Multidigit movement synergies of the human hand in an unconstrained haptic exploration task

Grasping affordance judgments depend on the object emotional value

Introduction

The concept of affordance refers to the opportunities for action provided by the environment, often conveyed through visual information. It has been applied to explain visuomotor processing and movement planning. As emotion modulates both visual perception and the motor system, it is reasonable to ask whether emotion can influence affordance judgments. If present, this relationship can have important ontological implications for affordances. Thus, we investigated whether the emotional value of manipulable objects affected the judgment of the appropriate grasping that could be used to interact with them (i.e., their affordance).

Methods

Volunteers were instructed to use a numerical scale to report their judgment on how an observed object should be grasped. We compared these judgments across emotional categories of objects (pleasant, unpleasant and neutral), while also considering the expected effect of object size.

Results

We found that unpleasant objects were rated as more appropriately graspable by a precision grip than pleasant and neutral objects. Simultaneously, smaller object size also favored this judgment. This effect was seen in all emotional categories examined in equal magnitude.

Discussion

Our findings suggest that the emotional value of objects modulates affordance judgments in a way that favors careful manipulation and minimal physical contact with aversive stimuli. Finally, we discuss how this affective aspect of our experience of objects overlaps with what affordances are conceptualized to be, calling for further reexamination of the relationship between affordances and emotions.

Comparison of synergy patterns between the right and left hand while performing postures and object grasps

The human hand, with many degrees of freedom, serves as an excellent tool for dexterous manipulation. Previous research has demonstrated that there exists a lower-dimensional subspace that synergistically controls the full hand kinematics. The elements of this subspace, also called synergies, have been viewed as the strategy developed by the CNS in the control of finger movements. Considering that the control of fingers is lateralized to the contralateral hemisphere, how the synergies differ for the control of the dominant and the non-dominant hand has not been widely addressed. In this paper, hand kinematics was recorded using electromagnetic tracking system sensors as participants made various postures and object grasps with their dominant hand and non-dominant hand separately. Synergies that explain 90% of variance in data of both hands were analyzed for similarity at the individual level as well as at the population level. The results showed no differences in synergies between the hands at both these levels. PC scores and cross-reconstruction errors were analyzed to further support the prevalence of similarity between the synergies of the hands. Future work is proposed, and implications of the results to the treatment and diagnosis of neuromotor disorders are discussed.

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.

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

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

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Hand movements are comprised of a low-dimensional set of movement primitives

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Primitive movements have an important temporal component

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Spatiotemporal movement primitives are conserved across individuals

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New complex movements can be flexibly reconstructed using these primitives

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.

Central Commands to the Elbow and Shoulder Muscles During Circular Planar Movements of Hand With Simultaneous Generation of Tangential Forces

This study examines some of the non-linear effects of signal transduction in the human motor system, with particular emphasis on muscle hysteresis. The movement tests were analyzed in a group of eight subjects, which were asked to develop tangential force using visual biofeedback while performing slow, externally imposed, circular movements of right hand holding a moving handle operated by a computerized mechatronic system. The positional changes in the averaged EMGs of the elbow and shoulder muscles were compared for all combinations of direction of movement and generated force. Additionally, for one of the subjects, there was carried out MRI identification and 3D printing of the bones of the forelimb, shoulder, scapula and collarbone, which made it possible to reconstruct for him the length and force traces of all the muscles under study. The averaged EMG traces in muscles of both joints show their close correspondence to the related force traces, however, the co-activation patterns of activity in agonists and antagonists were also often encountered. The EMG waves related to the respective force waves were strongly dependent on the predominant direction of the muscle length changes within the correspondent force wave locations: the EMG intensities were higher for the shortening muscle movements (concentric contractions) and lower during muscle lengthening (eccentric contractions). The data obtained allows to suggest that for two-joint movements of the forelimbs, it is sufficient to consider the force and activation synergies (patterns of simultaneous activity in different muscles), ignoring at the first stage the effects associated with kinematic synergy. On the other hand, the data obtained indicate that the movement kinematics has a strong modulating effect on the activation synergy, dividing it into concentric and eccentric subtypes, in accordance with the known non-linear features of the muscle dynamics. It has been shown that the concentric and eccentric differences in the responses of the shoulder muscles are more clearly distinguishable than those in the elbow muscles. The shoulder muscles also have a more pronounced symmetry of the averaged EMG responses with respect to the ascending and descending phases of force waves, while demonstrating a lower degree of antagonist cocontraction. The data obtained suggest that the central commands in two-joint movements are determined mainly by the interdependence of force and activation synergies including both intra- and inter-joint components, while kinematic synergy can be interpreted as a potent modulator of activation synergy.

Neural representation in M1 and S1 cortex of bilateral hand actions during prehension

Bimanual movements that require coordinated actions of the two hands may be coordinated by synchronous bilateral activation of somatosensory and motor cortical areas in both hemispheres, by enhanced activation of individual neurons specialized for bimanual actions, or by both mechanisms. To investigate cortical neural mechanisms that mediate unimanual and bimanual prehension, we compared actions of the left and right hands in a reach to grasp-and-pull instructed-delay task. Spike trains were recorded with multiple electrode arrays placed in the hand area of primary motor (M1) and somatosensory (S1) cortex of the right hemisphere in macaques, allowing us to measure and compare the relative timing, amplitude, and synchronization of cortical activity in these areas as animals grasped and manipulated objects that differed in shape and location. We report that neurons in the right hemisphere show common task-related firing patterns for the two hands but actions of the ipsilateral hand elicited weaker and shorter-duration responses than those of the contralateral hand. We report significant bimanual activation of neurons in M1 but not in S1 cortex when animals have free choice of hand use in prehension tasks. Population ensemble responses in M1 thereby provide an accurate depiction of hand actions during skilled manual tasks. These studies also demonstrate that somatosensory cortical areas serve important cognitive and motor functions in skilled hand actions. Bilateral representation of hand actions may serve an important role in "motor equivalence" when the same movements are performed by either hand and in transfer of skill learning between the hands.NEW & NOTEWORTHY Humans can manipulate small objects with the right or left hand but typically select the dominant hand to handle them. We trained monkeys to grasp and manipulate objects with either hand, while recording neural activity in primary motor (M1) and somatosensory (S1) cortex. Actions of both hands activate M1 neurons, but S1 neurons respond only to the contralateral hand. Bilateral sensitivity in M1 may aid skill transfer between hands after stroke or head injury.

Mental Rotation Skill Shapes Haptic Exploration Strategies

Haptic exploration strategies have been traditionally studied focusing on hand movements and neglecting how objects are moved in space. However, in daily life situations touch and movement cannot be disentangled. Furthermore, the relation between object manipulation as well as performance in haptic tasks and spatial skill is still little understood. In this study, we used iCube, a sensorized cube recording its orientation in space as well as the location of the points of contact on its faces. Participants had to explore the cube faces where little pins were positioned in varying number and count the number of pins on the faces with either even or odd number of pins. At the end of this task, they also completed a standard visual mental rotation test (MRT). Results showed that higher MRT scores were associated with better performance in the task with iCube both in term of accuracy and exploration speed and exploration strategies associated with better performance were identified. High performers tended to rotate the cube so that the explored face had the same spatial orientation (i.e., they preferentially explored the upward face and rotated iCube to explore the next face in the same orientation). They also explored less often twice the same face and were faster and more systematic in moving from one face to the next. These findings indicate that iCube could be used to infer subjects' spatial skill in a more natural and unobtrusive fashion than with standard MRTs.

Reducing Anthropomorphic Hand Degrees of Actuation with Grasp-Function-Dependent and Joint-Element-Sparse Hand Synergies

In this paper, a set of grasp-function-dependent and joint-element-sparse hand synergies was proposed. First, hand synergies were extracted from five basic categories of movements by principal component analysis (PCA). Then, varimax rotation was applied on these synergies, so each sparse synergy only represented a limited number of joints. Next, according to the contribution to these sparse synergies, finger joints were clustered into different joint modules. Finally, integrating the joint modules in different categories of hand movements, the minimum number of actuators and joint synergic modules for anthropomorphic hands were determined. The results showed that using 5 groups of joint modules and 7–9 actuators we can achieve the best performance of grasp function and motion flexibility. Furthermore, through the reasonable design of adaptive and hyperextension functional joint modules, anthropomorphic hands can better meet the requirements of different tasks like power grasping and precision pinching. Comparing with traditional finger-based actuation strategy, the joint coupling scheme achieved better anthropomorphic performance and larger workspace. These above findings will benefit the development of mechanical structure design and control method of anthropomorphic hands.

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.

Quantitative Investigation of Hand Grasp Functionality: Thumb Grasping Behavior Adapting to Different Object Shapes, Sizes, and Relative Positions

This paper is the first in the two-part series quantitatively modelling human grasp functionality and understanding the way human grasp objects. The aim is to investigate the thumb movement behavior influenced by object shapes, sizes, and relative positions. Ten subjects were requested to grasp six objects (3 shapes × 2 sizes) in 27 different relative positions (3 X deviation × 3 Y deviation × 3 Z deviation). Thumb postures were investigated to each specific joint. The relative position (X, Y, and Z deviation) significantly affects thumb opposition rotation (Rot) and flexion (interphalangeal (IP) and metacarpo-phalangeal (MCP)), while the object property (object shape and size) significantly affects thumb abduction/adduction (ABD) motion. Based on the F value, the Y deviation has the primary effects on thumb motion. When the Y deviation changing from proximal to distal, thumb opposition rotation (Rot) and flexion (IP and MCP joint) angles were increased and decreased, respectively. For principal component analysis (PCA) results, thumb grasp behavior can be accurately reconstructed by first two principal components (PCs) which variance explanation ratio reached 93.8% and described by the inverse and homodromous coordination movement between thumb opposition and IP flexion. This paper provides a more comprehensive understanding of thumb grasp behavior. The postural synergies can reproduce the anthropomorphic motion, reduce the robot hardware, and control dimensionality. All of these provide a more accurate and general basis for the design and control of the bionic thumb and novel wearable assistant robot, thumb function assessment, and rehabilitation.

Using Sensorized Gloves and Dimensional Reduction for Hand Function Assessment of Patients with Osteoarthritis

Sensorized gloves allow the measurement of all hand kinematics that are essential for daily functionality. However, they are scarcely used by clinicians, mainly because of the difficulty of analyzing all joint angles simultaneously. This study aims to render this analysis easier in order to enable the applicability of the early detection of hand osteoarthritis (HOA) and the identification of indicators of dysfunction. Dimensional reduction was used to compare kinematics (16 angles) of HOA patients and healthy subjects while performing the tasks of the Sollerman hand function test (SHFT). Five synergies were identified by using principal component (PC) analyses, patients using less fingers arch, higher palm arching, and a more independent thumb abduction. The healthy PCs, explaining 70% of patients’ data variance, were used to transform the set of angles of both samples into five reduced variables (RVs): fingers arch, hand closure, thumb-index pinch, forced thumb opposition, and palmar arching. Significant differences between samples were identified in the ranges of movement of most of the RVs and in the median values of hand closure and thumb opposition. A discriminant function for the detection of HOA, based in RVs, is provided, with a success rate of detection higher than that of the SHFT. The temporal profiles of the RVs in two tasks were also compared, showing their potentiality as dysfunction indicators. Finally, reducing the number of sensors to only one sensor per synergy was explored through a linear regression, resulting in a mean error of 7.0°.

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.

Sensorimotor strategies and neuronal representations for shape discrimination

Humans and other animals can identify objects by active touch, requiring the coordination of exploratory motion and tactile sensation. Both the motor strategies and neural representations employed could depend on the subject's goals. We developed a shape discrimination task that challenged head-fixed mice to discriminate concave from convex shapes. Behavioral decoding revealed that mice did this by comparing contacts across whiskers. In contrast, a separate group of mice performing a shape detection task simply summed up contacts over whiskers. We recorded populations of neurons in the barrel cortex, which processes whisker input, and found that individual neurons across the cortical layers encoded touch, whisker motion, and task-related signals. Sensory representations were task-specific: during shape discrimination, but not detection, neurons responded most to behaviorally relevant whiskers, overriding somatotopy. Thus, sensory cortex employs task-specific representations compatible with behaviorally relevant computations.

A Systematic Analysis of Hand Movement Functionality: Qualitative Classification and Quantitative Investigation of Hand Grasp Behavior

Understanding human hand movement functionality is fundamental in neuroscience, robotics, prosthetics, and rehabilitation. People are used to investigate movement functionality separately from qualitative or quantitative perspectives. However, it is still limited to providing an integral framework from both perspectives in a logical manner. In this paper, we provide a systematic framework to qualitatively classify hand movement functionality, build prehensile taxonomy to explore the general influence factors of human prehension, and accordingly design a behavioral experiment to quantitatively understand the hand grasp. In qualitative analysis, two facts are explicitly proposed: (1) the arm and wrist make a vital contribution to hand movement functionality; (2) the relative position (relative position in this paper is defined as the distance between the center of the human wrist and the object center of gravity) is a general influence factor significantly impacting human prehension. In quantitative analysis, the significant influence of three factors, object shape, size, and relative position, is quantitatively demonstrated. Simultaneously considering the impact of relative position, object shape, and size, the prehensile taxonomy and behavioral experiment results presented here should be more representative and complete to understand human grasp functionality. The systematic framework presented here is general and applicable to other body parts, such as wrist, arm, etc. Finally, many potential applications and the limitations are clarified.

HandMATE: Wearable Robotic Hand Exoskeleton and Integrated Android App for At Home Stroke Rehabilitation

We have developed HandMATE (Hand Movement Assisting Therapy Exoskeleton); a wearable motorized hand exoskeleton for home-based movement therapy following stroke. Each finger and the thumb is powered by a linear actuator which provides flexion and extension assistance. Force sensitive resistors integrated into the design measure grasp and extension initiation force. An assistive therapy mode is based on an admittance control strategy. We evaluated our control system via subject and bench testing. Errors during a grip force tracking task while using the HandMATE were minimal (<1%) and comparable to unassisted healthy hand performance. We also outline a dedicated app we have developed for optimal use of HandMATE at home. The exoskeleton communicates wirelessly with an Android tablet which features guided exercises, therapeutic games and performance feedback. We surveyed 5 chronic stroke patients who used the HandMATE device to further evaluate our system, receiving positive feedback on the exoskeleton and integrated app.

Sensing form - finger gaiting as key to tactile object exploration - a data glove analysis of a prototypical daily task

Background

Motor hand skill and associated dexterity is important for meeting the challenges of daily activity and an important resource post-stroke. In this context, the present study investigated the finger movements of right-handed subjects during tactile manipulation of a cuboid, a prototypical task underlying tactile exploration. During one motor act, the thumb and fingers of one hand surround the cuboid in a continuous and regular manner. While the object is moved by the guiding thumb, the opposed supporting fingers are replaced once they reach their joint limits by free fingers, a mechanism termed finger gaiting.

Methods

For both hands of 22 subjects, we acquired the time series of consecutive manipulations of a cuboid at a frequency of 1 Hz, using a digital data glove consisting of 29 sensors. Using principle component analysis, we decomposed the short action into motor patterns related to successive manipulations of the cuboid. The components purport to represent changing grasp configurations involving the stabilizing fingers and guiding thumb. The temporal features of the components permits testing whether the distinct configurations occur at the frequency of 1 Hz, i.e. within the time window of 1 s, and, thus, taxonomic classification of the manipulation as finger gaiting.

Results

The fraction of variance described by the principal components indicated that three components described the salient features of the single motor acts for each hand. Striking in the finger patterns was the prominent and varying roles of the MCP and PIP joints of the fingers, and the CMC joint of the thumb. An important aspect of the three components was their representation of distinct finger configurations within the same motor act. Principal component and graph theory analysis confirmed modular, functionally synchronous action of the involved joints. The computation of finger trajectories in one subject illustrated the workspace of the task, which differed for the right and left hands.

Conclusion

In this task one complex motor act of 1 s duration could be described by three elementary and hierarchically ordered grasp configurations occurring at the prescribed frequency of 1 Hz. Therefore, these configurations represent finger gaiting, described until now only in artificial systems, as the principal mechanism underlying this prototypical task.

Trial registration

clinicaltrials.gov, NCT02865642, registered 12 August 2016.

Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand

BACKGROUND

State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.e. postural synergies) in software and hardware architecture of artificial devices is opening new approaches for the design and control of upper-limb prostheses.

METHODS

Following these emerging principles, previous research on the SoftHand Pro, which embeds one physical synergy, showed promising results in terms of intuitiveness, robustness, and grasping performance. To explore these principles also in hands with augmented capabilities, this paper describes the SoftHand 2 Pro, a second generation of the device with 19 degrees-of-freedom and a second synergistic layer. After a description of the proposed device, the work explores a continuous switching control method based on a myoelectric pattern recognition classifier.

RESULTS

The combined system was validated using standardized assessments with able-bodied and, for the first time, amputee subjects. Results show an average improvement of more than 30% of fine grasp capabilities and about 10% of hand function compared with the first generation SoftHand Pro.

CONCLUSIONS

Encouraging results suggest how this approach could be a viable way towards the design of more natural, reliable, and intuitive dexterous hands.

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.

Hand Kinematics Characterization While Performing Activities of Daily Living Through Kinematics Reduction

Improving the understanding of hand kinematics during the performance of activities of daily living may help improve the control of hand prostheses and hand function assessment. This work identifies sparse synergies (each degree of freedom is present mainly in only one synergy), representative of the global population, with emphasis in unveiling the coordination of joints with small range of motion (palmar arching and fingers abduction). The study is the most complete study described in the literature till now, involving 22 healthy subjects and 26 representative day-to-day life activities. Principal component analysis was used to reduce the original 16 angles recorded with an instrumented glove. Five synergies explained 75% of total variance: closeness (coordinated flexion and abduction of metacarpophalangeal finger joints), digit arching (flexion of proximal interphalangeal joints), palmar-thumb coordination (coordination of palmar arching and thumb carpometacarpal flexion), thumb opposition, and thumb arch. The temporal evolution of these synergies is provided during reaching per intended grasp and during manipulation per specific task, which could be used as normative patterns for the global population. Reaching has been observed to require the modulation of closeness, digit arch and thumb opposition synergies, with different control patterns per grasp. All the synergies are very important during manipulation and need to be modulated for all the tasks. Finally, groups of tasks with similar kinematic requirements in terms of synergies have been identified, which could benefit the selection of tasks for rehabilitation and hand function assessments.

Fully Wearable Actuated Soft Exoskeleton for Grasping Assistance in Everyday Activities

Worldwide, over 50 million people suffer from persistent hand impairments after stroke or spinal cord injury (SCI). This results in major loss of independence and quality of life. Robotic hand exoskeletons can compensate for lost motor function and assist in grasping tasks performed in everyday activities. Several recent prototypes can partially provide this assistance. However, it remains challenging to integrate the dexterity required for daily tasks in a safe and user-friendly design that is acceptable for daily use in subjects with neuromotor hand impairments. We present the design of RELab tenoexo; a fully wearable assistive soft hand exoskeleton for daily activities. We present sleek mechanisms for a hand module that generates the four most frequently used grasp types, employing a remote actuation system that reduces weight on the hand. For optimal assistance and highest adaptability, we present various design and control options to customize the modular device, along with an automated tailoring algorithm that allows automatically generated hand modules for individual users. Mechanical evaluation shows that RELab tenoexo covers the range of motion and the fingertip forces required to assist users in up to 80% of all grasping activities. In user tests, we find that the low weight, unintrusive size, high wearing comfort, and appealing appearance are beneficial for user acceptance and usability in daily life. Finally, we demonstrate that RELab tenoexo leads to an immediate improvement of the functional grasping ability in a subject with SCI.

Sharing of hand kinematic synergies across subjects in daily living activities

The motor system is hypothesised to use kinematic synergies to simplify hand control. Recent studies suggest that there is a large set of synergies, sparse in degrees of freedom, shared across subjects, so that each subject performs each action with a sparse combination of synergies. Identifying how synergies are shared across subjects can help in prostheses design, in clinical decision-making or in rehabilitation. Subject-specific synergies of healthy subjects performing a wide number of representative daily living activities were obtained through principal component analysis. To make synergies comparable between subjects and tasks, the hand kinematics data were scaled using normative range of motion data. To obtain synergies sparse in degrees of freedom a rotation method that maximizes the sum of the variances of the squared loadings was applied. Resulting synergies were clustered and each cluster was characterized by a core synergy and different indexes (prevalence, relevance for function and within-cluster synergy similarity), substantiating the sparsity of synergies. The first two core synergies represent finger flexion and were present in all subjects. The remaining core synergies represent coordination of the thumb joints, thumb-index joints, palmar arching or fingers adduction, and were employed by subjects in different combinations, thus revealing different subject-specific strategies.

Hysteresis and Synergy of the Central Commands to Muscles Participating in Parafrontal Upper Limb Movements

The averaged electromyograms (EMGs) were registered from the arm muscles of ten subjects in movements of the right hand performed under visual guidance on the horizontal plane along linear trajectories going parallel to the frontal plane at various distances from the trunk. The tests consisted of the steady movements (speed 4 cm/s) between two points symmetrical about the shoulder axis; the hand moved firstly from left to right, then in the opposite direction. The tests repeated ten times for each of two equal loads (10.2 N) applied to the hand along movement trajectory in the right- (F_r) or leftward (F_l) directions. The elbow and shoulder flexors reacted predominantly on F_r loads; the extensors were mostly activated by F_l loads. Positional changes of the averaged EMGs in both flexor and extensor muscles belonging to different joints demonstrated hysteresis properties; the respective hysteresis loops had counterclockwise direction in flexors and clockwise in extensors. The muscles predominantly opposing the loading forces of a given direction participate in a cocontraction mode as antagonists when the direction of load is changed; in this case, together with a decrease in the amplitude of the hysteresis loops, their direction is also reversed. The multiplication index of synergy (MIS), which is based on multiplication of the respective normalized averaged EMG records, has been proposed to evaluate quantitatively changes in the synergy effects between various muscle groups. For distal shifts of the movement traces, the synergy effects are shown to be changed in different directions, increasing in flexors and decreasing in extensors. The obtained results demonstrate that the muscle hysteresis leads to strong modification of the central commands during movements.

Complex couplings between joints, muscles and performance: the role of the wrist in grasping

The relationship between posture, muscle length properties and performance remains unclear, because of a lack of quantitative data. Studies on grasping tasks suggested that wrist position could favour the extrinsic finger flexor in regards to their length to maximise grip force performance. The present study aimed at providing quantitative evidence of the links between wrist posture, muscle capacities and grip capabilities. It combines experimental measurements and a musculoskeletal model including the force-length relationship of the four prime muscles used in grasping. Participants exerted their maximum grip force on a cylindrical dynamometer in four different wrist postures, including one freely chosen by participants (spontaneous). A musculoskeletal model computed the muscle force level and length from motion capture and muscle activation. Results revealed that participants exerted maximum grip force spontaneously, with a loss of force when using other postures. At muscle force and length level, grip force variation seems to be associated with all the muscles under study. This observation led to a first quantitative link between power grip, posture and muscle properties, which could provide more insight into neuromechanical interaction involved when grasping. The design of ergonomic devices could also benefit from this quantification of the relationship between wrist angle and muscle length properties.

Postural Representations of the Hand in the Primate Sensorimotor Cortex

Manual dexterity requires proprioceptive feedback about the state of the hand. To date, study of the neural basis of proprioception in the cortex has focused primarily on reaching movements to the exclusion of hand-specific behaviors such as grasping. To fill this gap, we record both time-varying hand kinematics and neural activity evoked in somatosensory and motor cortices as monkeys grasp a variety of objects. We find that neurons in the somatosensory cortex, as well as in the motor cortex, preferentially track time-varying postures of multi-joint combinations spanning the entire hand. This contrasts with neural responses during reaching movements, which preferentially track time-varying movement kinematics of the arm, such as velocity and speed of the limb, rather than its time-varying postural configuration. These results suggest different representations of arm and hand movements suited to the different functional roles of these two effectors.

Reorganization of finger covariation patterns represented in the corticospinal system by learning of a novel movement irrelevant to common daily movements

How dexterous finger movements are acquired by the nervous system is a fundamental question in the neuroscience field. Previous studies have demonstrated that finger movements can be decomposed into finger covariation patterns, and these patterns are represented in the corticospinal system. However, it remains unclear how such covariation patterns represented in the corticospinal system develop during the acquisition of novel finger movements. In this study, each subject learned to perform a novel finger movement, which was mapped to a region outside the movement subspace spanned by common finger movements seen in daily life, through a custom task. After subjects practiced the task, we detected changes in the finger covariation patterns derived from artificially (transcranial magnetic stimulation) evoked finger joint movements. The artificially evoked movement-derived patterns seen after the training period were associated with both the novel and common finger movements. Regarding the patterns extracted from the artificially evoked movements, the number required to explain most of the variance in the data was unchanged after the training period. Our results indicate that novel finger movements are acquired through the reorganization of preexisting finger covariation patterns represented in the corticospinal system rather than the development of new patterns. These findings might have implications for the basic mechanism responsible for the development of movement repertories in the nervous system.NEW & NOTEWORTHY Various types of finger movements involve common finger covariation patterns, and these patterns are represented in the corticospinal system. Here we examined how a novel finger covariation pattern is acquired in that system through training of a novel finger movement that is irrelevant to common finger movements. Using transcranial magnetic stimulation, we found that the preexisting patterns that contribute to finer control of finger movements are rapidly reorganized to encode the novel pattern through the training.

Skin Stretch Haptic Feedback to Convey Closure Information in Anthropomorphic, Under-Actuated Upper Limb Soft Prostheses

Restoring hand function in individuals with upper limb loss is a challenging task, made difficult by the complexity of human hands from both a functional and sensory point of view. Users of commercial prostheses, even sophisticated devices, must visually attend to the hand to know its state, since in most cases they are not provided with any direct sensory information. Among the different types of haptic feedback that can be delivered, particularly information on hand opening is likely to reduce the requirement of constant visual attention. In recent years, there has been a trend of using underactuated, compliant multi-fingered hands as upper limb prostheses, in part due to their simplicity and ease of use attributed to low degree-of-freedom (d.o.f.) actuation. The trend toward underactuation encourages the design of one d.o.f. haptic devices to provide intuitive sensory feedback from the prosthesis. However, mapping the closure of a multi-d.o.f. prosthetic hand to a simple and intuitive haptic cue is not a trivial task. In this paper, we explore the use of a one d.o.f. skin stretch haptic device, the rice haptic rocker, to provide intuitive proprioceptive feedback indicating overall hand closure of an underactuated prosthesis. The benefits and challenges of the system are assessed in multi-tasking and reduced vision scenarios for an object-size discrimination task, in an effort to simulate challenges in daily life, and are compared against the haptic resolution of the device using the just noticeable difference. Finally, an evaluation done with a prosthesis user, in the form of a truncated version of the Activities Measure for Upper Limb Amputees (AM-ULA), shows possible benefits of the addition of haptic feedback in tasks with reduced visual attention.

A Physics-based Virtual Reality Environment to Quantify Functional Performance of Upper-limb Prostheses

Usability of upper-limb prostheses remains to be a challenge due to the complexity of hand-object interactions in activities of daily living. Functional evaluation is critical for the optimization of prosthesis performance during device design and parameter tuning phase. Therefore, we implemented a low-cost physics-based virtual reality environment (VRE) capable of simulating wide range of object grasping and manipulation tasks to enable human-in-the-loop optimization. Importantly, our novel VRE can assess user performance quantitatively using movement kinematics and interaction forces. We present a preliminary experiment to validate our VRE. Four able-bodied subjects performed object transfer tasks with a simulated myoelectric one DoF soft-synergy prosthetic hand, while wearing braces to restrain different levels of wrist motion. We found that the task completion time was similar across conditions, however limited wrist pronation led to more shoulder compensatory motion whereas challenging object orientation caused more torso compensatory motion.

Augmented manipulation ability in humans with six-fingered hands

Neurotechnology attempts to develop supernumerary limbs, but can the human brain deal with the complexity to control an extra limb and yield advantages from it? Here, we analyzed the neuromechanics and manipulation abilities of two polydactyly subjects who each possess six fingers on their hands. Anatomical MRI of the supernumerary finger (SF) revealed that it is actuated by extra muscles and nerves, and fMRI identified a distinct cortical representation of the SF. In both subjects, the SF was able to move independently from the other fingers. Polydactyly subjects were able to coordinate the SF with their other fingers for more complex movements than five fingered subjects, and so carry out with only one hand tasks normally requiring two hands. These results demonstrate that a body with significantly more degrees-of-freedom can be controlled by the human nervous system without causing motor deficits or impairments and can instead provide superior manipulation abilities.

Kinematic synergies of hand grasps: a comprehensive study on a large publicly available dataset

Background

Hand grasp patterns require complex coordination. The reduction of the kinematic dimensionality is a key process to study the patterns underlying hand usage and grasping. It allows to define metrics for motor assessment and rehabilitation, to develop assistive devices and prosthesis control methods. Several studies were presented in this field but most of them targeted a limited number of subjects, they focused on postures rather than entire grasping movements and they did not perform separate analysis for the tasks and subjects, which can limit the impact on rehabilitation and assistive applications. This paper provides a comprehensive mapping of synergies from hand grasps targeting activities of daily living. It clarifies several current limits of the field and fosters the development of applications in rehabilitation and assistive robotics.

Methods

In this work, hand kinematic data of 77 subjects, performing up to 20 hand grasps, were acquired with a data glove (a 22-sensor CyberGlove II data glove) and analyzed. Principal Component Analysis (PCA) and hierarchical cluster analysis were used to extract and group kinematic synergies that summarize the coordination patterns available for hand grasps.

Results

Twelve synergies were found to account for > 80% of the overall variation. The first three synergies accounted for more than 50% of the total amount of variance and consisted of: the flexion and adduction of the Metacarpophalangeal joint (MCP) of fingers 3 to 5 (synergy #1), palmar arching and flexion of the wrist (synergy #2) and opposition of the thumb (synergy #3). Further synergies refine movements and have higher variability among subjects.

Conclusion

Kinematic synergies are extracted from a large number of subjects (77) and grasps related to activities of daily living (20). The number of motor modules required to perform the motor tasks is higher than what previously described. Twelve synergies are responsible for most of the variation in hand grasping. The first three are used as primary synergies, while the remaining ones target finer movements (e.g. independence of thumb and index finger). The results generalize the description of hand kinematics, better clarifying several limits of the field and fostering the development of applications in rehabilitation and assistive robotics.

Posture similarity index: a method to compare hand postures in synergy space

Background

The human hand can perform a range of manipulation tasks, from holding a pen to holding a hammer. The central nervous system (CNS) uses different strategies in different manipulation tasks based on task requirements. Attempts to compare postures of the hand have been made for use in robotics and animation industries. In this study, we developed an index called the posture similarity index to quantify the similarity between two human hand postures.

Methods

Twelve right-handed volunteers performed 70 postures, and lifted and held 30 objects (total of 100 different postures, each performed five times). A 16-sensor electromagnetic tracking system captured the kinematics of individual finger phalanges (segments). We modeled the hand as a 21-DoF system and computed the corresponding joint angles. We used principal component analysis to extract kinematic synergies from this 21-DoF data. We developed a posture similarity index (PSI), that represents the similarity between posture in the synergy (Principal component) space. First, we tested the performance of this index using a synthetic dataset. After confirming that it performs well with the synthetic dataset, we used it to analyze the experimental data. Further, we used PSI to identify postures that are “representative” in the sense that they have a greater overlap (in synergy space) with a large number of postures.

Results

Our results confirmed that PSI is a relatively accurate index of similarity in synergy space both with synthetic data and real experimental data. Also, more special postures than common postures were found among “representative” postures.

Conclusion

We developed an index for comparing posture similarity in synergy space and demonstrated its utility by using synthetic dataset and experimental dataset. Besides, we found that “special” postures are actually “special” in the sense that there are more of them in the “representative” postures as identified by our posture similarity index.

Exploring representations of human grasping in neural, muscle and kinematic signals

Movement covariates, such as electromyographic or kinematic activity, have been proposed as candidates for the neural representation of hand control. However, it remains unclear how these movement covariates are reflected in electroencephalographic (EEG) activity during different stages of grasping movements. In this exploratory study, we simultaneously acquired EEG, kinematic and electromyographic recordings of human subjects performing 33 types of grasps, yielding the largest such dataset to date. We observed that EEG activity reflected different movement covariates in different stages of grasping. During the pre-shaping stage, centro-parietal EEG in the lower beta frequency band reflected the object's shape and size, whereas during the finalization and holding stages, contralateral parietal EEG in the mu frequency band reflected muscle activity. These findings contribute to the understanding of the temporal organization of neural grasping patterns, and could inform the design of noninvasive neuroprosthetics and brain-computer interfaces with more natural control.

Hand-Exoskeleton Assisted Progressive Neurorehabilitation using Impedance Adaptation based Challenge Level Adjustment Method

This paper presents an underactuated design of a robotic hand exoskeleton and a challenge based neurorehabilitation strategy. The exoskeleton is designed to reproduce natural human fingertip paths during extension and grasping, keeping minimal kinematic complexity. It facilitates an impedance adaptation based trigged assistance control strategy by a switching between active non-assist and passive assistance modes. In active non-assist mode, the exoskeleton motion follows the applied fingertip forces based on an impedance model. If the applied fingertip forces are inadequate, the passive assistance mode is triggered. The impedance parameters are updated at regular intervals based on the user performance, to implement a challenge based rehabilitation strategy. A six-week long hand therapy, conducted on four chronic stroke patients results in significant (p-value<0.05) increase in force generation capacity and decrease (p-value<0.05) in the required assistance. Also, there was a significant (p-value<0.05) increase in the system impedance parameters which adequately challenged the patients. The change in the Action-Research-Arm-Test (ARAT) scores from baseline are also found to be significant (p-value<0.05) and beyond the minimal clinically important difference (MCID) limit. Thus the results prove that the proposed control strategy with has the potential to be a clinically effective solution for personalized rehabilitation of poststroke hand functionality.

Muscle Synergy Analysis of a Hand-Grasp Dataset: A Limited Subset of Motor Modules May Underlie a Large Variety of Grasps

Background: Kinematic and muscle patterns underlying hand grasps have been widely investigated in the literature. However, the identification of a reduced set of motor modules, generalizing across subjects and grasps, may be valuable for increasing the knowledge of hand motor control, and provide methods to be exploited in prosthesis control and hand rehabilitation.

Methods: Motor muscle synergies were extracted from a publicly available database including 28 subjects, executing 20 hand grasps selected for daily-life activities. The spatial synergies and temporal components were analyzed with a clustering algorithm to characterize the patterns underlying hand-grasps.

Results: Motor synergies were successfully extracted on all 28 subjects. Clustering orders ranging from 2 to 50 were tested. A subset of ten clusters, each one represented by a spatial motor module, approximates the original dataset with a mean maximum error of 5% on reconstructed modules; however, each spatial synergy might be employed with different timing and recruited at different grasp stages. Two temporal activation patterns are often recognized, corresponding to the grasp/hold phase, and to the pre-shaping and release phase.

Conclusions: This paper presents one of the biggest analysis of muscle synergies of hand grasps currently available. The results of 28 subjects performing 20 different grasps suggest that a limited number of time dependent motor modules (shared among subjects), correctly elicited by a control activation signal, may underlie the execution of a large variety of hand grasps. However, spatial synergies are not strongly related to specific motor functions but may be recruited at different stages, depending on subject and grasp. This result can lead to applications in rehabilitation and assistive robotics.

Differences in EMG Burst Patterns During Grasping Dexterity Tests and Activities of Daily Living

The aim of this study was to characterize the muscle activation patterns which underlie the performance of two commonly used grasping patterns and compare the characteristics of such patterns during dexterity tests and activities of daily living. EMG of flexor digitorum and extensor digitorum were monitored from 6 healthy participants as they performed three tasks related to activities of daily living (picking up a coin, drinking from a cup, feeding with a spoon) and three dexterity tests (Variable Dexterity Test-Precision, Variable Dexterity Test-Cylinder, Purdue Pegboard Test). A ten-camera motion capture system was used to simultaneously acquire kinematics of index and middle fingers. Spatiotemporal aspects of the EMG signals were analyzed and compared to metacarpophalangeal joint angle of index and middle fingers. The work has shown that a common rehabilitation test such as the Purdue Pegboard test is a poor representation of the muscle activation patterns for activities of daily living. EMG and joint angle patterns from the Variable Dexterity Tests which has been designed to more accurately reflect a range of ADl's were consistently comparable with tasks requiring precision and cylinder grip, reaffirming the importance of object size and shape when attempting to accurately assess hand function.

HapPro: A Wearable Haptic Device for Proprioceptive Feedback

OBJECTIVE

Myoelectric hand prostheses have reached a considerable technological level and gained an increasing attention in assistive robotics. However, their abandonment rate remains high, with unintuitive control and lack of sensory feedback being major causes. Among the different types of sensory information, proprioception, e.g., information on hand aperture, is crucial to successfully perform everyday actions. Despite the many attempts in literature to restore and convey this type of feedback, much remains to be done to close the action-perception loop in prosthetic devices.

METHODS

With this as motivation, in this paper we introduce HapPro, a wearable, noninvasive haptic device that can convey proprioceptive information for a prosthetic hand. The device was used with an under-actuated, simple to control anthropomorphic robotic hand, providing information about hand aperture by mapping it to the position of a wheel that can run on the user's forearm. Tests with 43 able bodied subjects and one amputee subject were conducted in order to quantify the effectiveness of HapPro as a feedback device.

RESULTS

HapPro provided a good level of accuracy for item discrimination. Participants also reported the device to be intuitive and effective in conveying proprioceptive cues. Similar results were obtained in the proof-of-concept experiment with an amputee subject.

CONCLUSIONS

Results show that HapPro is able to convey information on the opening of a prosthetic hand in a noninvasive way.

SIGNIFICANCE

Using this device for proprioceptive feedback could improve usability of myoelectric prostheses, potentially reducing abandonment and increasing quality of life for their users.

State anxiety disorganizes finger movements during musical performance

Skilled performance, in many situations, exposes an individual to psychological stress and fear, thus triggering state anxiety and compromising motor dexterity. Suboptimal skill execution in people under pressure affects the future career prospects of trained individuals, such as athletes, clinicians, and musicians. However, it has not been elucidated in what manner state anxiety affects multijoint movements and thereby degrades fine motor control. Using principal component analysis of hand kinematics recorded by a data glove during piano performances, we tested whether state anxiety affects the organization of movements of multiple joints or merely constrains the amplitude of the individual joints without affecting joint movement coordination. The result demonstrated changes in the coordination of movements across joints in piano performances by experts under psychological stress. Overall, the change was characterized by reduction of synergistic movements between the finger responsible for the keypress and its adjacent fingers. A regression analysis further identified that the attenuation of the movement covariation between the fingers was associated with an increase in temporal error during performance under pressure. In contrast, neither the maximum nor minimum angles of the individual joints of the hand were susceptible to induced anxiety. These results suggest that degradation of fine motor control under pressure is mediated by incoordination of movements between the fingers in skilled piano performances. NEW & NOTEWORTHY A key issue in neuromuscular control of coordinated movements is how the nervous system organizes multiple degrees of freedom for production of skillful motor behaviors. We found that state anxiety disorchestrates the organization of finger movements so as to decrease synergistic motions between the fingers in musical performance, which degrades fine motor control. The findings are important to shed light on mechanisms underlying loss of motor dexterity under pressure.

Home-based hand rehabilitation after chronic stroke: Randomized, controlled single-blind trial comparing the MusicGlove with a conventional exercise program

Individuals with chronic stroke have limited options for hand rehabilitation at home. Here, we sought to determine the feasibility and efficacy of home-based MusicGlove therapy. Seventeen participants with moderate hand impairment in the chronic phase of stroke were randomized to 3 wk of home-based exercise with either the MusicGlove or conventional tabletop exercises. The primary outcome measure was the change in the Box and Blocks test score from baseline to 1 mo posttreatment. Both groups significantly improved their Box and Blocks test score, but no significant difference was found between groups. The MusicGlove group did exhibit significantly greater improvements than the conventional exercise group in motor activity log quality of movement and amount of use scores 1 mo posttherapy (p = 0.007 and p = 0.04, respectively). Participants significantly increased their use of MusicGlove over time, completing 466 gripping movements per day on average at study end. MusicGlove therapy was not superior to conventional tabletop exercises for the primary end point but was nevertheless feasible and led to a significantly greater increase in self-reported functional use and quality of movement of the impaired hand than conventional home exercises.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; "Influence of Timing on Motor Learning"; NCT01769326; https://clinicaltrials.gov/ct2/show/NCT01769326.

Evidence for sparse synergies in grasping actions

Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) – sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) – sparsity in synergy representation – i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) – a novel view combining both SC and SE – i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks.

Analyzing finger interdependencies during the Purdue Pegboard Test and comparative activities of daily living

STUDY DESIGN

Bench and cross-sectional study.

INTRODUCTION

Information obtained from dexterity tests is an important component of a comprehensive examination of the hand.

PURPOSE OF THE STUDY

To analyze and compare finger interdependencies during the performance of the Purdue Pegboard Test (PBT) and comparative daily tasks.

METHODS

A method based on the optoelectronic kinematic analysis of the precision grip style and on the calculation of cross-correlation coefficients between relevant joint angles, which provided measures of the degree of finger coordination, was conducted on 10 healthy participants performing the PBT and 2 comparative daily living tasks.

RESULTS

Daily tasks showed identifiable interdependencies patterns between the metacarpophalangeal joints of the fingers involved in the grip. Tasks related to activities of daily living resulted in significantly higher cross-correlation coefficients across subjects and movements during the formation and manipulation phases of the tasks (0.7-0.9), whereas the release stage produced significantly lower movement correlation values (0.3-0.7). Contrarily, the formation and manipulation stages of the PBT showed low finger correlation across most subjects (0.2-0.6), whereas the release stage resulted in the highest values for all relevant movements (0.65-0.9).

DISCUSSION

Interdependencies patterns were consistent for the activities of daily living but differ from the patterns observed from the PBT.

CONCLUSIONS

The PBT does not compare well with the whole range of finger movements that account for hand performance during daily tasks.

LEVEL OF EVIDENCE

Not applicable.

Postural Hand Synergies during Environmental Constraint Exploitation

Humans are able to intuitively exploit the shape of an object and environmental constraints to achieve stable grasps and perform dexterous manipulations. In doing that, a vast range of kinematic strategies can be observed. However, in this work we formulate the hypothesis that such ability can be described in terms of a synergistic behavior in the generation of hand postures, i.e., using a reduced set of commonly used kinematic patterns. This is in analogy with previous studies showing the presence of such behavior in different tasks, such as grasping. We investigated this hypothesis in experiments performed by six subjects, who were asked to grasp objects from a flat surface. We quantitatively characterized hand posture behavior from a kinematic perspective, i.e., the hand joint angles, in both pre-shaping and during the interaction with the environment. To determine the role of tactile feedback, we repeated the same experiments but with subjects wearing a rigid shell on the fingertips to reduce cutaneous afferent inputs. Results show the persistence of at least two postural synergies in all the considered experimental conditions and phases. Tactile impairment does not alter significantly the first two synergies, and contact with the environment generates a change only for higher order Principal Components. A good match also arises between the first synergy found in our analysis and the first synergy of grasping as quantified by previous work. The present study is motivated by the interest of learning from the human example, extracting lessons that can be applied in robot design and control. Thus, we conclude with a discussion on implications for robotics of our findings.