Distribution of motor unit force in human extensor digitorum assessed by spike-triggered averaging and intraneural microstimulation

Evolution, biomechanics, and neurobiology converge to explain selective finger motor control

Humans use their fingers to perform a variety of tasks, from simple grasping to manipulating objects, to typing and playing musical instruments, a variety wider than any other species. The more sophisticated the task, the more it involves individuated finger movements, those in which one or more selected fingers perform an intended action while the motion of other digits is constrained. Here we review the neurobiology of such individuated finger movements. We consider their evolutionary origins, the extent to which finger movements are in fact individuated, and the evolved features of neuromuscular control that both enable and limit individuation. We go on to discuss other features of motor control that combine with individuation to create dexterity, the impairment of individuation by disease, and the broad extent of capabilities that individuation confers on humans. We comment on the challenges facing the development of a truly dexterous bionic hand. We conclude by identifying topics for future investigation that will advance our understanding of how neural networks interact across multiple regions of the central nervous system to create individuated movements for the skills humans use to express their cognitive activity.

Effects of Daily Hand Activities on Age-Related Declines of Dynamic Motor Function in Individual Fingers

The present study examined the effects of daily activities of the hands on finger motor function in older adults. Maximum tapping frequency with each finger during single-finger tapping and alternate movements of index-middle, middle-ring, and ring-little finger pairs during double-finger tapping were compared between older adults who used their hands actively in their daily lives and those who did not. The active participants had significantly faster tapping rates for the ring finger in the single-finger tapping and the middle-ring finger pair in the double-finger tapping than did the inactive participants. Thus, daily activity of the hands in older adults could be effective at preventing the loss of dynamic motor function in individual fingers, especially with greater difficulty in movement, resulting from the degeneration with age.

The Effect of ICA and Non-negative Matrix Factorization Analysis for EMG Signals Recorded From Multi-Channel EMG Sensors

Surface electromyography (EMG) measurements are affected by various noises such as power source and movement artifacts and adjacent muscle activities. Hardware solutions have been found that use multi-channel EMG signal to attenuate noise signals related to sensor positions. However, studies addressing the overcoming of crosstalk from EMG and the division of overlaid superficial and deep muscles are scarce. In this study, two signal decompositions-independent component analysis and non-negative matrix factorization-were used to create a low-dimensional input signal that divides noise, surface muscles, and deep muscles and utilizes them for movement classification based on direction. In the case of index finger movement, it was confirmed that the proposed decomposition method improved the classification performance with the least input dimensions. These results suggest a new method to analyze more dexterous movements of the hand by separating superficial and deep muscles in the future using multi-channel EMG signals.

A Study of Personal Recognition Method Based on EMG Signal

With the increasing development of internet, the security of personal information becomes more and more important. Thus, variety of personal recognition methods have been introduced to ensure persons' information security. Traditional recognition methods such as Personal Identification Number (PIN), or Identification tag (ID) are vulnerable to hackers. Then the biometric technology, which uses the unique physiological characteristics of human body to identify user information has been proposed. But the biometrics widely used at present such as human face, fingerprint, iris, and voice can also be forged and falsified. The biometric with living body features such as electromyography (EMG) signal is a good method to achieve aliveness detection and prevent the spoofing attacks. However, there are few studies on personal recognition based on EMG signal. According to the application context, personal recognition system may operate either in identification mode or verification mode. In the personal identification mode, the system recognizes an individual by searching the templates of all the users in the database for a match. While in the personal verification mode, the system validates a person's identity by comparing the captured features with her or his own template(s) stored in the system database. In this paper, both EMG-based personal identification method and EMG-based personal verification method are investigated. First, the Myo armband is placed on the right forearm (specifically, the height of the radiohumeral joint) of 21 subjects to collect the surface EMG signal under hand-open gesture. Then, two different methods are proposed for EMG-based personal identification, i.e., personal identification method based on Discrete Wavelet Transform (DWT) and ExtraTreesClassifier, and personal identification method based on Continuous Wavelet Transform (CWT) and Convolutional Neural Networks (CNN). Experiments with 21 subjects show that the identification accuracy of this two methods can achieve 99.206% and 99.203% respectively. Then based on the identification method using CWT and CNN, transfer learning algorithm is adopted to solve the model update problem when new data is added. Finally, an EMG-based personal verification method using CWT and siamese networks is proposed. Experiments show that the verification accuracy of this method can achieve 99.285%.

Temporal and Force Characteristics of Rapid Single-Finger Tapping in Healthy Older Adults

The purpose of this study was to examine finger motor function in terms of temporal and force characteristics during rapid single-finger tapping in older adults. Ten older and 10 young males performed maximum frequency tapping by the index, middle, ring, or little finger. Nontapping fingers were maintained in contact with designated keys during tasks. Key-contact force for each of the fingers was monitored using four force transducers. The older subjects had slower tapping rates of all fingers during single-finger tapping than the young subjects. The average forces exerted by the nontapping fingers were larger for the older subjects than for the young subjects during tapping with the ring and little fingers. The ranges of the nontapping finger forces were larger for the older subjects during tapping by the middle, ring, and little fingers than for the young subjects. Thus, the motor abilities of the fingers evaluated by rapid single-finger tapping decline in older adults compared with young adults in terms of both movement speed and finger independence.

Extracting and Classifying Spatial Muscle Activation Patterns in Forearm Flexor Muscles Using High-Density Electromyogram Recordings

The human hand is capable of producing versatile yet precise movements largely owing to the complex neuromuscular systems that control our finger movement. This study seeks to quantify the spatial activation patterns of the forearm flexor muscles during individualized finger flexions. High-density (HD) surface electromyogram (sEMG) signals of forearm flexor muscles were obtained, and individual motor units were decomposed from the sEMG. Both macro-level spatial patterns of EMG activity and micro-level motor unit distributions were used to systematically characterize the forearm flexor activation patterns. Different features capturing the spatial patterns were extracted, and the unique patterns of forearm flexor activation were then quantified using pattern recognition approaches. We found that the forearm flexor spatial activation during the ring finger flexion was mostly distinct from other fingers, whereas the activation patterns of the middle finger were least distinguishable. However, all the different activation patterns can still be classified in high accuracy (94–100%) using pattern recognition. Our findings indicate that the partial overlapping of neural activation can limit accurate identification of specific finger movement based on limited recordings and sEMG features, and that HD sEMG recordings capturing detailed spatial activation patterns at both macro- and micro-levels are needed.

Robust estimation of average twitch contraction forces of populations of motor units in humans

The characteristics of motor unit force twitch profiles provide important information for the understanding of the muscle force generation. The twitch force is commonly estimated with the spike-triggered averaging technique, which, despite the many limitations, has been important for clarifying central issues in force generation. In this study, we propose a new technique for the estimation of the average twitch profile of populations of motor units with uniform contractile properties. The method encompasses a model-based deconvolution of the force signal using the identified discharge times of a population of motor units. The proposed technique was validated using simulations and tested on signals recorded during voluntary activation. The results of the simulations showed that the proposed method provides accurate estimates (relative error <25%) of the main parameters of the average twitch force when the number of identified motor units is between 5% and 15% of the total number of active motor units. It is discussed that current detection and decomposition methods of multi-channel surface EMG signals allow decoding this relative sample of the active motor unit pool. However, even when this condition is not met, our results show that the estimates provided by the new method are anyway always superior to those obtained by the spike triggered average approach, especially for high motor unit synchronization levels and when a relatively small number of triggers is available. In conclusion, we present a new method that overcome the main limitations of the spike-triggered average for the study of contractile properties of individual motor units. The method provides a new reliable tool for the investigation of the determinants of muscle force.

Extracting extensor digitorum communis activation patterns using high-density surface electromyography

The extensor digitorum communis muscle plays an important role in hand dexterity during object manipulations. This multi-tendinous muscle is believed to be controlled through separate motoneuron pools, thereby forming different compartments that control individual digits. However, due to the complex anatomical variations across individuals and the flexibility of neural control strategies, the spatial activation patterns of the extensor digitorum communis compartments during individual finger extension have not been fully tracked under different task conditions. The objective of this study was to quantify the global spatial activation patterns of the extensor digitorum communis using high-density (7 × 9) surface electromyogram (EMG) recordings. The muscle activation map (based on the root mean square of the EMG) was constructed when subjects performed individual four finger extensions at the metacarpophalangeal joint, at different effort levels and under different finger constraints (static and dynamic). Our results revealed distinct activation patterns during individual finger extensions, especially between index and middle finger extensions, although the activation between ring and little finger extensions showed strong covariance. The activation map was relatively consistent at different muscle contraction levels and for different finger constraint conditions. We also found that distinct activation patterns were more discernible in the proximal–distal direction than in the radial–ulnar direction. The global spatial activation map utilizing surface grid EMG of the extensor digitorum communis muscle provides information for localizing individual compartments of the extensor muscle during finger extensions. This is of potential value for identifying more selective control input for assistive devices. Such information can also provide a basis for understanding hand impairment in individuals with neural disorders.

Quantifying forearm muscle activity during wrist and finger movements by means of multi-channel electromyography

The study of hand and finger movement is an important topic with applications in prosthetics, rehabilitation, and ergonomics. Surface electromyography (sEMG) is the gold standard for the analysis of muscle activation. Previous studies investigated the optimal electrode number and positioning on the forearm to obtain information representative of muscle activation and robust to movements. However, the sEMG spatial distribution on the forearm during hand and finger movements and its changes due to different hand positions has never been quantified. The aim of this work is to quantify 1) the spatial localization of surface EMG activity of distinct forearm muscles during dynamic free movements of wrist and single fingers and 2) the effect of hand position on sEMG activity distribution. The subjects performed cyclic dynamic tasks involving the wrist and the fingers. The wrist tasks and the hand opening/closing task were performed with the hand in prone and neutral positions. A sensorized glove was used for kinematics recording. sEMG signals were acquired from the forearm muscles using a grid of 112 electrodes integrated into a stretchable textile sleeve. The areas of sEMG activity have been identified by a segmentation technique after a data dimensionality reduction step based on Non Negative Matrix Factorization applied to the EMG envelopes. The results show that 1) it is possible to identify distinct areas of sEMG activity on the forearm for different fingers; 2) hand position influences sEMG activity level and spatial distribution. This work gives new quantitative information about sEMG activity distribution on the forearm in healthy subjects and provides a basis for future works on the identification of optimal electrode configuration for sEMG based control of prostheses, exoskeletons, or orthoses. An example of use of this information for the optimization of the detection system for the estimation of joint kinematics from sEMG is reported.

Extrinsic finger and thumb muscles command a virtual hand to allow individual finger and grasp control

Fine-wire intramuscular electrodes were used to obtain electromyogram (EMG) signals from six extrinsic hand muscles associated with the thumb, index, and middle fingers. Subjects' EMG activity was used to control a virtual three-degree-of-freedom (DOF) hand as they conformed the hand to a sequence of hand postures testing two controllers: direct EMG control and pattern recognition control. Subjects tested two conditions using each controller: starting the hand from a predefined neutral posture before each new posture and starting the hand from the previous posture in the sequence. Subjects demonstrated their abilities to simultaneously, yet individually, move all three DOFs during the direct EMG control trials; however, results showed subjects did not often utilize this feature. Performance metrics such as failure rate and completion time showed no significant difference between the two controllers.

Limitations of the spike-triggered averaging for estimating motor unit twitch force: a theoretical analysis

Contractile properties of human motor units provide information on the force capacity and fatigability of muscles. The spike-triggered averaging technique (STA) is a conventional method used to estimate the twitch waveform of single motor units in vivo by averaging the joint force signal. Several limitations of this technique have been previously discussed in an empirical way, using simulated and experimental data. In this study, we provide a theoretical analysis of this technique in the frequency domain and describe its intrinsic limitations. By analyzing the analytical expression of STA, first we show that a certain degree of correlation between the motor unit activities prevents an accurate estimation of the twitch force, even from relatively long recordings. Second, we show that the quality of the twitch estimates by STA is highly related to the relative variability of the inter-spike intervals of motor unit action potentials. Interestingly, if this variability is extremely high, correct estimates could be obtained even for high discharge rates. However, for physiological inter-spike interval variability and discharge rate, the technique performs with relatively low estimation accuracy and high estimation variance. Finally, we show that the selection of the triggers that are most distant from the previous and next, which is often suggested, is not an effective way for improving STA estimates and in some cases can even be detrimental. These results show the intrinsic limitations of the STA technique and provide a theoretical framework for the design of new methods for the measurement of motor unit force twitch.

Motor unit

Movement is accomplished by the controlled activation of motor unit populations. Our understanding of motor unit physiology has been derived from experimental work on the properties of single motor units and from computational studies that have integrated the experimental observations into the function of motor unit populations. The article provides brief descriptions of motor unit anatomy and muscle unit properties, with more substantial reviews of motoneuron properties, motor unit recruitment and rate modulation when humans perform voluntary contractions, and the function of an entire motor unit pool. The article emphasizes the advances in knowledge on the cellular and molecular mechanisms underlying the neuromodulation of motoneuron activity and attempts to explain the discharge characteristics of human motor units in terms of these principles. A major finding from this work has been the critical role of descending pathways from the brainstem in modulating the properties and activity of spinal motoneurons. Progress has been substantial, but significant gaps in knowledge remain.

Activation of individual extrinsic thumb muscles and compartments of extrinsic finger muscles

Mechanical and neurological couplings exist between musculotendon units of the human hand and digits. Studies have begun to understand how these muscles interact when accomplishing everyday tasks, but there are still unanswered questions regarding the control limitations of individual muscles. Using intramuscular electromyographic (EMG) electrodes, this study examined subjects' ability to individually initiate and sustain three levels of normalized muscular activity in the index and middle finger muscle compartments of extensor digitorum communis (EDC), flexor digitorum profundus (FDP), and flexor digitorum superficialis (FDS), as well as the extrinsic thumb muscles abductor pollicis longus (APL), extensor pollicis brevis (EPB), extensor pollicis longus (EPL), and flexor pollicis longus (FPL). The index and middle finger compartments each sustained activations with significantly different levels of coactivity from the other finger muscle compartments. The middle finger compartment of EDC was the exception. Only two extrinsic thumb muscles, EPL and FPL, were capable of sustaining individual activations from the other thumb muscles, at all tested activity levels. Activation of APL was achieved at 20 and 30% MVC activity levels with significantly different levels of coactivity. Activation of EPB elicited coactivity levels from EPL and APL that were not significantly different. These results suggest that most finger muscle compartments receive unique motor commands, but of the four thumb muscles, only EPL and FPL were capable of individually activating. This work is encouraging for the neural control of prosthetic limbs because these muscles and compartments may potentially serve as additional user inputs to command prostheses.

Independence and control of the fingers depend on direction and contraction mode

Both biomechanical and neural factors are suggested to contribute to the limited independence of finger movement and involuntary force production. The purpose of this study was to evaluate finger independence by examining the activity of the four compartments of extensor digitorum (ED) and flexor digitorum superficialis (FDS) and involuntary force production in the non-task fingers using the "enslaving effect" (EE). Twelve male participants performed a series of 5s sub-maximal exertions at 5%, 25%, 50% and 75% of maximum using isometric isotonic and ramp flexion and extension exertions. Ramp exertions were performed from 0% to 85% of each finger's maximum force with ascending and descending phases taking 4.5s. EE was lower in flexion exertions likely due to the higher activity of the antagonist ED compartments counterbalancing the involuntary activation of the non-task FDS compartments. Minimal FDS activity was seen during extension exertions. At forces up to and including 50%, both EE and muscle activity of the non-task compartments were significantly higher in descending exertions than isotonic or ascending exertions. Up to mid-level forces, both finger proximity and contraction mode affect involuntary force production and muscle activation while only finger proximity contributed to finger independence at higher forces.

IMPACT OF FINGERTIP ACTIONS ON TOTAL POWER OF SURFACE ELECTROMYOGRAPHY FROM EXTRINSIC HAND MUSCLES

Quantizing the relationship between finger force and multitendoned extrinsic hand muscles could be useful for understanding the control strategies that underlie the coordination of finger movements and forces. The objective of this study is to explore the relationship of fingertip force production and total power of surface electromyography (sEMG) recorded on extrinsic hand muscles under isometric voluntary contraction. Thirteen healthy volunteers were recruited to participate in this study. In the designed force-tracking tasks, all volunteers were required to produce a certain force with either index finger or middle finger to match the target force for 5 s. Meanwhile, the sEMG signals were acquired from two extrinsic hand muscles: extensor digitorum (ED) and flexor digitorum superficialis (FDS). For each trial, sEMG of the effective force segment was extracted; then, the power spectrum was estimated based on autoregressive (AR) model and from which the corresponding total power of sEMG was computed. The experimental results reveal that the total power of sEMG linearly increases with force level regardless of the task finger and extrinsic hand muscle. It is also found that the total power obtained from index finger is significantly less than that of middle finger for FDS at the same force level (p < 0.05), while this kind of statistical significance cannot be found for ED. However, with respect to the measurement of total power, the type of extrinsic hand muscle has not exhibited significantly different contribution to the task finger under a certain fingertip force level. The findings of this study indicate that the total power of the extrinsic hand muscle's sEMG can be used to characterize finger's activities.

Mechanical properties and neural control of human hand motor units

Motor units serve both as the mechanical apparatus and the final stage of neural processing through which motor behaviours are enacted. Therefore, knowledge about the contractile properties and organization of the neural inputs to motor units supplying finger muscles is essential for understanding the control strategies underlying the diverse motor functions of the human hand. In this brief review, basic contractile properties of motor units residing in human hand muscles are described. Hand motor units are not readily categorized into the classical physiological types as established in the cat gastrocnemius muscle. In addition, the distribution of descending synaptic inputs to motor nuclei supplying different hand muscles is outlined. Motor neurons innervating intrinsic muscles appear to have relatively independent lines of input from supraspinal centres whereas substantial divergence of descending input is seen across motor nuclei supplying extrinsic hand muscles. The functional significance of such differential organizations of descending inputs for the control of hand movements is discussed.

Constraints for control of the human hand

More than 30 muscles drive the hand to perform a multitude of essential dextrous tasks. Here we consider new views on the evolution of hand structure and on peripheral and central constraints for independent control of the digits of the hand. The human hand is widely assumed to have evolved from hands like those of African apes, yet recent studies have shown that our hands and those of the earliest hominids are very similar and unlike those of living apes. Understanding the limits of hand function may come from investigation of our last common ancestor with the great apes, rather than the great apes themselves. In the periphery, movement across the full range of joint space can be limited by mechanical linkages among the extrinsic muscles. Further, peripheral limits occur when the hand adopts some positions in which the contraction of muscles fails to move the joints on which they usually act; there is muscle 'disengagement' and functional paralysis for some actions. Surprisingly, the central nervous system drives the hand seamlessly through this landscape of mechanical limits. Central constraints on control of the individual digits include the spillover of neural drive to neighbouring muscles and their 'compartments', and the inability to make maximal muscle forces when multiple digits contract strongly which produces a force deficit. The pattern of these latter constraints correlates with amounts of daily use of each digit and favours enslaved extension to lift fingers from an object but selective flexion of fingers to contact it.

Diminished capacity to modulate motor activation patterns according to task contributes to thumb deficits following stroke

The objective of this study was to explore motor impairment of the thumb following stroke. More specifically, we quantitatively examined kinetic deficits of the thumb. We anticipated that force deficits would be nonuniformly distributed across the kinetic workspace, due in part to varying levels of difficulty in altering the motor activation pattern to meet the task. Eighteen stroke survivors with chronic hemiparesis participated in the trials, along with nine age-matched controls. Of the stroke-survivor group, nine subjects had moderate hand impairment, and the other nine subjects had severe hand impairment. Subjects were instructed to generate maximal isometric thumb-tip force, as measured with a load cell, in each of six orthogonal directions with respect to the thumb tip. Activity of three representative thumb muscles was monitored through intramuscular and surface electrodes. Univariate split-plot analysis of variance revealed that clinical impairment level had a significant effect on measured force (P < 0.001), with the severely impaired group producing only 13% of the control forces, and the moderately impaired group generating 32% of control forces, on average. Weakness in the moderately impaired group exhibited a dependence on force direction (P = 0.015), with the least-relative weakness in the medial direction. Electromyographic recordings revealed that stroke survivors exhibited limited modulation of thumb-muscle activity with intended force direction. The difference in activation presented by the control group for a given muscle was equal to 40% of its full activation range across force directions, whereas this difference was only 26% for the moderately impaired group and 15% for the severely impaired group. This diminished ability to modify voluntary activation patterns, which we observed previously in index-finger muscles as well, appears to be a primary factor in hand impairment following stroke.

Changes in spatial distribution of flexor digitorum superficialis muscle activity is correlated to finger's action

Multitendoned extrinsic muscles of the human hand can be divided into several neuromuscular compartments (NMCs), each of which contributes to the ability of human finger to produce independent finger movements or force. The aim of this study was to investigate the changes in the spatial activation of flexor digitorum superficialis (FDS) during the fingertip force production with non-invasive multichannel surface electromyography (sEMG) technique. 7 healthy Subjects were instructed to match the target force level for 5s using individual index finger (I), individual middle finger (M) and the combination of the index and middle finger (IM) respectively. Simultaneously, a 2 × 6 electrode array was employed to record multichannel sEMG from FDS as finger force was produced. The entropy and center of gravity of the sEMG root mean square (RMS) map were computed to assess the spatial inhomogeneity in muscle activation and the change in spatial distribution of EMG amplitude related to the force generation of specific task finger. The results showed that the area and intensity of high amplitude region increased with force production, and the entropy increased with force level under the same task finger. The findings indicate that the change of spatial distribution of multitendoned extrinsic hand muscle activation is correlated to specific biomechanical functions.

Multi-finger interaction during involuntary and voluntary single finger force changes

Two types of finger interaction are characterized by positive co-variation (enslaving) or negative co-variation (error compensation) of finger forces. Enslaving reflects mechanical and neural connections among fingers, while error compensation results from synergic control of fingers to stabilize their net output. Involuntary and voluntary force changes by a finger were used to explore these patterns. We hypothesized that synergic mechanisms will dominate during involuntary force changes, while enslaving will dominate during voluntary finger force changes. Subjects pressed with all four fingers to match a target force that was 10% of their maximum voluntary contraction (MVC). One of the fingers was unexpectedly raised 5.0 mm at a speed of 30.0 mm/s. During finger raising the subject was instructed "not to intervene voluntarily". After the finger was passively lifted and a new steady-state achieved, subjects pressed down with the lifted finger, producing a pulse of force voluntarily. The data were analyzed in terms of finger forces and finger modes (hypothetical commands to fingers reflecting their intended involvement). The target finger showed an increase in force during both phases. In the involuntary phase, the target finger force changes ranged between 10.71 ± 1.89% MVC (I-finger) and 16.60 ± 2.26% MVC (L-finger). Generally, non-target fingers displayed a force decrease with a maximum amplitude of -1.49 ± 0.43% MVC (L-finger). Thus, during the involuntary phase, error compensation was observed--non-lifted fingers showed a decrease in force (as well as in mode magnitude). During the voluntary phase, enslaving was observed--non-target fingers showed an increase in force and only minor changes in mode magnitude. The average change in force of non-target fingers ranged from 21.83 ± 4.47% MVC for R-finger (M-finger task) to 0.71 ± 1.10% MVC for L-finger (I-finger task). The average change in mode of non-target fingers was between -7.34 ± 19.27% MVC for R-finger (L-finger task) and 7.10 ± 1.38% MVC for M-finger (I-finger task). We discuss a range of factors affecting force changes, from purely mechanical effects of finger passive lifting to neural synergic adjustments of commands to individual fingers. The data fit a recently suggested scheme that merges the equilibrium-point hypothesis (control with referent configurations) with the idea of hierarchical synergic control of multi-element systems.

Finger tapping ability in healthy elderly and young adults

PURPOSE

The maximum isometric force production capacity of the fingers decreases with age. However, little information is available on age-related changes in dynamic motor capacity of individual fingers. The purpose of this study was to compare the dynamic motor function of individual fingers between elderly and young adults using rapid single-finger and double-finger tapping.

METHODS

Fourteen elderly and 14 young adults performed maximum frequency tapping by the index, middle, ring, or little finger (single-finger tapping) and with alternate movements of the index-middle, middle-ring, or ring-little finger-pair (double-finger tapping). The maximum pinch force between the thumb and each finger, tactile sensitivity of each fingertip, and time taken to complete a pegboard test were also measured.

RESULTS

Compared with young subjects, the older subjects had significantly slower tapping rates in all fingers and finger-pairs in the tapping tasks. The age-related decline was also observed in the tactile sensitivities of all fingers and in the pegboard test. However, there was no group difference in the pinch force of any finger. The tapping rate of each finger did not correlate with the pinch force or tactile sensitivity for the corresponding finger in the elderly subjects.

CONCLUSIONS

Maximum rate of finger tapping was lower in the elderly adults compared with the young adults. The decline of finger tapping ability in elderly adults seems to be less affected by their maximum force production capacities of the fingers as well as tactile sensitivities at the tips of the fingers.

Extraction of individual muscle mechanical action from endpoint force

Most motor tasks require the simultaneous coordination of multiple muscles. That coordination is poorly understood in part because there is no noninvasive means of isolating a single muscle's contribution to the resultant endpoint force. The contribution of a single motor unit to isometric tasks can, however, be characterized using the spike-triggered averaging (STA) technique, applied to a single motor unit's spike train. We propose that a technique analogous to STA, which we call electromyogram (EMG)-weighted averaging (EWA), can be applied to surface EMGs to extract muscle mechanical action from the natural endpoint force fluctuations generated during steady isometric contraction. We demonstrate this technique on simultaneous recordings of fingertip force and surface EMG from the first dorsal interosseous (FDI) and extensor indicis (EI) of humans. The EWA direction was approximately the same across a wide range of fingertip force directions, and the average EWA direction was consistent with mechanical action direction of these muscles estimated from cadaveric and imaging data: the EWA directions were 193 +/- 2 degrees for the FDI and 71 +/- 5 degrees for the EI (95% confidence). EWA transient behavior also appears to capture temporal characteristics of muscle force fluctuations with peak force time and general waveform shape similar to that of the associated spike-triggered averages from single motor units. The EWA may provide a means of empirically characterizing the complex transformation between muscle force and endpoint force without the need for invasive electrode recordings or complex anatomical measurements of musculoskeletal geometry.

Limits to the Control of the Human Thumb and Fingers in Flexion and Extension

In humans, hand performance has evolved from a crude multidigit grasp to skilled individuated finger movements. However, control of the fingers is not completely independent. Although musculotendinous factors can limit independent movements, constraints in supraspinal control are more important. Most previous studies examined either flexion or extension of the digits. We studied differences in voluntary force production by the five digits, in both flexion and extension tasks. Eleven healthy subjects were instructed either to maximally flex or extend their digits, in all single- and multidigit combinations. They received visual feedback of total force produced by “instructed” digits and had to ignore “noninstructed” digits. Despite attempts to maximally flex or extend instructed digits, subjects rarely generated their “maximal” force, resulting in a “force deficit,” and produced forces with noninstructed digits (“enslavement”). Subjects performed differently in flexion and extension tasks. Enslavement was greater in extension than in flexion tasks ( P = 0.019), whereas the force deficit in multidigit tasks was smaller in extension ( P = 0.035). The difference between flexion and extension in the relationships between the enslavement and force deficit suggests a difference in balance of spillover of neural drive to agonists acting on neighboring digits and focal neural drive to antagonist muscles. An increase in drive to antagonists would lead to more individualized movements. The pattern of force production matches the daily use of the digits. These results reveal a neural control system that preferentially lifts fingers together by extension but allows an individual digit to flex so that the finger pads can explore and grasp.

Limited ability to extend the digits of the human hand independently with extensor digitorum

While the human hand has an extraordinary capacity to manipulate objects, movement of its digits is usually not completely independent. These limits have been documented for extrinsic flexor muscles, although hand skills also require selectivity for extension movements. Hence, we measured the degree of independent control of the major extrinsic extensor (extensor digitorum, ED). Subjects grasped a cylinder, with the thumb perpendicular to the fingers. Load cells were connected to the proximal phalanges of the fingers and the thumb's distal phalanx. Intramuscular recordings using needle electrodes were made from the individual digital compartments of ED. Subjects were instructed to extend each digit isometrically in a voluntary ramp contraction to 50% maximal force. In total, the behaviour of 283 single motor units was analysed. More than half of the units associated with one 'test' finger were recruited inadvertently when another digit contracted to 50% maximum, with most units being recruited by extension of the adjacent digits. Usually, test motor units were recruited at higher forces by extension of fingers further from the test finger. Unexpectedly, extension of the thumb recruited many motor units acting on the little finger. Across tasks, at recruitment of the test motor units, the force produced by the test finger often differed between the voluntary and inadvertent contractions. Overall, the independent control of the output of ED is limited; this may reflect 'spill-over' of motor commands to other digital extensor compartments. This level of control of the extrinsic extensor muscles is more independent than the control of the deep extrinsic flexor muscle but less independent than that of the superficial extrinsic flexor muscle.

Assessment of individual finger muscle activity in the extensor digitorum communis by surface EMG

The extensor digitorum communis (ED) is a slender muscle group in the dorsal forearm from which tendons arise to the index (D2), medius (D3), ring (D4), and little (D5) fingers. Limited independence has been attributed to the parts that actuate the individual fingers. However, in a detailed anatomical analysis, it was found that the ED parts to the different fingers have constant and widely spaced anatomical locations that promote independent function. These observations and the superficial muscle belly locations prompted the hypothesis that these ED parts would be individually assessable by small anatomically placed surface EMG electrodes. In the present study, this hypothesis was evaluated by measuring electromyography (EMG) from the ED parts and surrounding muscles during individual finger tapping tasks with the forearm resting on a flat surface. It was found that individual ED activity can be well measured in ED2, ED3, ED4, and extensor digiti minimi (EDM). ED3 did not give nor did its electrodes receive significant crosstalk from other ED parts. ED4 electrodes recorded an EMG level of 30 +/- 19% (mean +/- SD) ED2 EMG in D2 tapping and ED2 electrodes a level of 53 +/- 22% ED4 EMG in D4 tapping, by hypothesis mostly crosstalk. EDM electrodes may record EMG at the level of ED4 EMG in D4 tapping. In D2 tapping, the mutual ED2 and extensor indicis redundancy reflected in large intersubject EMG differences with sometimes one or the other almost silent. The results may expand the possibilities of EMG analysis and finger muscle electrostimulation in ergonomic and clinical applications.

Anatomic basis for individuated surface EMG and homogeneous electrostimulation with neuroprostheses of the extensor digitorum communis

The extensor digitorum communis (ED) is generally regarded as a fairly undiversified muscle that gives extensor tendons to all fingers. Some fine wire electromyographic (EMG) investigations have been carried out to study individuation of the muscle parts to the different fingers. However, individuated surface EMG of the ED has not been investigated. This study analyses the anatomy of the ED muscle parts to the different fingers in detail and proposes optimal locations for surface or indwelling electrodes for individuated EMG and for electrostimulation with neuroprostheses. The dissections show that the ED arises from extensive origin tendons (OT), which originate at the lateral epicondyle and reach far in the forearm. The ED OT is V-shaped with shorter central tendon fibers but with a long radial and an even longer ulnar slip. The ED parts to the individual fingers consistently arise from distinct OT locations: the ED3 (medius) arises proximally, the ED2 (index) from the radial slip distal to ED3, the ED4 (ring finger) from the ulnar slip distal to ED3, and the ED5 (to ring/little finger) from the ulnar slip distal to ED4. This lengthwise widely spaced arrangement of ED parts compensates to some degree for the narrow ED width and suggests that ED parts should be individually assessable by indwelling and even by surface EMG electrodes, albeit in the latter case with variable mutual cross-talk. Conversely, the anatomic spacing of ED parts warrants that electromyographic stimulation with neuroprostheses by a single implanted electrode cannot likely homogeneously activate all ED parts.

Alternative computer mouse design and testing to reduce finger extensor muscle activity during mouse use

OBJECTIVE

The purpose of this study was to design and test alternative computer mouse designs that attempted to reduce extensor muscle loading of the index and middle fingers by altering the orientation of the button switch direction and the force of the switch.

BACKGROUND

Computer users of two-button mouse designs exhibit sustained lifted finger behaviors above the buttons, which may contribute to hand and forearm musculoskeletal pain associated with intensive mouse use.

METHODS

In a repeated-measures laboratory experiment, 20 participants completed point-and-click, steering, and drag tasks with four alternative mouse designs and a reference mouse. Intramuscular and surface electromyography (EMG) measured muscle loading, and movement times recorded by software provided a measure of performance.

RESULTS

Changing the direction of the switch from a conventional downward to a forward design reduced (up to 2.5% maximum voluntary contraction [MVC]) sustained muscle activity (10th percentile EMG amplitude distribution) in the finger extensors but increased (up to 0.6% MVC) flexor EMG and increased movement times (up to 31%) compared with the reference mouse (p < .001). Implementing a high switch force design also increased flexor EMG but did not differ in movement times compared with the reference mouse (p < .001).

CONCLUSION

The alternative mouse designs with altered switch direction reduced sustained extensor muscle loading; however, trade-offs with higher flexor muscle loading and lower performance existed.

APPLICATION

Potential applications of this study include ergonomic and human computer interface design strategies in reducing the exposure to risk factors that may lead to upper extremity musculoskeletal disorders.

Analysis of the effects of firing rate and synchronization on spike-triggered averaging of multidirectional motor unit torque

Spike-triggered averaging (STA) of muscle force transients has often been used to estimate motor unit contractile properties, using the discharge of a motor unit within the muscle as the triggering events. For motor units that exert torque about multiple degrees-of-freedom, STA has also been used to estimate motor unit pulling direction. It is well known that motor unit firing rate and weak synchronization of motor unit discharges with other motor units in the muscle can distort STA estimates of contractile properties, but the distortion of STA estimates of motor unit pulling direction has not been thoroughly evaluated. Here, we derive exact equations that predict that STA decouples firing rate and synchronization distortion when used to estimate motor unit pulling direction. We derive a framework for analyzing synchronization, consider whether the distortion due to synchronization can be removed from STA estimates of pulling direction, and show that there are distributions of motor unit pulling directions for which STA is insensitive to synchronization. We conclude that STA may give insight into how motoneuronal synchronization is organized with respect to motor unit pulling direction.

Selective Inhibition of Movement

In studies of volitional inhibition, successful task performance usually requires the prevention of all movement. In reality, movements are selectively prevented in the presence of global motor output. The aim of this study was to investigate the ability to prevent one movement while concurrently executing another, referred to as selective inhibition. In two experiments, participants released switches with either their index and middle fingers (unimanual) or their left and right index fingers (bimanual) to stop two moving indicators at a fixed target (Go trials). Stop trials occurred when either one or both indicators automatically stopped before reaching the target, signaling that prevention of the prepared movement was required. Stop All and selective Stop trials were randomly interspersed among more frequently occurring Go trials. We found that selective inhibition is harder to perform than nonselective inhibition, for both unimanual and bimanual task contexts. During selective inhibition trials, lift time of the responding digit was delayed in both experiments by ≤100 ms, demonstrating the generality of the result. A nonselective neural inhibitory pathway may temporarily “brake” the required response, followed by selective excitation of the to-be-moved digit's cortical representation. After selective inhibition trials, there were persistent asynchronies between finger lift times of subsequent Go trials. The persistent effects reflect the behavioral consequences of nonspecific neural inhibition combined with selective neural disinhibition.

Motor-unit synchrony within and across compartments of the human flexor digitorum superficialis

An interesting feature of the muscular organization of the human hand is that the main flexors and extensors of the fingers are compartmentalized and give rise to multiple parallel tendons that insert onto all the fingers. Previous studies of motor-unit synchrony in extensor digitorum and flexor digitorum profundus indicated that synaptic input to motor neurons supplying these multitendoned muscles is not uniformly distributed across the entire pool of motor neurons but instead appears to be partially segregated to supply subsets of motor neurons that innervate different muscular compartments. Little is known, however, about the organization of the synaptic inputs to the motor neurons supplying another multitendoned finger muscle, the flexor digitorum superficialis (FDS). Therefore in this study, we estimated the extent of divergence of last-order inputs to FDS motor neurons by measuring the degree of short-term synchrony among motor units within and across compartments of FDS. The degree of synchrony for motor-unit pairs within the same digit compartment was nearly twofold that of pairs of motor units in adjacent compartments and more than fourfold that of pairs in nonadjacent compartments. Therefore like other multitendoned muscles of the hand, last-order synaptic inputs to motor neurons supplying the FDS appear to primarily supply subsets of motor neurons innervating specific finger compartments. Such an organization presumably enables differential activation of separate compartments to facilitate independent movements of the fingers.

Selective recruitment of single motor units in human flexor digitorum superficialis muscle during flexion of individual fingers

Flexor digitorum superficialis (FDS) is an extrinsic multi-tendoned muscle which flexes the proximal interphalangeal joints of the four fingers. It comprises four digital components, each with a tendon that inserts onto its corresponding finger. To determine the degree to which these digital components can be selectively recruited by volition, we recorded the activity of a single motor unit in one component via an intramuscular electrode while the subject isometrically flexed each of the remaining fingers, one at a time. The finger on which the unit principally acted was defined as the 'test finger' and that which flexed isometrically was the 'active' finger. Activity in 79 units was recorded. Isometric finger flexion forces of 50% maximum voluntary contraction (MVC) activated less than 50% of single units in components of FDS acting on fingers that were not voluntarily flexed. With two exceptions, the median recruitment threshold for all active-test finger combinations involving the index, middle, ring and little finger test units was between 49 and 60% MVC (60% MVC being the value assigned to those not recruited). The exceptions were flexion of the little finger while recording from ring finger units (median: 40% MVC), and vice versa (median: 2% MVC). For all active-test finger combinations, only 35/181 units were activated when the active finger flexed at less than 20% MVC, and the fingers were adjacent for 28 of these. Functionally, to recruit FDS units during grasping and lifting, relatively heavy objects were required, although systematic variation occurred with the width of the object. In conclusion, FDS components can be selectively activated by volition and this may be especially important for grasping at high forces with one or more fingers.

Simulations of motor unit number estimation techniques

Motor unit number estimation (MUNE) is an electrodiagnostic procedure used to evaluate the number of motor axons connected to a muscle. All MUNE techniques rely on assumptions that must be fulfilled to produce a valid estimate. As there is no gold standard to compare the MUNE techniques against, we have developed a model of the relevant neuromuscular physiology and have used this model to simulate various MUNE techniques. The model allows for a quantitative analysis of candidate MUNE techniques that will hopefully contribute to consensus regarding a standard procedure for performing MUNE.

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.

A comparison of muscular activity during single and double mouse clicks

Work-related musculoskeletal disorders (WMSDs) in the neck/shoulder region and the upper extremities are a common problem among computer workers. Occurrences of motor unit (MU) double discharges with very short inter-firing intervals (doublets) have been hypothesised as a potential additional risk for overuse of already exhausted fibres during long-term stereotyped activity. Doublets are reported to be present during double-click mouse work tasks. A few comparative studies have been carried out on overall muscle activities for short-term tasks with single types of actions, but none on occurrences of doublets during double versus single clicks. The main purpose of this study was to compare muscle activity levels of single and double mouse clicks during a long-term combined mouse/keyboard work task. Four muscles were studied: left and right upper trapezius, right extensor digitorum communis (EDC) and right flexor carpi ulnaris. Additionally, MU activity was analysed through intramuscular electromyography in the EDC muscle for a selection of subjects. The results indicate that double clicking produces neither higher median or 90th percentile levels in the trapezius and EDC muscles, nor a higher disposition for MU doublets, than does single clicking. Especially for the 90th percentile levels, the indications are rather the opposite (in the EDC significantly higher during single clicks in 8 of 11 subjects, P < 0.05). Although it cannot be concluded from the present study that double clicks are harmless, there were no signs that double clicks during computer work generally constitute a larger risk factor for WMSDs than do single clicks.

Intraneural microstimulation of motor axons in the study of human single motor units

Single motor unit activity has been studied in depth since the first intramuscular electrodes were developed more than 70 years ago. Many techniques have been combined or used in isolation since then. Intraneural motor axon microstimulation allows the detailed study of single motor units in awake human subjects in a manner most analogous to that used in reduced animal preparations. A microelectrode, inserted percutaneously into a peripheral nerve, stimulates the axon of a single alpha-motoneuron at a site remote from the contracting muscle, allowing detailed analyses of the contractile properties of a single motor unit in an otherwise quiescent muscle, that is, without interference of simultaneously active motor units or the presence of an electrode within the muscle. The methods and results obtained using this technique are described and compared to those of other studies of single motor units in human subjects. Differences have been found between human and animal motor units and between motor units of various muscles. Studying human and animal motor units using an analogous technique provides insight into the interpretation of human data when results differ from animal data, and when human motor units cannot be examined in the same way, or at a similar level of detail, as animal motor units.

The influence of contraction amplitude and firing history on spike-triggered averaged trapezius motor unit potentials

The spike-triggered averaged (STA) technique was used to examine trapezius motor unit potentials and their dependence on contraction amplitude and firing history. Individual motor unit firings were identified by a fine-wire intramuscular electrode, while STA-derived potentials were extracted from the simultaneously recorded surface electromyographic (SEMG) signal. Amplitude-controlled contractions and contractions with typing tasks and mental stress were carried out. STA potentials were mostly derived from 20 s intervals of firing. Motor unit synchrony was estimated by peristimulus time histograms (PSTHs). An association between SEMG amplitude and STA-derived motor unit potentials was found: motor unit area showed a four-fold increase when SEMG amplitude increased from 1.5 to 10.5% of the root mean square-detected SEMG signal at maximal voluntary contraction (%EMG(max)). Low- and higher threshold motor unit potentials, all with recruitment thresholds <10% EMG(max), had similar area at the same contraction amplitude. A significant increase in the STA-derived potentials was observed after 3 min of constant-amplitude contractions; however, this difference was reduced after 10 min and no longer present after 30 min of contraction. Motor unit synchrony accounted for, on average, 2.8% additional firings within 2 ms of the triggering motor unit. We conclude that the increase in STA-derived potentials with contraction amplitude is, to a major extent, due to motor unit synchrony, limiting the applicability of this method in postural muscles presenting wide motor unit potentials. The similar area of motor units at same SEMG amplitude may indicate that trapezius motor units recruited below 10% EMG(max) are of similar size and thus not organized according to the Henneman size principle.

Human finger independence: limitations due to passive mechanical coupling versus active neuromuscular control

We studied the extent to which mechanical coupling and neuromuscular control limit finger independence by studying passive and active individuated finger movements in healthy adults. For passive movements, subjects relaxed while each finger was rotated into flexion and extension by a custom-built device. For active movements, subjects moved each finger into flexion and extension while attempting to keep the other, noninstructed fingers still. Active movements were performed through approximately the same joint excursions and at approximately the same speeds as the passive movements. We quantified how mechanical coupling limited finger independence from the passive movements, and quantified how neuromuscular control limited finger independence using an analysis that subtracted the indices obtained in the passive condition from those obtained in the active condition. Finger independence was generally similar during passive and active movements, but showed a trend toward less independence in the middle, ring, and little fingers during active, large-arc movements. Mechanical coupling limited the independence of the index, middle, and ring fingers to the greatest degree, followed by the little finger, and placed only negligible limitations on the independence of the thumb. In contrast, neuromuscular control primarily limited the independence of the ring, and little fingers during large-arc movements, and had minimal effects on the other fingers, especially during small-arc movements. For the movement conditions tested here, mechanical coupling between the fingers appears to be a major factor limiting the complete independence of finger movement.

Short-term synchronization between motor units in different functional subdivisions of the human flexor digitorum profundus muscle

The ability to independently move the digits is limited by peripheral as well as central factors. A central limitation to independent finger movements might arise from the inability of the human nervous system to activate motor units (MUs) that exert force on one finger without also activating MUs that exert force on adjacent fingers. Short-term synchronization between MU pairs is thought to be the result of the two motoneurons receiving common input from last-order neuronal projections. The human flexor digitorum profundus (FDP) muscle contains four subdivisions, one for each of the fingers. We hypothesized that the distribution of MU synchrony within and between subdivisions of FDP might parallel the ability to selectively activate different functional subdivisions within FDP, and the ability to flex one digit independently of another. We found that the degree of MU synchrony indeed was not uniform among the different functional subdivisions of FDP; MUs acting on ulnar digits (d5, d4) were more synchronized than MUs acting on radial digits (d2, d3). Furthermore, synchrony was observed between MU pairs where each unit acted on a different digit and was highest when both units of a pair acted on the least-independent digits (d4, d5). This indicates that the CNS does not exert completely independent control over the different functional subdivisions of FDP. The strength of synchrony appears related to the inability to produce completely independent forces or movements with the digits. These observations reflect widespread divergence of last-order inputs within the FDP motoneuron pool, and we suggest that the organization of the CNS drive to this muscle contributes to the limited ability of humans to flex one digit in isolation from other digits.