Quantifying the independence of human finger movements: comparisons of digits, hands, and movement frequencies

Effect of Forearm Supination and Pronation on Median & Ulnar Nerve Conduction Velocity Among Throwers, Archers, and Non-Athletes

The distinct and specialized movements performed in different sports disciplines may significantly influence nerve performance, potentially affecting nerve responses and the overall function within the respective athletic activities. The purpose of this study is to find the effect of forearm supination and pronation across the elbow joint on ulnar and median nerve conduction velocity (NCV) in throwers, archers, and non-athletes. A total of 34 participants both male and females were recruited with a body mass index (BMI) between 18.5 and 24.9 kg/m2. Nerve conduction study (NeuroStim NS2 EMG/NCV/EP System) was used for measuring ulnar and median NCV across the elbow joint at different angles with the forearm in supination and pronation. Repeated measure analysis of variance (RMANOVA) revealed that there are statistically significant differences in mean values of forearm positions, angles, nerves and groups (p < .05). This study illuminates distinctive NCV variations across diverse athletic groups during forearm supination and pronation movements. Pronation consistently exhibited faster ulnar NCV compared to the median nerve across throwers, archers, and non-athletes, while in supination specific joint positions revealed notable differences within sports groups and nerve function.

3D Kinematics Quantifies Gait Response to Levodopa earlier and to a more Comprehensive Extent than the MDS-Unified Parkinson's Disease Rating Scale in Patients with Motor Complications

BACKGROUND

Quantitative 3D movement analysis using inertial measurement units (IMUs) allows for a more detailed characterization of motor patterns than clinical assessment alone. It is essential to discriminate between gait features that are responsive or unresponsive to current therapies to better understand the underlying pathophysiological basis and identify potential therapeutic strategies.

OBJECTIVES

This study aims to characterize the responsiveness and temporal evolution of different gait subcomponents in Parkinson's disease (PD) patients in their OFF and various ON states following levodopa administration, utilizing both wearable sensors and the gold-standard MDS-UPDRS motor part III.

METHODS

Seventeen PD patients were assessed while wearing a full-body set of 15 IMUs in their OFF state and at 20-minute intervals following the administration of a supra-threshold levodopa dose. Gait was reconstructed using a biomechanical model of the human body to quantify how each feature was modulated. Comparisons with non-PD control subjects were conducted in parallel.

RESULTS

Significant motor changes were observed in both the upper and lower limbs according to the MDS-UPDRS III, 40 minutes after levodopa intake. IMU-assisted 3D kinematics detected significant motor alterations as early as 20 minutes after levodopa administration, particularly in upper limbs metrics. Although all "pace-domain" gait features showed significant improvement in the Best-ON state, most rhythmicity, asymmetry, and variability features did not.

CONCLUSION

IMUs are capable of detecting motor alterations earlier and in a more comprehensive manner than the MDS-UPDRS III. The upper limbs respond more rapidly to levodopa, possibly reflecting distinct thresholds to levodopa across striatal regions.

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.

Descending motor command to prime mover of dependent finger induces tactile gating in target and distant non-target finger

This study examined whether tactile gating induced by the descending motor command to one finger spreads out to the other fingers to which the command is not delivered and whether this gating is dependent on the target finger to which the command is delivered. The change in perceptual threshold to the digital nerve stimulation of one finger induced by tonic contraction of the first dorsal interosseous or abductor digiti minimi muscle was examined. The perceptual threshold to the digital nerve stimulation of the thumb or little finger was increased by tonic contraction of the abductor digiti minimi muscle. This finding indicates that the descending motor command to the prime mover of the little finger abduction induces tactile gating not only in the finger to which the command is delivered but also in the other finger to which the command is not delivered. Tonic contraction of the first dorsal interosseous muscle did not change the perceptual threshold to the digital nerve stimulation in any finger. This finding means that tactile gating occurs particularly when the descending motor command is delivered to the dependent finger. Spreading out of tactile gating of one finger, to which the descending motor command is not delivered, is likely mediated by surround inhibition.

Post-Stroke Impairments of Manual Dexterity and Finger Proprioception: Their Contribution to Upper Limb Activity Capacity

BACKGROUND

Knowing how impaired manual dexterity and finger proprioception affect upper limb activity capacity is important for delineating targeted post-stroke interventions for upper limb recovery.

OBJECTIVES

To investigate whether impaired manual dexterity and finger proprioception explain variance in post-stroke activity capacity, and whether they explain more variance than conventional clinical assessments of upper limb sensorimotor impairments.

METHODS

Activity capacity and hand sensorimotor impairments were assessed using clinical measures in N = 42 late subacute/chronic hemiparetic stroke patients. Dexterity was evaluated using the Dextrain Manipulandum to quantify accuracy of visuomotor finger force-tracking (N = 36), timing of rhythmic tapping (N = 36), and finger individuation (N = 24), as well as proprioception (N = 27). Stepwise multivariate and hierarchical linear regression models were used to identify impairments best explaining activity capacity.

RESULTS

Dexterity and proprioceptive components significantly increased the variance explained in activity capacity: (i) Box and Block Test was best explained by baseline tonic force during force-tracking and tapping frequency (adjusted R2 = .51); (ii) Motor Activity Log was best explained by success rate in finger individuation (adjusted R2 = .46); (iii) Action Research Arm Test was best explained by release of finger force and proprioceptive measures (improved reaction time related to use of proprioception; adjusted R2 = .52); and (iv) Moberg Pick-Up test was best explained by proprioceptive function (adjusted R2 = .18). Models excluding dexterity and proprioception variables explained up to 19% less variance.

CONCLUSIONS

Manual dexterity and finger proprioception explain unique variance in activity capacity not captured by conventional impairment measures and should be assessed when considering the underlying causes of post-stroke activity capacity limitations.URL: https://www.clinicaltrials.gov. Unique identifier: NCT03934073.

The role of distinct ECoG frequency features in decoding finger movement

Objective.To identify the electrocorticography (ECoG) frequency features that encode distinct finger movement states during repeated finger flexions.Approach.We used the publicly available Stanford ECoG dataset of cue-based, repeated single finger flexions. Using linear regression, we identified the spectral features that contributed most to the encoding of movement dynamics and discriminating movement events from rest, and combined them to predict finger movement trajectories. Furthermore, we also looked into the effect of the used frequency range and the spatial distribution of the identified features.Main results.Two frequency features generate superior performance, each one for a different movement aspect: high gamma band activity distinguishes movement events from rest, whereas the local motor potential (LMP) codes for movement dynamics. Combining these two features in a finger movement decoder outperformed comparable prior work where the entire spectrum was used as the average correlation coefficient with the true trajectories increased from 0.45 to 0.5, both applied to the Stanford dataset, and erroneous predictions during rest were demoted. In addition, for the first time, our results show the influence of the upper cut-off frequency used to extract LMP, yielding a higher performance when this range is adjusted to the finger movement rate.Significance.This study shows the benefit of a detailed feature analysis prior to designing the finger movement decoder.

Decomposition and Reconstruction of Human Palm Movements

OBJECTIVE

The human hand is known to have excellent manipulation ability compared to other primate hands. Without the palm movements, the human hand would lose more than 40% of its functions. However, uncovering the constitution of palm movements is still a challenging problem involving kinesiology, physiology, and engineering science.

METHODS

By recording the palm joint angles during common grasping, gesturing, and manipulation tasks, we built a palm kinematic dataset. Then, a method for extracting the eigen-movements to characterize the common motion correlation relationships of palm joints was proposed to explore the palm movement constitution.

RESULTS

This study revealed a palm kinematic characteristic that we named the joint motion grouping coupling characteristic. During natural palm movements, there are several joint groups with a high degree of motor independence, while the movements of joints within each joint group are interdependent. Based on these characteristics, the palm movements can be decomposed into seven eigen-movements. The linear combinations of these eigen-movements can reconstruct more than 90% of palm movement ability. Moreover, combined with the palm musculoskeletal structures, we found that the revealed eigen-movements are associated with joint groups that are defined by muscular functions, which provided a meaningful context for palm movement decomposition.

CONCLUSION

This paper suggests that some invariable characteristics underlie the variable palm motor behaviors and can be used to simplify palm movement generation.

SIGNIFICANCE

This paper provides important insights into palm kinematics, and helps facilitate motor function assessment and the development of better artificial hands.

Random forest-based simultaneous and proportional myoelectric control system for finger movements

A classification scheme for myoelectric control systems (MCS) cannot mimic complex hand movements. This paper presents simultaneous and proportional MCS by estimating the angles of fourteen finger joints using time-domain feature extraction and random forest. The experimental results show that the best feature was the root mean square (RMS). Furthermore, the random forest attained an average coefficient of determination (R2) of 0.85 compared to other regressors which perform below 0.75. The ANOVA tests indicated that the performance of the proposed system was significantly different. Therefore, the proposed system will be the best option for real-time MCS applications in the future.

Loss of finger control complexity and intrusion of flexor biases are dissociable in finger individuation impairment after stroke

The ability to control each finger independently is an essential component of human hand dexterity. A common observation of hand function impairment after stroke is the loss of this finger individuation ability, often referred to as enslavement, i.e., the unwanted coactivation of non-intended fingers in individuated finger movements. In the previous literature, this impairment has been attributed to several factors, such as the loss of corticospinal drive, an intrusion of flexor synergy due to upregulations of the subcortical pathways, and/or biomechanical constraints. These factors may or may not be mutually exclusive and are often difficult to tease apart. It has also been suggested, based on a prevailing impression, that the intrusion of flexor synergy appears to be an exaggerated pattern of the involuntary coactivations of task-irrelevant fingers seen in a healthy hand, often referred to as a flexor bias. Most previous studies, however, were based on assessments of enslavement in a single dimension (i.e., finger flexion/extension) that coincide with the flexor bias, making it difficult to tease apart the other aforementioned factors. Here, we set out to closely examine the nature of individuated finger control and finger coactivation patterns in all dimensions. Using a novel measurement device and a 3D finger-individuation paradigm, we aim to tease apart the contributions of lower biomechanical, subcortical constraints, and top-down cortical control to these patterns in both healthy and stroke hands. For the first time, we assessed all five fingers' full capacity for individuation. Our results show that these patterns in the healthy and paretic hands present distinctly different shapes and magnitudes that are not influenced by biomechanical constraints. Those in the healthy hand presented larger angular distances that were dependent on top-down task goals, whereas those in the paretic hand presented larger Euclidean distances that arise from two dissociable factors: a loss of complexity in finger control and the dominance of an intrusion of flexor bias. These results suggest that finger individuation impairment after stroke is due to two dissociable factors: the loss of finger control complexity present in the healthy hand reflecting a top-down neural control strategy and an intrusion of flexor bias likely due to an upregulation of subcortical pathways. Our device and paradigm are demonstrated to be a promising tool to assess all aspects of the dexterous capacity of the hand.

Quantifying Hand Strength and Isometric Pinch Individuation Using a Flexible Pressure Sensor Grid

Modulating force between the thumb and another digit, or isometric pinch individuation, is critical for daily tasks and can be impaired due to central or peripheral nervous system injury. Because surgical and rehabilitative efforts often focus on regaining this dexterous ability, we need to be able to consistently quantify pinch individuation across time and facilities. Currently, a standardized metric for such an assessment does not exist. Therefore, we tested whether we could use a commercially available flexible pressure sensor grid (Tekscan F-Socket [Tekscan Inc., Norwood, MA, USA]) to repeatedly measure isometric pinch individuation and maximum voluntary contraction (MVC) in twenty right-handed healthy volunteers at two visits. We developed a novel equation informed by the prior literature to calculate isometric individuation scores that quantified percentage of force on the grid generated by the indicated digit. MVC intra-class correlation coefficients (ICCs) for the left and right hands were 0.86 (p < 0.0001) and 0.88 (p < 0.0001), respectively, suggesting MVC measurements were consistent over time. However, individuation score ICCs, were poorer (left index ICC 0.41, p = 0.28; right index ICC -0.02, p = 0.51), indicating that this protocol did not provide a sufficiently repeatable individuation assessment. These data support the need to develop novel platforms specifically for repeatable and objective isometric hand dexterity assessments.

Higher synchronization stability with piano experience: relationship with finger and presentation modality

BACKGROUND

Synchronous finger tapping to external sensory stimuli is more stable for audiovisual combined stimuli than sole auditory or visual stimuli. In addition, piano players are superior in synchronous tapping and manipulating the ring and little fingers as compared to inexperienced individuals. However, it is currently unknown whether the ability to synchronize to external sensory stimuli with the ring finger is at the level of the index finger in piano players. The aim of this study was to compare the effect of piano experience on synchronization stability between the index and ring fingers using auditory, visual, and audiovisual combined stimuli.

METHODS

Thirteen piano players and thirteen novices participated in this study. They were instructed to tap with their index or ring finger synchronously to auditory, visual, and audiovisual combined stimuli. The stimuli were presented from an electronic metronome at 1 Hz, and the tapping was performed 30 times in each condition. We analyzed standard deviation of intervals between the stimulus onset and the tap onset as synchronization stability.

RESULTS

Synchronization stability for visual stimuli was lower during ring than index finger tapping in novices; however, this decline was absent in piano players. Also, piano players showed the higher synchronization stability for audiovisual combined stimuli than sole visual and auditory stimuli when tapping with the index finger. On the other hand, in novices, synchronization stability was higher for audiovisual combined stimuli than only visual stimuli.

CONCLUSIONS

These findings suggest that improvements of both sensorimotor processing and finger motor control by piano practice would contribute to superior synchronization stability.

The spatio-temporal architecture of everyday manual behavior

In everyday activities, humans move alike to manipulate objects. Prior works suggest that hand movements are built by a limited set of basic building blocks consisting of a set of common postures. However, how the low dimensionality of hand movements supports the adaptability and flexibility of natural behavior is unknown. Through a sensorized glove, we collected kinematics data from thirty-six participants preparing and having breakfast in naturalistic conditions. By means of an unbiased analysis, we identified a repertoire of hand states. Then, we tracked their transitions over time. We found that manual behavior can be described in space through a complex organization of basic configurations. These, even in an unconstrained experiment, recurred across subjects. A specific temporal structure, highly consistent within the sample, seems to integrate such identified hand shapes to realize skilled movements. These findings suggest that the simplification of the motor commands unravels in the temporal dimension more than in the spatial one.

Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex

Objective. Enable neural control of individual prosthetic fingers for participants with upper-limb paralysis.Approach. Two tetraplegic participants were each implanted with a 96-channel array in the left posterior parietal cortex (PPC). One of the participants was additionally implanted with a 96-channel array near the hand knob of the left motor cortex (MC). Across tens of sessions, we recorded neural activity while the participants attempted to move individual fingers of the right hand. Offline, we classified attempted finger movements from neural firing rates using linear discriminant analysis with cross-validation. The participants then used the neural classifier online to control individual fingers of a brain-machine interface (BMI). Finally, we characterized the neural representational geometry during individual finger movements of both hands.Main Results. The two participants achieved 86% and 92% online accuracy during BMI control of the contralateral fingers (chance = 17%). Offline, a linear decoder achieved ten-finger decoding accuracies of 70% and 66% using respective PPC recordings and 75% using MC recordings (chance = 10%). In MC and in one PPC array, a factorized code linked corresponding finger movements of the contralateral and ipsilateral hands.Significance. This is the first study to decode both contralateral and ipsilateral finger movements from PPC. Online BMI control of contralateral fingers exceeded that of previous finger BMIs. PPC and MC signals can be used to control individual prosthetic fingers, which may contribute to a hand restoration strategy for people with tetraplegia.

Quantitative assessments of finger individuation with an instrumented glove

BACKGROUND

In clinical and research settings, hand dexterity is often assessed as finger individuation, or the ability to move one finger at a time. Despite its clinical importance, there is currently no standardized, sufficiently sensitive, or fully objective platform for these evaluations.

METHODS

Here we developed two novel individuation scores and tested them against a previously developed score using a commercially available instrumented glove and data collected from 20 healthy adults. Participants performed individuation for each finger of each hand as well as whole hand open-close at two study visits separated by several weeks. Using the three individuation scores, intra-class correlation coefficients (ICC) and minimal detectable changes (MDC) were calculated. Individuation scores were further correlated with subjective assessments to assess validity.

RESULTS

We found that each score emphasized different aspects of individuation performance while generating scores on the same scale (0 [poor] to 1 [ideal]). These scores were repeatable, but the quality of the metrics varied by both equation and finger of interest. For example, index finger intra-class correlation coefficients (ICC's) were 0.90 (< 0.0001), 0.77 (< 0.001), and 0.83 (p < 0.0001), while pinky finger ICC's were 0.96 (p < 0.0001), 0.88 (p < 0.0001), and 0.81 (p < 0.001) for each score. Similarly, MDCs also varied by both finger and equation. In particular, thumb MDCs were 0.068, 0.14, and 0.045, while index MDCs were 0.041, 0.066, and 0.078. Furthermore, objective measurements correlated with subjective assessments of finger individuation quality for all three equations (ρ = - 0.45, p < 0.0001; ρ = - 0.53, p < 0.0001; ρ = - 0.40, p < 0.0001).

CONCLUSIONS

Here we provide a set of normative values for three separate finger individuation scores in healthy adults with a commercially available instrumented glove. Each score emphasizes a different aspect of finger individuation performance and may be more uniquely applicable to certain clinical scenarios. We hope for this platform to be used within and across centers wishing to share objective data in the physiological study of hand dexterity. In sum, this work represents the first healthy participant data set for this platform and may inform future translational applications into motor physiology and rehabilitation labs, orthopedic hand and neurosurgery clinics, and even operating rooms.

Exploring Kinetic and Kinematic Finger Individuation Capability in Children With Hemiplegic Cerebral Palsy

While fine manual dexterity develops over time, the extent to which children show independent control of their digits in each hand and the impact of perinatal brain injury on this individuation have not been well quantified. Our goal in this study was to assess and compare finger force and movement individuation in 8-14 year old children with hemiplegic cerebral palsy (hCP; n = 4) and their typically developing peers (TD; n = 10). We evaluated finger force individuation with five independent load cells and captured joint movement individuation with video tracking. We observed no significant differences in individuation indices between the dominant and non-dominant hands of TD children, but individuated force and movement were substantially reduced in the paretic versus non paretic hands of children with hCP (p < 0.001). In TD participants, the thumb tended to have the greatest level of independent control. This small sample of children with hCP showed substantial loss of individuation in the paretic hand and some deficits in the non-paretic hand, suggesting possible benefit from targeted training of digit independence in both hands for children with CP.

Quantitative physical performance tests can effectively detect Degenerative Cervical Myelopathy: A systematic review and meta-analysis

PURPOSE

This review aimed to identify effective physical performance tests (PPT) as clinical outcome indicators for detecting and monitoring degenerative cervical myelopathy (DCM).

METHODS

A comprehensive literature search was performed on seven electronic databases on the effectiveness in detection and monitoring of DCM by PPT. All included studies were reviewed and undergone quality assessments on the risk-of-bias by Newcastle-Ottawa Scale and were pooled by random-effect analysis with level of significance at 0.05. Homogeneity among studies was assessed by I²-statistics and effect of PPT was confirmed by Cohen's d effect size and confidence intervals.

RESULTS

Totally, 3111 articles were retrieved, and 19 studies were included for review and meta-analysis. There were 13 studies investigating PPT regarding the upper limbs and 12 studies regarding the lower limbs. Performance in 10-second-Grip-and-Release Test (G&R) and 9-Hole-Peg Test (9HPT) was studied in 10 and 3 articles, respectively, while 10-second-Stepping Test (SST), 30-meter-Walking Test (30MWT) and Foot-Tapping Test (FTT) for lower limbs were studied in 5, 4, and 3 articles correspondingly. Only 1 study utilized the Triangle-Stepping Test. High-quality study with fair risk-of-bias was revealed from Newcastle-Ottawa scale. Large effect size facilitated detection and monitoring in DCM was unveiling for G&R, 9HPT, SST, and 30MWT. FTT, while also effective, was hindered by a high-degree heterogeneity in the meta-analysis.

CONCLUSION

Effective PPT including G&R, 9HPT, SST, 30MWT, and FTT was identified for disease detection and monitoring in DCM.

Handgrip strength and its correlation with anthropometric determinants and hand dimensions in children aged 6-12 years: A cross-sectional study

BACKGROUND

Handgrip strength is considered an important interpreter of general health, and hand functions in children. It is mainly influenced by anthropometric determinants and hand dimensions.

OBJECTIVE

To assess the handgrip strength and their association with anthropometric determinants, hand circumference, hand span, and hand length among school children in both the dominant and non-dominant hand.

METHODS

Anthropometric measurements, hand circumference, hand span, hand length, and grip strength measurements were obtained from 133 school children of both genders aged 6-12 years. A Jamar hand-held dynamometer was used to measure handgrip strength and the hand dimensions with a tape measure in cm.

RESULTS

Significant differences were found between the handgrip strength among boys and girls. The dominant hand was found to be sturdier than the non-dominant hand in both genders. We also found a significant correlation of anthropometric determinants and hand dimensions with handgrip strength. Age, BMI, hand circumference, hand span, and hand length had a strong correlation with grip strength (p < 0.01).

CONCLUSIONS

The study revealed the reference values and concluded its correlations with hand dimensions among school children aged 6-12 years and this information can serve as a manual for interpretation of handgrip strength measurements in children.

More comprehensive proprioceptive stimulation of the hand amplifies its cortical processing

Corticokinematic coherence (CKC) quantifies the phase coupling between limb kinematics and cortical neurophysiological signals reflecting proprioceptive feedback to the primary sensorimotor (SM1) cortex. We studied whether the CKC strength or cortical source location differs between proprioceptive stimulation (i.e., actuator-evoked movements) of right-hand digits (index, middle, ring, and little). Twenty-one volunteers participated in magnetoencephalography measurements during which three conditions were tested: 1) simultaneous stimulation of all four fingers at the same frequency, 2) stimulation of each finger separately at the same frequency, and 3) simultaneous stimulation of the fingers at finger-specific frequencies. CKC was computed between MEG responses and accelerations of the fingers recorded with three-axis accelerometers. CKC was stronger (P < 0.003) for the simultaneous (0.52 ± 0.02) than separate (0.45 ± 0.02) stimulation at the same frequency. Furthermore, CKC was weaker (P < 0.03) for the simultaneous stimulation at the finger-specific frequencies (0.38 ± 0.02) than for the separate stimulation. CKC source locations of the fingers were concentrated in the hand region of the SM1 cortex and did not follow consistent finger-specific somatotopic order. Our results indicate that proprioceptive afference from the fingers is processed in partly overlapping cortical neuronal circuits, which was demonstrated by the modulation of the finger-specific CKC strengths due to proprioceptive afference arising from simultaneous stimulation of the other fingers of the same hand as well as overlapping cortical source locations. Finally, comprehensive simultaneous proprioceptive stimulation of the hand would optimize functional cortical mapping to pinpoint the hand region, e.g., prior brain surgery.

NEW & NOTEWORTHY Corticokinematic coherence (CKC) can be used to study cortical proprioceptive processing and localize proprioceptive hand representation. Our results indicate that proprioceptive stimulation delivered simultaneously at the same frequency to fingers (D2–D4) maximizes CKC strength allowing robust and fast localization of the human hand region in the sensorimotor cortex using MEG.

How the hand has shaped sign languages

In natural languages, biological constraints push toward cross-linguistic homogeneity while linguistic, cultural, and historical processes promote language diversification. Here, we investigated the effects of these opposing forces on the fingers and thumb configurations (handshapes) used in natural sign languages. We analyzed over 38,000 handshapes from 33 languages. In all languages, the handshape exhibited the same form of adaptation to biological constraints found in tasks for which the hand has naturally evolved (e.g., grasping). These results were not replicated in fingerspelling—another task where the handshape is used—thus revealing a signing-specific adaptation. We also showed that the handshape varies cross-linguistically under the effects of linguistic, cultural, and historical processes. Their effects could thus emerge even without departing from the demands of biological constraints. Handshape’s cross-linguistic variability consists in changes in the frequencies with which the most faithful handshapes to biological constraints appear in individual sign languages.

Prehension kinematics in humans and macaques

Non-human primates, especially rhesus macaques, have been a dominant model to study sensorimotor control of the upper limbs. Indeed, human and macaques have similar hands and homologous neural circuits to mediate manual behavior. However, few studies have systematically and quantitatively compared the manual behaviors of the two species. Such comparison is critical for assessing the validity of using the macaque sensorimotor system as a model of its human counterpart. In this study, we systematically compared the prehensile behaviors of humans and rhesus macaques using an identical experimental setup. We found human and macaque prehension kinematics to be generally similar with a few subtle differences. While the structure of the pre-shaping hand postures is similar in humans and macaques, human postures are more object-specific and human joints are less intercorrelated. Conversely, monkeys demonstrate more stereotypical pre-shaping behaviors that are common across all objects and more variability in their postures across repeated presentations of the same object. Despite these subtle differences in manual behavior between humans and monkeys, our results bolster the use of the macaque model to understand the neural mechanisms of manual dexterity in humans.

Tactile perception of right middle fingertip suppresses excitability of motor cortex supplying right first dorsal interosseous muscle

The present study examined whether tactile perception of the fingertip modulates excitability of the motor cortex supplying the intrinsic hand muscle and whether this modulation is specific to the fingertip stimulated and the muscle and hand tested. Tactile stimulation was given to one of the five fingertips in the left or right hand, and transcranial magnetic stimulation eliciting motor evoked potential in the first dorsal interosseous muscle (FDI) or abductor digiti minimi was given 200 ms after the onset of tactile stimulation. The corticospinal excitability of the FDI at rest was suppressed by the tactile stimulation of the right middle fingertip, but such suppression was absent for the other fingers stimulated and for the other muscle or hand tested. The persistence and amplitude of the F-wave was not significantly influenced by tactile stimulation of the fingertip in the right hand. These findings indicate that tactile perception of the right middle fingertip suppresses excitability of the motor cortex supplying the right FDI at rest. The suppression of corticospinal excitability was absent during tonic contraction of the right FDI, indicating that the motor execution process interrupts the tactile perception-induced suppression of motor cortical excitability supplying the right FDI. These findings are in line with a view that the tactile perception of the right middle finger induces surround inhibition of the motor cortex supplying the prime mover of the finger neighboring the stimulated finger.

Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population response fields

For cortical motor activity, the relationships between different body part representations is unknown. Through reciprocal body part relationships, functionality of cortical motor areas with respect to whole body motor control can be characterized. In the current study, we investigate the relationship between body part representations within individual neuronal populations in motor cortices, following a 7 Tesla fMRI 18-body-part motor experiment in combination with our newly developed non-rigid population Response Field (pRF) model and graph theory. The non-rigid pRF metrics reveal somatotopic structures in all included motor cortices covering frontal, parietal, medial and insular cortices and that neuronal populations in primary sensorimotor cortex respond to fewer body parts than secondary motor cortices. Reciprocal body part relationships are estimated in terms of uniqueness, clique-formation, and influence. We report unique response profiles for the knee, a clique of body parts surrounding the ring finger, and a central role for the shoulder and wrist. These results reveal associations among body parts from the perspective of the central nervous system, while being in agreement with intuitive notions of body part usage.

A novel tablet-based application for assessment of manual dexterity and its components: a reliability and validity study in healthy subjects

BACKGROUND

We developed five tablet-based tasks (applications) to measure multiple components of manual dexterity.

AIM

to test reliability and validity of tablet-based dexterity measures in healthy participants.

METHODS

Tasks included: (1) Finger recognition to assess mental rotation capacity. The subject taps with the finger indicated on a virtual hand in three orientations (reaction time, correct trials). (2) Rhythm tapping to evaluate timing of finger movements performed with, and subsequently without, an auditory cue (inter-stimulus interval). (3) Multi-finger tapping to assess independent finger movements (reaction time, correct trials, unwanted finger movements). (4) Sequence tapping to assess production and memorization of visually cued finger sequences (successful taps). (5) Line-tracking to assess movement speed and accuracy while tracking an unpredictably moving line on the screen with the fingertip (duration, error). To study inter-rater reliability, 34 healthy subjects (mean age 35 years) performed the tablet tasks twice with two raters. Relative reliability (Intra-class correlation, ICC) and absolute reliability (Standard error of measurement, SEM) were established. Task validity was evaluated in 54 healthy subjects (mean age 49 years, range: 20-78 years) by correlating tablet measures with age, clinical dexterity assessments (time taken to pick-up objects in Box and Block Test, BBT and Moberg Pick Up Test, MPUT) and with measures obtained using a finger force-sensor device.

RESULTS

Most timing measures showed excellent reliability. Poor to excellent reliability was found for correct trials across tasks, and reliability was poor for unwanted movements. Inter-session learning occurred in some measures. Age correlated with slower and more variable reaction times in finger recognition, less correct trials in multi-finger tapping, and slower line-tracking. Reaction times correlated with those obtained using a finger force-sensor device. No significant correlations between tablet measures and BBT or MPUT were found. Inter-task correlation among tablet-derived measures was weak.

CONCLUSIONS

Most tablet-based dexterity measures showed good-to-excellent reliability (ICC ≥ 0.60) except for unwanted movements during multi-finger tapping. Age-related decline in performance and association with finger force-sensor measures support validity of tablet measures. Tablet-based components of dexterity complement conventional clinical dexterity assessments. Future work is required to establish measurement properties in patients with neurological and psychiatric disorders.

Idiosyncratic selection of active touch for shape perception

Hand movements are essential for tactile perception of objects. However, the specific functions served by active touch strategies, and their dependence on physiological parameters, are unclear and understudied. Focusing on planar shape perception, we tracked at high resolution the hands of 11 participants during shape recognition task. Two dominant hand movement strategies were identified: contour following and scanning. Contour following movements were either tangential to the contour or oscillating perpendicular to it. Scanning movements crossed between distant parts of the shapes’ contour. Both strategies exhibited non-uniform coverage of the shapes’ contours. Idiosyncratic movement patterns were specific to the sensed object. In a second experiment, we have measured the participants’ spatial and temporal tactile thresholds. Significant portions of the variations in hand speed and in oscillation patterns could be explained by the idiosyncratic thresholds. Using data-driven simulations, we show how specific strategy choices may affect receptors activation. These results suggest that motion strategies of active touch adapt to both the sensed object and to the perceiver’s physiological parameters.

TheraProx: Capacitive Proximity Sensing

This paper presents the development of a novel contactless omnidirectional capacitive proximity sensor. The presented device has been designed to be energy-efficient (≈5 mW power consumption) by means of duty-cycling the power supply. A comprehensive methodological experiment has been carried out to extensively evaluate the performance within the sensing range (5–10 cm). A simple boot-up self-adjustment mechanism has been implemented using a digital potentiometer. This feature allows for an effortless utilization of the proposed device in a wide variety of potential applications, including mobile robotics and human–machine interaction.

Predicting post-stroke motor recovery of upper extremity using clinical variables and performance assays: A prospective cohort study protocol

BACKGROUND AND PURPOSE

Measurement of movement quality is essential to distinguish motor recovery patterns and optimize rehabilitation strategies post-stroke. Recently, the Stroke Recovery and Rehabilitation Roundtable Taskforce (SRRR) recommended four kinetic and kinematic performance assays to measure upper extremity (UE) movements and distinguish behavioral restitution and compensation mechanisms early post-stroke. The purpose of this study is to develop and validate a prediction model to analyze the added prognostic value of performance assays over clinical variables assessed up to 1-month post stroke for predicting recovery of UE motor impairment, capacity and quality of movement (QoM) measured at 3 months post-stroke onset.

METHODS

In this prospective cohort study, 120 stroke survivors will be recruited within seven days post-stroke. Candidate predictors such as baseline characteristics, demographics and performance assays as per SRRR recommendations along with tonic stretch reflex threshold will be measured up to 1-month post-stroke. Upper extremity motor recovery will be evaluated in terms of motor impairment (Fugl-Meyer assessment for UE), UE capacity measured with Action Research Arm Test (ARAT) and QoM (movement smoothness in the form of peak metrics [PM]) assessed with a reach-to-grasp-to-mouth task (mimicking a drinking task) at 3 months post-stroke. Three multivariable linear regression models will be developed to predict factors responsible for the outcomes of Fugl-Meyer assessment for upper extremity (FM-UE), ARAT and movement quality. The developed models will be internally validated using a split-sample method.

DISCUSSION

This study will provide a validated prediction model inclusive of clinical and performance assays that may assist in prediction of UE motor recovery. Predicting the amount of recovery and differentiating between behavioral restitution and compensation (as reflected by the FM-UE, QoM and ARAT) would enable us in realistic goal formation and planning rehabilitation. It would also help in encouraging patients to partake in early post-stroke rehabilitation thus improving the recovery potential.

Representational Similarity Scores of Digits in the Sensorimotor Cortex Are Associated with Behavioral Performance

Previous studies aimed to unravel a digit-specific somatotopy in the primary sensorimotor (SM1) cortex. However, it remains unknown whether digit somatotopy is associated with motor preparation and/or motor execution during different types of tasks. We adopted multivariate representational similarity analysis to explore digit activation patterns in response to a finger tapping task (FTT). Sixteen healthy young adults underwent magnetic resonance imaging, and additionally performed an out-of-scanner choice reaction time task (CRTT) to assess digit selection performance. During both the FTT and CRTT, force data of all digits were acquired using force transducers. This allowed us to assess execution-related interference (i.e., digit enslavement; obtained from FTT & CRTT), as well as planning-related interference (i.e., digit selection deficit; obtained from CRTT) and determine their correlation with digit representational similarity scores of SM1. Findings revealed that digit enslavement during FTT was associated with contralateral SM1 representational similarity scores. During the CRTT, digit enslavement of both hands was also associated with representational similarity scores of the contralateral SM1. In addition, right hand digit selection performance was associated with representational similarity scores of left S1. In conclusion, we demonstrate a cortical origin of digit enslavement, and uniquely reveal that digit selection is associated with digit representations in primary somatosensory cortex (S1). Significance statement In current systems neuroscience, it is of critical importance to understand the relationship between brain function and behavioral outcome. With the present work, we contribute significantly to this understanding by uniquely assessing how digit representations in the sensorimotor cortex are associated with planning- and execution-related digit interference during a continuous finger tapping and a choice reaction time task. We observe that digit enslavement (i.e., execution-related interference) finds its origin in contralateral digit representations of SM1, and that deficits in digit selection (i.e., planning-related interference) in the right hand during a choice reaction time task are associated with more overlapping digit representations in left S1. This knowledge sheds new light on the functional contribution of the sensorimotor cortex to everyday motor skills.

Compartmentalized dynamics within a common multi-area mesoscale manifold represent a repertoire of human hand movements

The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from complex prehension to fine finger individuation. How does the brain represent such a diverse repertoire of movements? We evaluated mesoscale neural dynamics across the human "grasp network," using electrocorticography and dimensionality reduction methods, for a repertoire of hand movements. Strikingly, we found that the grasp network represented both finger and grasping movements alike. Specifically, the manifold characterizing the multi-areal neural covariance structure was preserved during all movements across this distributed network. In contrast, latent neural dynamics within this manifold were surprisingly specific to movement type. Aligning latent activity to kinematics further uncovered distinct submanifolds despite similarities in synergistic coupling of joints between movements. We thus find that despite preserved neural covariance at the distributed network level, mesoscale dynamics are compartmentalized into movement-specific submanifolds; this mesoscale organization may allow flexible switching between a repertoire of hand movements.

Quantitative Investigation of Hand Grasp Functionality: Hand Joint Motion Correlation, Independence, and Grasping Behavior

Modeling and understanding human grasp functionality are fundamental in prosthetics, robotics, medicine, and rehabilitation, since they contribute to exploring motor control mechanism, evaluating grasp function, and designing and controlling prosthetic hands or exoskeletons. However, there are still limitations in providing a comprehensive and quantitative understanding of hand grasp functionality. After simultaneously considering three significant and essential influence factors in daily grasping contained relative position, object shape, and size, this paper presents the tolerance grasping to provide a more comprehensive understanding of human grasp functionality. The results of joint angle distribution and variance explained by PCs supported that tolerance grasping can represent hand grasp functionality more comprehensively. Four synergies are found and account for 93% ± 1.5% of the overall variance. The ANOVA confirmed that there was no significant individual difference in the first four postural synergies. The common patterns of grasping behavior were found and characterized by the mean value of postural synergy across 10 subjects. The independence analysis demonstrates that the tolerance grasping results highly correlate with unstructured natural grasping and more accurately correspond to cortical representation size of finger movement. The potential for exploring the neuromuscular control mechanism of human grasping is discussed. The analysis of hand grasp characteristics that contained joint angle distribution, correlation, independence, and postural synergies, presented here, should be more representative to provide a more comprehensive understanding of hand grasp functionality.

Sensing and decoding the neural drive to paralyzed muscles during attempted movements of a person with tetraplegia using a sleeve array

Motor neurons convey information about motor intent that can be extracted and interpreted to control assistive devices. However, most methods for measuring the firing activity of single neurons rely on implanted microelectrodes. Although intracortical brain-computer interfaces (BCIs) have been shown to be safe and effective, the requirement for surgery poses a barrier to widespread use that can be mitigated by instead using noninvasive interfaces. The objective of this study was to evaluate the feasibility of deriving motor control signals from a wearable sensor that can detect residual motor unit activity in paralyzed muscles after chronic cervical spinal cord injury (SCI). Despite generating no observable hand movement, volitional recruitment of motor units below the level of injury was observed across attempted movements of individual fingers and overt wrist and elbow movements. Subgroups of motor units were coactive during flexion or extension phases of the task. Single digit movement intentions were classified offline from the EMG power (RMS) or motor unit firing rates with median classification accuracies >75% in both cases. Simulated online control of a virtual hand was performed with a binary classifier to test feasibility of real-time extraction and decoding of motor units. The online decomposition algorithm extracted motor units in 1.2 ms, and the firing rates predicted the correct digit motion 88 ± 24% of the time. This study provides the first demonstration of a wearable interface for recording and decoding firing rates of motor units below the level of injury in a person with motor complete SCI.

A Wearable Finger-Tapping Motion Recognition System Using Biodegradable Piezoelectric Film Sensors

In this paper, we aimed to develop a method for the automatic recognition of individual finger-tapping motion. Biodegradable piezoelectric film sensors were attached to the skin of a forearm near the wrist (16 channels) to measure small movements of the tendons during five-finger tapping. In the proposed method, the segments in which motion occurred were detected by calculating the total activity for all channels. A neural network is trained to classify tapping motion using the extracted data based on the total activity, thereby allowing the accurate classification of flexion/extension of each finger. We collected experimental data from five healthy young adults to verify the motion recognition accuracy of the proposed method. The results revealed that the proposed method can recognize five-finger tapping motions with high accuracy (flexion/extension of each finger: 92.0%; time-series tapping motion: 88.4%).

The neural mechanisms of manual dexterity

The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.

Real-time linear prediction of simultaneous and independent movements of two finger groups using an intracortical brain-machine interface

Modern brain-machine interfaces can return function to people with paralysis, but current upper extremity brain-machine interfaces are unable to reproduce control of individuated finger movements. Here, for the first time, we present a real-time, high-speed, linear brain-machine interface in nonhuman primates that utilizes intracortical neural signals to bridge this gap. We created a non-prehensile task that systematically individuates two finger groups, the index finger and the middle-ring-small fingers combined. During online brain control, the ReFIT Kalman filter could predict individuated finger group movements with high performance. Next, training ridge regression decoders with individual movements was sufficient to predict untrained combined movements and vice versa. Finally, we compared the postural and movement tuning of finger-related cortical activity to find that individual cortical units simultaneously encode multiple behavioral dimensions. Our results suggest that linear decoders may be sufficient for brain-machine interfaces to execute high-dimensional tasks with the performance levels required for naturalistic neural prostheses.

The Nature of Finger Enslaving: New Results and Their Implications

We present a review on the phenomenon of unintentional finger action seen when other fingers of the hand act intentionally. This phenomenon (enslaving) has been viewed as a consequence of both peripheral (e.g., connective tissue links and multifinger muscles) and neural (e.g., projections of corticospinal pathways) factors. Recent studies have shown relatively large and fast drifts in enslaving toward higher magnitudes, which are not perceived by subjects. These and other results emphasize the defining role of neural factors in enslaving. We analyze enslaving within the framework of the theory of motor control with spatial referent coordinates. This analysis suggests that unintentional finger force changes result from drifts of referent coordinates, possibly reflecting the spread of cortical excitation.

Inhibitory Control of Adjacent Finger Movements while Performing a Modified Version of the Halstead Finger Tapping Test: Effects of Age, Education and Sex

OBJECTIVE

Selective motor inhibition is known to decline with age. The purpose of this study was to determine the frequency of failures at inhibitory control of adjacent finger movements while performing a repetitive finger tapping task in young, middle-aged and older adults. Potential education and sex effects were also evaluated.

METHODS

Kinematic recordings of adjacent finger movements were obtained on 107 healthy adults (ages 20-80) while they performed a modified version of the Halstead Finger Tapping Test (HTFF). Study participants were instructed to inhibit all finger movements while tapping with the index finger.

RESULTS

Inability to inhibit adjacent finger movements while performing the task was infrequent in young adults (2.9% of individuals between 20 and 39 years of age) but increased with age (23.3% between the ages of 40 and 59; 31.0% between ages 60 and 80). Females and males did not differ in their inability to inhibit adjacent finger movements, but individuals with a college education showed a lower frequency of failure to inhibit adjacent finger movements (10.3%) compared to those with a high school education (28.6%). These findings were statistically significant only for the dominant hand.

CONCLUSION

Selective motor inhibition failures are most common in the dominant hand and occur primarily in older healthy adults while performing the modified version of the HFTT. Monitoring selective motor inhibition failures may have diagnostic significance.

Adaptation of the Corticomuscular and Biomechanical Systems of Pianists

Independent control of movements between the fingers plays a role in hand dexterity characterizing skilled individuals. However, it remains unknown whether and in what manner neuromuscular and biomechanical constraints on the movement independence of the fingers depend on motor expertise. Here, we compared motor dexterity, corticospinal excitability of multiple muscles, muscular activation, and anatomical features of the fingers between the pianists and nonpianists. When the ring finger was passively moved by a robot, passive motions produced at the adjacent fingers were smaller for the pianists than the nonpianists, indicating reduced biomechanical constraint of fingers in the pianists. In contrast, when the ring finger moved actively, we found no group difference in passive motions produced at the adjacent fingers; however, reduced inhibition of corticospinal excitability of the adjacent fingers in the pianists compared with the nonpianists. This suggests strengthened neuromuscular coupling between the fingers of the pianists, enhancing the production of coordinated finger movements. These group differences were not evident during the index and little finger movements. Together, pianists show expertise-dependent biomechanical and neurophysiological adaptations, specifically at the finger with innately low movement independence. Such contrasting adaptations of pianists may subserve dexterous control of both the individuated and coordinated finger movements.

Common Motor Drive Triggers Response of Prime Movers When Two Fingers Simultaneously Respond to a Cue

This study investigated whether the motor execution process of one finger movement in response to a start cue is influenced by the participation of another finger movement and whether the process of the finger movement is dependent on the movement direction. The participants performed a simple reaction time (RT) task, the abduction or flexion of one (index or little finger) or two fingers (index and little fingers). The RT of the prime mover for the finger abduction was significantly longer than that for the flexion, indicating that the time taken for the motor execution of the finger response is dependent on the movement direction. The RT of the prime mover was prolonged when the abduction of another finger, whose RT was longer than the flexion, was added. This caused closer RTs between the prime movers for a two-finger response compared with the RTs for a one finger response. The absolute difference in the RT between the index and little finger responses became smaller when two fingers responded together compared with one finger response. Those results are well explained by a view that the common motor drive triggers the prime movers when two fingers move together in response to a start cue.

Influence of visual feedback, hand dominance and sex on individuated finger movements

The ability to perform individual finger movements, highly important in daily activities, involves visual monitoring and proprioception. We investigated the influence of vision on the spatial and temporal control of independent finger movements, for the dominant and non-dominant hand and in relation to sex. Twenty-six healthy middle-aged to old adults (M age = 61 years; range 46–79 years; females n = 13) participated. Participants performed cyclic flexion–extension movements at the metacarpophalangeal joint of one finger at a time while keeping the other fingers as still as possible. Movements were recorded using 3D optoelectronic motion technique (120 Hz). The movement trajectory distance; speed peaks (movement smoothness); Individuation Index (II; the degree a finger can move in isolation from the other fingers) and Stationarity Index (SI; how still a finger remains while the other fingers move) were extracted. The main findings were: (1) vision only improved the II and SI marginally; (2) longer trajectories were evident in the no-vision condition for the fingers of the dominant hand in the female group; (3) longer trajectories were specifically evident for the middle and ring fingers within the female group; (4) females had marginally higher II and SI compared with males; and (5) females had fewer speed peaks than males, particularly for the ring finger. Our results suggest that visual monitoring of finger movements marginally improves performance of our non-manipulative finger movement task. A consistent finding was that females showed greater independent finger control compared with males.

Force Steadiness: From Motor Units to Voluntary Actions

Voluntary actions are controlled by the synaptic inputs that are shared by pools of spinal motor neurons. The slow common oscillations in the discharge times of motor units due to these synaptic inputs are strongly correlated with the fluctuations in force during submaximal isometric contractions (force steadiness) and moderately associated with performance scores on some tests of motor function. However, there are key gaps in knowledge that limit the interpretation of differences in force steadiness.

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.

Synergy-Based Sensor Reduction for Recording the Whole Hand Kinematics

Simultaneous measurement of the kinematics of all hand segments is cumbersome due to sensor placement constraints, occlusions, and environmental disturbances. The aim of this study is to reduce the number of sensors required by using kinematic synergies, which are considered the basic building blocks underlying hand motions. Synergies were identified from the public KIN-MUS UJI database (22 subjects, 26 representative daily activities). Ten synergies per subject were extracted as the principal components explaining at least 95% of the total variance of the angles recorded across all tasks. The 220 resulting synergies were clustered, and candidate angles for estimating the remaining angles were obtained from these groups. Different combinations of candidates were tested and the one providing the lowest error was selected, its goodness being evaluated against kinematic data from another dataset (KINE-ADL BE-UJI). Consequently, the original 16 joint angles were reduced to eight: carpometacarpal flexion and abduction of thumb, metacarpophalangeal and interphalangeal flexion of thumb, proximal interphalangeal flexion of index and ring fingers, metacarpophalangeal flexion of ring finger, and palmar arch. Average estimation errors across joints were below 10% of the range of motion of each joint angle for all the activities. Across activities, errors ranged between 3.1% and 16.8%.

A novel energy-motion model for continuous sEMG decoding: from muscle energy to motor pattern

At present, sEMG-based gesture recognition requires vast amounts of training data; otherwise it is limited to a few gestures. Objective. This paper presents a novel dynamic energy model that decodes continuous hand actions by training small amounts of sEMG data. Approach. The activation of forearm muscles can set the corresponding fingers in motion or state with movement trends. The moving fingers store kinetic energy, and the fingers with movement trends store potential energy. The kinetic energy and potential energy in each finger are dynamically allocated due to the adaptive-coupling mechanism of five-fingers in actual motion. Meanwhile, the sum of the two energies remains constant at a certain muscle activation. We regarded hand movements with the same direction of acceleration for five-finger as the same in energy mode and divided hand movements into ten energy modes. Independent component analysis and machine learning methods were used to model associations between sEMG signals and energy modes and expressed gestures by energy form adaptively. This theory imitates the self-adapting mechanism in actual tasks. Thus, ten healthy subjects were recruited, and three experiments mimicking activities of daily living were designed to evaluate the interface: (1) the expression of untrained gestures, (2) the decoding of the amount of single-finger energy, and (3) real-time control. Main results. (1) Participants completed the untrained hand movements (100/100, p < 0.0001). (2) The interface performed better than chance in the experiment where participants pricked balloons with a needle tip (779/1000, p < 0.0001). (3) In the experiment where participants punched a hole in the plasticine on the balloon, the success rate was over 95% (97.67 ± 5.04%, p < 0.01). Significance. The model can achieve continuous hand actions with speed or force information by training small amounts of sEMG data, which reduces learning task complexity.

Classification of Individual Finger Movements Using Intracortical Recordings in Human Motor Cortex

BACKGROUND

Intracortical microelectrode arrays have enabled people with tetraplegia to use a brain-computer interface for reaching and grasping. In order to restore dexterous movements, it will be necessary to control individual fingers.

OBJECTIVE

To predict which finger a participant with hand paralysis was attempting to move using intracortical data recorded from the motor cortex.

METHODS

A 31-yr-old man with a C5/6 ASIA B spinal cord injury was implanted with 2 88-channel microelectrode arrays in left motor cortex. Across 3 d, the participant observed a virtual hand flex in each finger while neural firing rates were recorded. A 6-class linear discriminant analysis (LDA) classifier, with 10 × 10-fold cross-validation, was used to predict which finger movement was being performed (flexion/extension of all 5 digits and adduction/abduction of the thumb).

RESULTS

The mean overall classification accuracy was 67% (range: 65%-76%, chance: 17%), which occurred at an average of 560 ms (range: 420-780 ms) after movement onset. Individually, thumb flexion and thumb adduction were classified with the highest accuracies at 92% and 93%, respectively. The index, middle, ring, and little achieved an accuracy of 65%, 59%, 43%, and 56%, respectively, and, when incorrectly classified, were typically marked as an adjacent finger. The classification accuracies were reflected in a low-dimensional projection of the neural data into LDA space, where the thumb-related movements were most separable from the finger movements.

CONCLUSION

Classification of intention to move individual fingers was accurately predicted by intracortical recordings from a human participant with the thumb being particularly independent.

A Soft 3D-Printed Robotic Hand Actuated by Coiled SMA

Robotic hands with unique designs, capabilities and applications have been presented in the literature focusing on sensing, actuation, control, powering and manufacturing, most of which are created by manual assembly process. However, due to advancements in additive manufacturing, new capabilities have replaced traditional methods of manufacturing. In this paper, we present a soft 3D-printed robotic hand actuated by custom-made coiled shape memory alloy (SMA) actuators. The hand uses additive manufacturing of flexible thermoplastic polyurethane (TPU) material, which allows flexing at the joint and hence eliminates the need for additional assembly. Here, we present the full characteristics of the robotic hand such as object grasping categorized by size and weight from the ARAT kit and others. The robotic hand is 425 mm in length, weighs 235 g and is able to operate at a frequency of 0.125 Hz without active cooling. It can grasp an object of 55–81 mm widths, weighing up to 133 g, while consuming an average power of 7.82 W. We also show the time domain response of our custom-made coiled SMA to different current inputs, and its corresponding force and displacement. The current design yields a lightweight and low cost artificial hand with significantly simplified manufacturing for applications in robotics and prosthetics.

Gaze direction influences grasping actions towards unseen, haptically explored, objects

Haptic exploration produces mental object representations that can be memorized for subsequent object-directed behaviour. Storage of haptically-acquired object images (HOIs), engages, besides canonical somatosensory areas, the early visual cortex (EVC). Clear evidence for a causal contribution of EVC to HOI representation is still lacking. The use of visual information by the grasping system undergoes necessarily a frame of reference shift by integrating eye-position. We hypothesize that if the motor system uses HOIs stored in a retinotopic coding in the visual cortex, then its use is likely to depend at least in part on eye position. We measured the kinematics of 4 fingers in the right hand of 15 healthy participants during the task of grasping different unseen objects behind an opaque panel, that had been previously explored haptically. The participants never saw the object and operated exclusively based on haptic information. The position of the object was fixed, in front of the participant, but the subject’s gaze varied from trial to trial between 3 possible positions, towards the unseen object or away from it, on either side. Results showed that the middle and little fingers’ kinematics during reaching for the unseen object changed significantly according to gaze position. In a control experiment we showed that intransitive hand movements were not modulated by gaze direction. Manipulating eye-position produces small but significant configuration errors, (behavioural errors due to shifts in frame of reference) possibly related to an eye-centered frame of reference, despite the absence of visual information, indicating sharing of resources between the haptic and the visual/oculomotor system to delayed haptic grasping.

Unexpected complexity of everyday manual behaviors

How does the brain control an effector as complex and versatile as the hand? One possibility is that neural control is simplified by limiting the space of hand movements. Indeed, hand kinematics can be largely described within 8 to 10 dimensions. This oft replicated finding has been construed as evidence that hand postures are confined to this subspace. A prediction from this hypothesis is that dimensions outside of this subspace reflect noise. To address this question, we track the hand of human participants as they perform two tasks—grasping and signing in American Sign Language. We apply multiple dimension reduction techniques and replicate the finding that most postural variance falls within a reduced subspace. However, we show that dimensions outside of this subspace are highly structured and task dependent, suggesting they too are under volitional control. We propose that hand control occupies a higher dimensional space than previously considered.

How does the brain control the complex movements of hands? Here, by tracking human hand kinematics and applying multidimensional reduction techniques, the authors provide evidence that grasping involves a complex control system that regulates even the most subtle aspects of hand movement.

Effect of muscular activation on surrounding motor networks in developmental stuttering: A TMS study

Previous studies regarding developmental stuttering (DS) suggest that motor neural networks are strongly affected. Transcranial magnetic stimulation (TMS) was used to investigate neural activation of the primary motor cortex in DS during movement execution, and the influence of muscle representations involved in movements on "surrounding" ones. TMS was applied over the contralateral abductor digiti minimi (ADM) motor representation, at rest and during the movement of homologue first dorsal interosseous muscles (tonic contraction, phasic movements cued by acoustic signalling, and "self-paced" movements). Results highlighted a lower cortico-spinal excitability of ADM in the left hemisphere of stutterers, and an enhanced intracortical inhibition in their right motor cortex (in comparison to fluent speakers). Abnormal intracortical functioning was especially evident during phasic contractions cued by "external" acoustic signals. An exaggerated inhibition of muscles not directly involved in intended movements, in stuttering, may be useful to obtain more efficient motor control. This was stronger during contractions cued by "external" signals, highlighting mechanisms likely used by stutterers during fluency-evoking conditions.