 was used. In subsequent experiments, at selected delay times from movement-onset, we probed the excitability of the cortico-spinal circuits using three different approaches: (i) electric cervicomedullary stimulation (CMS), to test spinal excitability, (ii) paired-pulse TMS over M1, to evaluate the cortical inhibitory-excitatory balance (short intracortical inhibition (SICI) and intracortical facilitation (ICF)], and (iii) continuous theta-burst stimulation (cTBS), to modulate the excitability of M1 cortical circuits. We observed a stereotyped response in the modulation of CSE. At 500 ms after movement-onset the ICF was increased; although the most clear-cut effect was a decrease of CSE. The compensatory mechanism was not explained by changes in SICI, but by M1-intracortical circuits targeted by cTBS. Meanwhile, the spinal cord maintained the elevated level of excitability induced when expecting to observe movements, potentially useful to facilitate any required response to the movement observed.

The effects of expectancy on corticospinal excitability: passively preparing to observe a movement

The corticospinal tract excitability is modulated when preparing movements. Earlier to movement execution, the excitability of the spinal cord increases waiting for supraspinal commands to release the movement. Movement execution and movement observation share processes within the motor system, although movement observation research has focused on processes later to movement onset. We used single and paired pulse transcranial magnetic stimulation on M1 ( n = 12), and electrical cervicomedullary stimulation ( n = 7), to understand the modulation of the corticospinal system during the “preparation” to observe a third person's movement. Subjects passively observed a hand that would remain still or make an index finger extension. The observer's corticospinal excitability rose when “expecting to see a movement” vs. when “expecting to see a still hand.” The modulation took origin at a spinal level and not at the corticocortical networks explored. We conclude that expectancy of seeing movements increases the excitability of the spinal cord.

Terminal distribution of the corticospinal projection from the hand/arm region of the primary motor cortex to the cervical enlargement in rhesus monkey

To further our understanding of the corticospinal projection (CSP) from the hand/arm representation of the primary motor cortex (M1), high-resolution anterograde tracing methodology and stereology were used to investigate the terminal distribution of this connection at spinal levels C5 to T1. The highest number of labeled terminal boutons occurred contralaterally (98%) with few ipsilaterally (2%). Contralaterally, labeled boutons were located within laminae I-X, with the densest distribution found in lamina VII and, to a lesser extent, laminae IX and VI. Fewer terminals were found in other contralateral laminae. Within lamina VII, terminal boutons were most prominent in the dorsomedial, dorsolateral, and ventrolateral subsectors. Within lamina IX, the heaviest terminal labeling was distributed dorsally. Ipsilaterally, boutons were found in laminae V-X. The most pronounced distribution occurred in the dorsomedial and ventromedial sectors of lamina VII and fewer labeled boutons were located in other ipsilateral laminae. Segmentally, contralateral lamina VII labeling was highest at levels C5-C7. In contrast, lamina IX labeling was highest at C7-T1 and more widely dispersed among the quadrants at C8-T1. Our findings suggest dominant contralateral influence of the M1 hand/arm CSP, a contralateral innervation pattern in lamina VII supporting Kuypers (1982) conceptual framework of a "lateral motor system," and a projection to lamina IX indicating significant influence on motoneurons innervating flexors acting on the shoulder and elbow rostrally (C5-C7), along with flexors, extensors, abductors and adductors acting on the digits, hand and wrist caudally (C8-T1).

Wrist posture affects hand and forearm muscle stress during tapping

Non-neutral wrist posture is a risk factor of the musculoskeletal disorders among computer users. This study aimed to assess internal loads on hand and forearm musculature while tapping in different wrist postures. Ten healthy subjects tapped on a key switch using their index finger in four wrist postures: straight, ulnar deviated, flexed and extended. Torque at the finger and wrist joints were calculated from measured joint postures and fingertip force. Muscle stresses of the six finger muscles and four wrist muscles that balanced the calculated joint torques were estimated using a musculoskeletal model and optimization algorithm minimizing the squared sum of muscle stress. Non-neutral wrist postures resulted in greater muscle stresses than the neutral (straight) wrist posture, and the stress in the extensor muscles were greater than the flexors in all conditions. Wrist extensors stress remained higher than 4.5 N/cm² and wrist flexor stress remained below 0.5 N/cm² during tapping. The sustained high motor unit recruitment of extensors suggests a greater risk than other muscles especially in flexed wrist posture. This study demonstrated from the perspective of internal tissue loading the importance of maintaining neutral wrist posture during keying activities.

Identification of three movement phases of the hand during lateral and pulp pinches using video motion capture

BACKGROUND

Hand injuries affect a person's ability to engage successfully in activities of daily living (ADLs). Video motion capture (VMC) facilitates measurement of dynamic movement. No study to date has used VMC as a means of quantifying the simultaneous movement patterns of all joints of all digits of the hand during active purposeful movement.

METHOD

The purpose of this study was to analyze all joints of all five digits during active completion of the lateral and pulp pinches. VMC data were collected from four participants during completion of two pinches. Joint angles were plotted to facilitate identification of movement patterns.

RESULTS

Range of motion recorded in all joints with VMC, excluding flexion of the thumb carpometacarpal of both pinches, coincided with the normative goniometric data. Three phases were observed: initiation, preshaping, and pinch phases. Patterns of movement in all digits were identified for the two pinches.

CONCLUSION

VMC is a feasible and valid method for objectively quantifying dynamic movement of multiple joints simultaneously. The results provide new insight to the dynamics of hand movement as well as a basis for subsequent evaluations of movement patterns performed in ADLs and instrumental ADLs.

Contributions of intrinsic visco-elastic torques during planar index finger and wrist movements

Human hand movements have been studied for many decades, yet the role of hand biomechanics in achieving dexterity has not been fully understood. In this paper, we investigate the contributions of the intrinsic passive viscoelastic component in the hand during the coordinated wrist and hand movements. We compare the contributions of stiffness, damping, and dynamics torques under two types of joint phase movements at two speeds. The analysis of the data collected from subject studies demonstrated that the passive visco-elastic component is dominant over dynamic coupling terms. Although the exact contributions of the three torques vary under different speeds and phasic movements, the stiffness torque was the highest (at least 47%) followed by the damping torque, while the dynamics torque was the lowest (less than 11%) in all movement scenarios. Comparisons with studies involving coordinated arm movements illustrate that dominant torques in arm and hand movements are different suggesting that neural control strategies might be distinct as well.

Use of a novel robotic interface to study finger motor control

Stroke is the leading cause of permanent adult disability in the U.S., frequently resulting in chronic motor impairments. Rehabilitation of the upper limb, particularly the hand, is especially important as arm and hand deficits post-stroke limit the performance of activities of daily living and, subsequently, functional independence. Hand rehabilitation is challenging due to the complexity of motor control of the hand. New instrumentation is needed to facilitate examination of the hand. Thus, a novel actuated exoskeleton for the index finger, the FingerBot, was developed to permit the study of finger kinetics and kinematics under a variety of conditions. Two such novel environments, one applying a spring-like extension torque proportional to angular displacement at each finger joint and another applying a constant extension torque at each joint, were compared in 10 stroke survivors with the FingerBot. Subjects attempted to reach targets located throughout the finger workspace. The constant extension torque assistance resulted in a greater workspace area (p < 0.02) and a larger active range of motion for the metacarpophalangeal joint (p < 0.01) than the spring-like assistance. Additionally, accuracy in terms of reaching the target was greater with the constant extension assistance as compared to no assistance. The FingerBot can be a valuable tool in assessing various hand rehabilitation paradigms following stroke.

Uncovering patterns of forearm muscle activity using multi-channel mechanomyography

A coordinated activation of distal forearm muscles allows the hand and fingers to be shaped during movement and grasp. However, little is known about how the muscle activation patterns are reflected in multi-channel mechanomyogram (MMG) signals. The purpose of this study is to determine if multi-site MMG signals exhibit distinctive patterns of forearm muscle activity. MMG signals were recorded from forearm muscle sites of nine able-bodied participants during hand movement. By using 14 features selected by a genetic algorithm and classified by a linear discriminant analysis classifier (LDA), we show that MMG patterns are specific and consistent enough to identify 7+/-1 hand movements with an accuracy of 90+/-4%. MMG-based movement recognition required a minimum of three recording sites. Further, by classifying five classes of contraction patterns with 98+/-3% accuracy from MMG signals recorded from the residual limb of an amputee participant, we demonstrate that MMG shows pattern-specificity even in the absence of typical musculature. Multi-site monitoring of the RMS of MMG signals is suggested as a method of estimating the relative contributions of muscles to motor tasks. The patterns in MMG facilitate our understanding of the mechanical activity of muscles during movement.

Characterization of EMG patterns from proximal arm muscles during object- and orientation-specific grasps

Reach-to-grasp tasks are composed of several actions that are more and more considered as simultaneously controlled by the central nervous system in a feedforward manner (at least for well-known activities). If this hypothesis is correct, during prehension tasks, the activity of proximal muscles (and not only of the distal ones used to control finger movements) is modulated according to the kind of object to be grasped and its position. This means that different objects could be identified by processing the electromyographic (EMG) signals recorded from proximal muscles. In this paper, specific experiments have been carried out to support this hypothesis in able-bodied subjects. The results achieved seem to confirm this possibility by showing that the activation of proximal muscles can be statistically different for different grip types. This finding supports the hypothesis that proximal and distal muscles are simultaneously controlled during reaching and grasping. Moreover, this kind of information could allow the development of an EMG-based control strategy based on the natural muscular activities selected by the central nervous system.

Beyond parameter estimation: extending biomechanical modeling by the explicit exploration of model topology

Selecting a model topology that realistically predicts biomechanical function remains an unsolved problem. Today's dominant modeling approach is to replicate experimental input/output data by performing parameter estimation on an assumed topology. In contrast, we propose that modeling some complex biomechanical systems requires the explicit and simultaneous exploration of model topology (i.e., the type, number, and organization of physics-based functional building blocks) and parameter values. In this paper, we use the example of modeling the notoriously complex tendon networks of the fingers to present three critical advances towards the goal of implementing this extended modeling paradigm. First, we describe a novel computational environment to perform quasi-static simulations of arbitrary topologies of elastic structures undergoing large deformations. Second, we use this form of simulation to show that the assumed topology for the tendon network of a finger plays an important role in the propagation of tension to the finger joints. Third, we demonstrate the use of a novel inference algorithm that simultaneously explores the topology and parameter values for hidden synthetic tendon networks. We conclude by discussing critical issues of observability, separability, and uniqueness of topological features inferred from input/output data, and outline the challenges that need to be overcome to apply this novel modeling paradigm to extract causal models in real anatomical systems.

Finger flexor motor control patterns during active flexion: an in vivo tendon force study

An in vivo tendon force measurement system was used to evaluate index finger flexor motor control patterns during active finger flexion. During open carpal tunnel release surgery (N=12) the flexor digitorum profundus (FDP) and flexor digitorum superficilias (FDS) tendons were instrumented with buckle force transducers and participants performed finger flexion at two different wrist angles (0 degrees or 30 degrees ). During finger flexion, there was concurrent change of metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joint angles, but the FDP and FDS tendon force changes were not concurrent. For the FDS tendon, no consistent changes in force were observed across participants at either wrist angle. For the FDP tendon, there were two force patterns. With the wrist in a neutral posture, the movement was initiated without force from the finger flexors, and further flexion (after the first 0.5s) was carried out with force from the FDP. With the wrist in a flexed posture, the motion was generally both initiated and continued using FDP force. At some wrist postures, finger flexion was initiated by passive forces which were replaced by FDP force to complete the motion.

Finger joint coordination during tapping

We investigated finger joint coordination during tapping by characterizing joint kinematics and torques in terms of muscle activation patterns and energy profiles. Six subjects tapped with their index finger on a computer keyswitch as if they were typing on the middle row of a keyboard. Fingertip force, keyswitch position, kinematics of the metacarpophalangeal (MCP) and the proximal and distal interphalangeal (IP) joints, and intramuscular electromyography of intrinsic and extrinsic finger muscles were measured simultaneously. Finger joint torques were calculated based on a closed-form Newton-Euler inverse dynamic model of the finger. During the keystroke, the MCP joint flexed and the IP joints extended before and throughout the loading phase of the contact period, creating a closing reciprocal motion of the finger joints. As the finger lifted, the MCP joint extended and the interphalangeal (IP) joints flexed, creating an opening reciprocal motion. Intrinsic finger muscle and extrinsic flexor activities both began after the initiation of the downward finger movement. The intrinsic finger muscle activity preceded both the IP joint extension and the onset of extrinsic muscle activity. Only extrinsic extensor activity was present as the finger was lifted. While both potential energy and kinetic energy are present and large enough to overcome the work necessary to press the keyswitch, the motor control strategies utilize the muscle forces and joint torques to ensure a successful keystroke.

Finger motion analysis of the patients with cervical myelopathy

STUDY DESIGN

Pinch motion between the thumb and the index finger in myelopathy hand was analyzed using micro-reflective markers and the VICON system.

OBJECTIVE

To clarify the disturbance in small finger motions of the myelopathy hand.

SUMMARY OF BACKGROUND DATA

Specificity of hand dysfunction of the patients with cervical myelopathy was recently recognized as the myelopathy hand. The author established the video-based finger motion analysis system and have been applied it to some disease with abnormal pattern in finger movement.

METHODS

The subjects included 11 normal persons (normal group; mean age, 30.2 years) and 9 patients with cervical myelopathy caused by spondylosis, ossification of the posterior longitudinal ligament, or disc herniation (myelopathy group; mean age, 56.0 years). All patients exhibited myelopathy hand, which was defined by two specific signs: the finger escape sign and the inability to grip and release rapidly with the fingers. Fourteen 3-mm micro-reflective markers were placed on the dorsal surface of the thumb and the index finger, and on the dorsal hand. Repeated pinching of a small ball, coin, and small rod was recorded by four infrared video cameras with the movement of each marker tracked in three dimensions. The flexion angle of the thumb IP and MCP joints, and the DIP, PIP, and MCP joints of the index finger were calculated as the angle between the vector joining the markers.

RESULTS

When pinching the ball, the mean maximum flexion angle and arc of motion of the index DIP and PIP joints were significantly larger in the myelopathy group than in the normal group, while there was no difference in the MCP joint. In the thumb, the maximum flexion angle and the arc of motion of the thumb MCP joint were significantly larger in the myelopathy group than in the normal group. In addition, the arc of motion of the thumb IP joint was larger in the myelopathy group than in the normal group. Similar results were obtained when pinching the coin and small bar.

CONCLUSION

Overall, the patients with myelopathy hand exhibited a larger flexion angle in the two distal finger joints when pinching small objects.

Kinematic and dynamic synergies of human precision-grip movements

We analyzed the adaptability of human thumb and index finger movement kinematics and dynamics to variations of precision grip aperture and movement velocity. Six subjects performed precision grip opening and closing movements under different conditions of movement velocity and movement aperture (thumb and index finger tip-to-tip distance). Angular motion of the thumb and index finger joints was recorded with a CyberGlove and a three-dimensional biomechanical model was used for solving the inverse dynamics problem during precision grip movements, i.e., for calculating joint torques from experimentally obtained angular variations. The time-varying joint angles and joint torques were analyzed by principal-component analysis to quantify the contributions of individual joints in kinematic and dynamic synergies. At the level of movement kinematics, we found subject-specific angular contributions. However, the adaptation to large aperture, achieved by an increase of the relative contribution of the proximal joints, was subject-invariant. At the level of movement dynamics, the adaptation of thumb-index finger movements to task constraints was similar among all subjects and required the linear scaling of joint torques, the synchronization of joint torques under high velocity conditions, and a flexible redistribution of joint torques between the proximal joint of the thumb and that of the index finger. This work represents one of the first attempts at calculating the joint torques during human precision-grip movements and indicates that the dynamic synergies seem to be remarkably simple compared with the synergies found for movement kinematics.

An integrative approach to the biomechanical function and neuromuscular control of the fingers

The exquisite mechanical functionality and versatility of the human hand emerges from complex neuro-musculo-skeletal interactions that are not completely understood. I have found it useful to work within a theoretical/experimental paradigm that outlines the fundamental neuro-musculo-skeletal components and their interactions. In this integrative paradigm, the laws of mechanics, the specifications of the manipulation task, and the sensorimotor signals define the interactions among hand anatomy, the nervous system, and manipulation function. Thus, our collaborative research activities emphasize a firm grounding in the mechanics of finger function, insistence on anatomical detail, and meticulous characterization of muscle activity. This overview of our work on precision pinch (i.e., the ability to produce and control fingertip forces) presents some of our findings around three Research Themes: Mechanics-based quantification of manipulation ability; Anatomically realistic musculoskeletal finger models; and Neural control of finger muscles. I conclude that (i) driving the fingers to some limit of sensorimotor performance is instrumental to elucidating motor control strategies; (ii) that the cross-over of tendons from flexors to extensors in the extensor mechanism is needed to produce force in every direction, and (iii) the anatomical routing of multiarticular muscles makes co-contraction unavoidable for many tasks. Moreover, creating realistic and clinically useful finger models still requires developing new computational means to simulate the viscoelastic tendinous networks of the extensor mechanism, and the muscle-bone-ligament interactions in complex articulations. Building upon this neuromuscular biomechanics paradigm is of immense clinical relevance: it will be instrumental to the development of clinical treatments to preserve and restore manual ability in people suffering from neurological and orthopedic conditions. This understanding will also advance the design and control of robotic hands whose performance lags far behind that of their biological counterparts.

Finger joint impedance during tapping on a computer keyswitch

We studied the dynamic behavior of finger joints during the contact period of tapping on a computer keyswitch, to characterize and parameterize joint function with a lumped-parameter impedance model. We tested the hypothesis that the metacarpophalangeal (MCP) and interphalangeal (IP) joints act similarly in terms of kinematics, torque, and energy production when tapping. Fifteen human subjects tapped with the index finger of the right hand on a computer keyswitch mounted on a two-axis force sensor, which measured forces in the vertical and sagittal planes. Miniature fiber-optic goniometers mounted across the dorsal side of each joint measured joint kinematics. Joint torques were calculated from endpoint forces and joint kinematics using an inverse dynamic algorithm. For each joint, a linear spring and damper model was fitted to joint torque, position, and velocity during the contact period of each tap (22 per subject on average). The spring-damper model could account for over 90% of the variance in torque when loading and unloading portions of the contact were separated, with model parameters comparable to those previously measured during isometric loading of the finger. The finger joints functioned differently, as illustrated by energy production during the contact period. During the loading phase of contact the MCP joint flexed and produced energy, whereas the proximal and distal IP joints extended and absorbed energy. These results suggest that the MCP joint does work on the interphalangeal joints as well as on the keyswitch.

Patterns of muscle activity underlying object-specific grasp by the macaque monkey

During object grasp, a coordinated activation of distal muscles is required to shape the hand in relation to the physical properties of the object. Despite the fundamental importance of the grasping action, little is known of the muscular activation patterns that allow objects of different sizes and shapes to be grasped. In a study of two adult macaque monkeys, we investigated whether we could distinguish between EMG activation patterns associated with grasp of 12 differently shaped objects, chosen to evoke a wide range of grasping postures. Each object was mounted on a horizontal shuttle held by a weak spring (load force 1-2 N). Objects were located in separate sectors of a "carousel," and inter-trial rotation of the carousel allowed sequential presentation of the objects in pseudorandom order. EMG activity from 10 to 12 digit, hand, and arm muscles was recorded using chronically implanted electrodes. We show that the grasp of different objects was characterized by complex but distinctive patterns of EMG activation. Cluster analysis shows that these object-related EMG patterns were specific and consistent enough to identify the object unequivocally from the EMG recordings alone. EMG-based object identification required a minimum of six EMGs from simultaneously recorded muscles. EMG patterns were consistent across recording sessions in a given monkey but showed some differences between animals. These results identify the specific patterns of activity required to achieve distinct hand postures for grasping, and they open the way to our understanding of how these patterns are generated by the central motor network.

Effect of intramuscular botulinum toxin injection on upper limb spasticity in stroke patients

OBJECTIVE

To evaluate the therapeutic effect of intramuscular injection of botulinum toxin on spasticity of the upper limb, with emphasis on its influence over limb function.

DESIGN

An open-label, noncontrolled trial with a duration of 12 wk was designed to determine the safety and efficacy of intramuscular botulinum toxin A injection in the treatment of 16 patients with stroke with spastic hemiparesis. Electromyographically guided intramuscular botulinum toxin A injections were applied to the spastic limbs. A detailed scale system was used for the evaluation of muscle tone and functional changes induced by botulinum toxin A treatment.

RESULTS

No major side effect secondary to botulinum toxin A injection was reported. Statistically significant (P < 0.05) improvements of muscle tone, joint range of motion, hand muscle strength, and muscular pain were seen after the injection. The improvements lasted up to 8-12 wk after the treatment. However, there was no significant functional improvement except in two of the patients.

CONCLUSIONS

Botulinum toxin A injection may help relieve upper limb spasticity and pain in patients with stroke. Its effect on function is probably determined by case selection.

A demonstration of validity of 3-D video motion analysis method for measuring finger flexion and extension

This study demonstrates the validity of using 3-D video motion analysis to measure hand motion. Several researchers have devised ingenious methods to study normal and abnormal hand movements. Although very helpful, these earlier studies are static representations of a dynamic phenomenon. Despite the many studies of hand motion using scientifically impeccable techniques, little is known about digital motion, and there are still few researchers investigating dynamic three-dimensional motion of the hand. Results from a three-camera video motion analysis system were compared to those from the "gold standard", 2-D lateral view fluoroscopy. We used these two methods to record hand motion simultaneously during unrestricted flexion and extension of the index finger of the dominant hand in 6 neurologically normal, healthy volunteers. After collection and post-processing, the waveforms of the PIP, DIP and MCP joint angles were compared using the adjusted coefficient of multiple determination (R2(a), or CMD). The mean CMD values for the MCP, PIP and DIP joint angle waveforms were 0.96, 0.98 and 0.94, respectively, suggesting a close similarity between motion of comparable joints analyzed by the 2-D and 3-D methods. This shows that the method of 3-D motion analysis is capable of accurately quantifying digital joint motion. It is anticipated that 3-D motion analysis, in addition to being used as a research tool, will also have clinical applications such as surgical planning in neuromuscular disorders and the documentation of abnormal motion in many other pathological hand conditions.

Characterization of multijoint finger stiffness: dependence on finger posture and force direction

The two-dimensional static stiffness of the index finger was measured with the interphalangeal joints in flexed and extended postures. The stiffness of the relaxed finger was compared with the stiffness when voluntary force was exerted in different directions. The finger stiffness was found to be anisotropic, with the direction of greatest stiffness being approximately parallel to the proximal phalange of the finger. This direction was relatively unaffected by finger posture or direction of finger force. Finger stiffness was more anisotropic when the interphalangeal joints were extended than flexed. The stiffness was most anisotropic when the interphalangeal joints were extended and force was being exerted in the direction of pointing, while it was least anisotropic when the interphalangeal joints were flexed and force was being exerted in directions normally associated with pinching and tapping actions. The stiffness of the individual finger joints was computed and the relation between stiffness and joint torque was examined. Previous studies, which examined single finger joints in isolation, had found that joint stiffness varied in a linear fashion with net joint torque. In contrast, we did not find a monotonic relation between joint stiffness and net joint torque, which we attributed to the need to vary the amount of cocontraction of antagonistic muscles when controlling the direction of finger force.

Fine-wire electromyographic recording during force generation. Application to index finger kinesiologic studies

When accurately placed, fine-wire electrodes (FWEs) permit selective electromyographic recording during kinesiologic studies; however, their potential to limit contraction of the index finger muscles has not previously been evaluated. Given that these electrodes cannot be reinserted, reliable techniques are necessary to achieve proper placement while minimizing subject discomfort and electrode waste. The small size, close arrangement, and anatomic variability of hand and forearm muscles create challenges to achieving these goals. In this study, we simultaneously measured maximal fingertip forces and fine-wire electromyographic signals from all seven muscles of the index finger. Forces in five directions, with and without FWEs in place, were not statistically different (repeated-measures analysis of variance, P < 0.46) in five healthy adult subjects. To guide electrode placement, we identified skin penetration landmarks, direction of needle advancement, and depth of muscle fibers. Fibers of flexor digitorum superficialis and flexor digitorum profundus to the index finger were more distal than depicted in textbooks, requiring electrode placement at or distal to the midpoint of the forearm. For these muscles and the extensor digitorum, locating the desired fibers first with a monopolar needle electrode facilitated subsequent FWE placement. For the dorsal and palmar interossei, lumbrical, and extensor indicis proprius, insertion was aided by concurrent monitoring of the electromyographic signals. We achieved a 93% success rate during FWE placement in a total of 60 muscles. Techniques for recording from each of the seven index finger muscles are described.

A dynamic model of the hand with application in functional neuromuscular stimulation

Potential hand function in people with tetraplegia was evaluated using a three-dimensional dynamic mathematical model. The model was used to evaluate hand positioning, grasp force, and the outcome of surgeries such as tendon transfers and joint fusion, in situations typical of those encountered when using functional neuromuscular stimulation to restore function in people with tetraplegia. In the model, the hand is treated as a jointed multibody system. Each joint is subjected to muscle moments, passive joint moment, and moments due to grasp forces. Model simulations showed that function was highly dependent on both muscle strength and joint passive moments. The potential for tendon transfers, such as the Zancolli-lasso and intrinsicplasty, plasty, to improve hand function was demonstrated, but their value is subject-dependent. It was also shown that activation of multiple thumb muscles (adductor pollicis, abductor pollicis brevis, and flexor pollicis longus) without interphalangeal joint fusion can provide convenient lateral pinch posture with approximately 70% more grip force than a currently used method, which includes joint fusion but requires only one muscle. Finally, a grasp protocol was introduced and shown successful in palmar grasp and hold of movable cylindrical objects using only extrinsic muscles, provided the fingers could be extended sufficiently to enclose the object.

An experimentally based nonlinear viscoelastic model of joint passive moment

Previous investigations have not converged on a generally accepted model of the dissipative part of joint passive moment. To provide a basis for developing a model, a series of measurements were performed to characterize the passive moment at the metacarpophalangeal joint of the index finger. Two measurement procedures were used, one in moment relaxation over a range of fixed joint angles and the other at a series of constant joint velocities. Fung's quasi-linear viscoelastic theory motivated the development of the passive moment model. Using this approach, it was not necessary to make restrictive assumptions regarding the viscoelastic behavior of the passive moment. The generality of the formulation allowed specific functions to be chosen based on experimental data rather than finding coefficients which attempted to fit a preselected model of the data. It was shown that a nonlinear viscoelastic model described the passive stiffness. No significant frictional effects were found. Of particular importance was the nonlinear behavior of the dissipative part of the passive moment which was modeled by joint speed raised to a power less than one. This result could explain the differing findings among previous investigations, and may have important implications for control of limb movement.

A quantitative description of typing biomechanics

One approach to combating work- related upper extremity musculoskeletal disorders (UEMSDs) is to improve understanding of MSD risk factors through quantitative biomechanical characterization of manual tasks, including joint postures, joint dynamics, and force exertion. This paper describes a methodology employed to quantitatively assess professional typing in a workplace setting, and the results of that assessment. Results are compared between different kinds of typing tasks, and between typing and hand- intensive industrial tasks, based on nontask- specific biomechanical terms. Quantitative, biomechanical characterizations of manual tasks will lead to identification of appropriate ranges for joint kinematics and force exertion, which will, in turn, facilitate proper design of manual tasks. Additionally, the methodology could be used to assess manual performance of skilled tasks for proper (healthy) technique, or be used to evaluate progress through a course of rehabilitation (when do an impaired worker's motions begin to resemble motions of healthy workers?).

Coordination of index finger movements

The purpose of this investigation was to describe the patterns of coordination among the joint motions of the index finger, and among the EMGs of index finger muscles. Index finger movements involving all three joints were varied in speed and direction. Joint motions were recorded along with fine-wire EMG from all the muscles that insert into the index finger. We observed nearly linear relationships for angular position between the two interphalangeal (IP) joints, and between the metacarpophalangeal (MP) and proximal IP (PIP) joints regardless of movement, speed and direction. The activities of the extrinsic flexors were of similar magnitude and were highly correlated when they acted as agonists but were poorly correlated when they acted as antagonists to the movement. Extrinsic extensor muscles behaved in this way also. The activation patterns of the intrinsic musculature correlated weakly except for extension movements voluntarily limited to the IP joints. We conclude that the highly coordinated action of the extrinsic flexors during flexion contribute importantly to the linked motions of the IP joints in part because these muscles span two or all the three index finger joints. Hence, interjoint movement patterns appear not to arise solely from restraints imposed by passive tissues, especially for fast flexion movements. The weakly correlated intrinsic muscle activity does not uncouple the flexion motions at the PIP and DIP joints because these muscles exert extensor torques at both IP joints. However, the actions of the intrinsic muscles are necessary for stabilizing the MP joint in flexion postures during IP motion and in producing motions voluntarily limited to the MP joint.