Dextrous hands: human, prosthetic, and robotic

Longitudinal multiparametric MRI of traumatic spinal cord injury in animal models

Multi-parametric MRI (mpMRI) technology enables non-invasive and quantitative assessments of the structural, molecular, and functional characteristics of various neurological diseases. Despite the recognized importance of studying spinal cord pathology, mpMRI applications in spinal cord research have been somewhat limited, partly due to technical challenges associated with spine imaging. However, advances in imaging techniques and improved image quality now allow longitudinal investigations of a comprehensive range of spinal cord pathological features by exploiting different endogenous MRI contrasts. This review summarizes the use of mpMRI techniques including blood oxygenation level-dependent (BOLD) functional MRI (fMRI), diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST) MRI in monitoring different aspects of spinal cord pathology. These aspects include cyst formation and axonal disruption, demyelination and remyelination, changes in the excitability of spinal grey matter and the integrity of intrinsic functional circuits, and non-specific molecular changes associated with secondary injury and neuroinflammation. These approaches are illustrated with reference to a nonhuman primate (NHP) model of traumatic cervical spinal cord injuries (SCI). We highlight the benefits of using NHP SCI models to guide future studies of human spinal cord pathology, and demonstrate how mpMRI can capture distinctive features of spinal cord pathology that were previously inaccessible. Furthermore, the development of mechanism-based MRI biomarkers from mpMRI studies can provide clinically useful imaging indices for understanding the mechanisms by which injured spinal cords progress and repair. These biomarkers can assist in the diagnosis, prognosis, and evaluation of therapies for SCI patients, potentially leading to improved outcomes.

Design-validation of a hand exoskeleton using musculoskeletal modeling

Exoskeletons are progressively reaching homes and workplaces, allowing interaction with virtual environments, remote control of robots, or assisting human operators in carrying heavy loads. Their design is however still a challenge as these robots, being mechanically linked to the operators who wear them, have to meet ergonomic constraints besides usual robotic requirements in terms of workspace, speed, or efforts. They have in particular to fit the anthropometry and mobility of their users. This traditionally results in numerous prototypes which are progressively fitted to each individual person. In this paper, we propose instead to validate the design of a hand exoskeleton in a fully digital environment, without the need for a physical prototype. The purpose of this study is thus to examine whether finger kinematics are altered when using a given hand exoskeleton. Therefore, user specific musculoskeletal models were created and driven by a motion capture system to evaluate the fingers' joint kinematics when performing two industrial related tasks. The kinematic chain of the exoskeleton was added to the musculoskeletal models and its compliance with the hand movements was evaluated. Our results show that the proposed exoskeleton design does not influence fingers' joints angles, the coefficient of determination between the model with and without exoskeleton being consistently high (R²¯=0.93) and the nRMSE consistently low (nRMSE¯ = 5.42°). These results are promising and this approach combining musculoskeletal and robotic modeling driven by motion capture data could be a key factor in the ergonomics validation of the design of orthotic devices and exoskeletons prior to manufacturing.

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation

After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required-a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery.

Analysis of hand contact areas and interaction capabilities during manipulation and exploration

Manual human-computer interfaces for virtual reality are designed to allow an operator interacting with a computer simulation as naturally as possible. Dexterous haptic interfaces are the best suited for this goal. They give intuitive and efficient control on the environment with haptic and tactile feedback. This paper is aimed at helping in the choice of the interaction areas to be taken into account in the design of such interfaces. The literature dealing with hand interactions is first reviewed in order to point out the contact areas involved in exploration and manipulation tasks. Their frequencies of use are then extracted from existing recordings. The results are gathered in an original graphical interaction map allowing for a simple visualization of the way the hand is used, and compared with a map of mechanoreceptors densities. Then an interaction tree, mapping the relative amount of actions made available through the use of a given contact area, is built and correlated with the losses of hand function induced by amputations. A rating of some existing haptic interfaces and guidelines for their design are finally achieved to illustrate a possible use of the developed graphical tools.

Naturalistic approaches to sensorimotor control

Human sensorimotor control has been predominantly studied using fixed tasks performed under laboratory conditions. This approach has greatly advanced our understanding of the mechanisms that integrate sensory information and generate motor commands during voluntary movement. However, experimental tasks necessarily restrict the range of behaviors that are studied. Moreover, the processes studied in the laboratory may not be the same processes that subjects call upon during their everyday lives. Naturalistic approaches thus provide an important adjunct to traditional laboratory-based studies. For example, wearable self-contained tracking systems can allow subjects to be monitored outside the laboratory, where they engage spontaneously in natural everyday behavior. Similarly, advances in virtual reality technology allow laboratory-based tasks to be made more naturalistic. Here, we review naturalistic approaches, including perspectives from psychology and visual neuroscience, as well as studies and technological advances in the field of sensorimotor control.

Information capacity of the thumb and the index finger in communication

Due to its large number of degrees of freedom and extensive connection to the brain, the human hand has been used to create channels of communication for a variety of human-machine systems. However, a fundamental question about the hand channel is still unanswered: what is its information capacity? This study aims to provide quantitative indication of effectiveness of the hand as a communication channel. We estimated that per gesture, the thumb and the index finger may deliver at most 10 and 7 bits of information, respectively. Based on this, we derived an upper bound for the information capacity of the hand in gesture-based communication: 150 b/s. Knowing this bound is critical to evaluating the potential and limitation of the hand channel for various forms of human-machine interactions.

The statistics of natural hand movements

Humans constantly use their hands to interact with the environment and they engage spontaneously in a wide variety of manual activities during everyday life. In contrast, laboratory-based studies of hand function have used a limited range of predefined tasks. The natural movements made by the hand during everyday life have thus received little attention. Here, we developed a portable recording device that can be worn by subjects to track movements of their right hand as they go about their daily routine outside of a laboratory setting. We analyse the kinematic data using various statistical methods. Principal component analysis of the joint angular velocities showed that the first two components were highly conserved across subjects, explained 60% of the variance and were qualitatively similar to those reported in previous studies of reach-to-grasp movements. To examine the independence of the digits, we developed a measure based on the degree to which the movements of each digit could be linearly predicted from the movements of the other four digits. Our independence measure was highly correlated with results from previous studies of the hand, including the estimated size of the digit representations in primary motor cortex and other laboratory measures of digit individuation. Specifically, the thumb was found to be the most independent of the digits and the index finger was the most independent of the fingers. These results support and extend laboratory-based studies of the human hand.

Dielectric elastomers as actuators for upper limb prosthetics: challenges and opportunities

Recent research has indicated that consumers of upper limb prostheses desire lighter-weight, anthropomorphic devices. The potential of dielectric elastomer (DE) actuators to better meet the design priorities of prosthesis users is explored. Current challenges are critically reviewed with respect to (1) durability, (2) precision control, (3) energy consumption, and (4) anthropomorphic implementation. The key points arising from the literature review are illustrated with empirical examples of the strain performance and durability of one of the most popular DEs, VHB 4910. Practical application of DE actuators in powered upper extremity prosthetics is at present impeded by poor durability and susceptibility to air-borne contaminants, unreliable control owing to viscoelasticity, hysteresis, stress relaxation and creep mechanisms, high voltage requirements, and insufficient stress and strain performance within the confines of anthropomorphic size, weight, and function. Our review suggests that the implementation of DE actuators in powered upper extremity prosthetics is not feasible at present but worthy of reevaluation as the materials advance.

Continuous shared control for stabilizing reaching and grasping with brain-machine interfaces

Research on brain-machine interfaces (BMI's) is directed toward enabling paralyzed individuals to manipulate their environment through slave robots. Even for able-bodied individuals, using a robot to reach and grasp objects in unstructured environments can be a difficult telemanipulation task. Controlling the slave directly with neural signals instead of a hand-master adds further challenges, such as uncertainty about the intended trajectory coupled with a low update rate for the command signal. To address these challenges, a continuous shared control (CSC) paradigm is introduced for BMI where robot sensors produce reflex-like reactions to augment brain-controlled trajectories. To test the merits of this approach, CSC was implemented on a 3-degree-of-freedom robot with a gripper bearing three co-located range sensors. The robot was commanded to follow eighty-three reach-and-grasp trajectories estimated previously from the outputs of a population of neurons recorded from the brain of a monkey. Five different levels of sensor-based reflexes were tested. Weighting brain commands 70% and sensor commands 30% produced the best task performance, better than brain signals alone by more than seven-fold. Such a marked performance improvement in this test case suggests that some level of machine autonomy will be an important component of successful BMI systems in general.

Electroactive polymeric sensors in hand prostheses: bending response of an ionic polymer metal composite

In stark contrast to the inspiring functionality of the natural hand, limitations of current upper limb prostheses stemming from marginal feedback control, challenges of mechanical design, and lack of sensory capacity, are well-established. This paper provides a critical review of current sensory systems and the potential of a selection of electroactive polymers for sensory applications in hand prostheses. Candidate electroactive polymers are reviewed in terms of their relevant advantages and disadvantages, together with their current implementation in related applications. Empirical analysis of one of the most novel electroactive polymers, ionic polymer metal composites (IPMC), was conducted to demonstrate its potential for prosthetic applications. With linear responses within the operating range typical of hand prostheses, bending angles, and bending rates were accurately measured with 4.4+/-2.5 and 4.8+/-3.5% error, respectively, using the IPMC sensors. With these comparable error rates to traditional resistive bend sensors and a wide range of sensitivities and responses, electroactive polymers offer a promising alternative to more traditional sensory approaches. Their potential role in prosthetics is further heightened by their flexible and formable structure, and their ability to act as both sensors and actuators.

Manual control and tracking--a human factor analysis relevant for beating heart surgery

Manual control and tracking are fundamental to human factors and define a metric framework which determines the limits of surgical precision. This review provides a brief analysis of factors that are relevant for targeted motions. Knowing and accepting the limitations of human performance may help to optimize performance in off-pump surgery.

A biomimetic controller for a multifinger prosthesis

A novel controller for a multifinger hand prosthesis was developed and tested to measure its accuracy and performance in transducing volitional signals for individual "phantom" fingers. Pneumatic sensors were fabricated from open-cell polymeric foam, and were interposed between the prosthetic socket and superficial extrinsic tendons associated with individual finger flexion. Test subjects were prompted to move individual fingers or combinations thereof to execute either taps or grasps. Sensor outputs were processed by a computer that controlled motions of individual fingers on a mechanical prosthesis. Trials on three upper-limb amputees showed that after brief training sessions, the TAP controller was effective at producing voluntary flexions of individual fingers and grasping motions. Signal energies were between 5 and 25 dB relative to noise from all sources, including adjacent sensors, indicating high degrees of both sensitivity and specificity for tendon-associated transduction. Finger flexions at up to three repetitions per second, and rhythmic tapping of sequential fingers were readily transduced. One amputee subject was able to play a short piano piece with three fingers, at approximately one-quarter normal tempo. TAP sensors responded linearly to graded forces from individual fingers, indicating proportional force control. Our results demonstrate the feasibility of restoring some degree of finger dexterity by noninvasive sensing of extrinsic tendons.

Are there critical bands in kinesthesia?

The effect of changing the bandwidth of noise on the ability of human subjects to detect a 10-Hz sinusoidal movement signal was measured in two experiments. The objective of these studies was to investigate whether critical bands exist for the kinesthetic system, as has been demonstrated for the auditory and tactile systems. It was found that subjects' ability to detect a 10-Hz sinusoidal movement stimulus embedded in noise was not influenced by the bandwidth of the noise over a range of 4-10 Hz. These findings suggest that, if a critical filter does exist for this system, it would have to be greater than 10 Hz.