A Better Framework for the Assessment of Performance and Stability of Co-Adaptive Myoelectric Systems.

Co-adaptive myoelectric human-machine systems are a fairly recent, but promising, advancement in pattern recognition-based myoelectric control. Their performance and stability, however, are not fully understood due in part to a lack of proper assessment tools. Time-series based analyses are typically used despite the availability of techniques used in other fields that can robustly measure stability and performance. In this research, we leverage the success achieved by lower limb systems to improve the assessment framework of co-adaptive myoelectric systems by exploiting a key feature common between the two systems. The cyclical dynamics found in lower limbs are also apparent in co-adaptive myoelectric systems, allowing us to analyze their behavior using Poincaré maps. A 10-day experiment was designed and conducted to observe the effects of algorithm adaptation and myoelectric experience level on the performance of a co-adaptive myoelectric control system. Through Poincaré maps, we were able to identify learning effects, as well as oscillations and uncertainty in performance. Assessment of these seemingly random variations in performance led to the inference that co-adaptive systems can be chaotic. Modelling co-adaptive myoelectric systems as cyclical leads to the application of an improved framework to better assess and describe their dynamics and performance.

A Comparison of Force-Plate Based Center of Mass Estimation Algorithms.

Estimating horizontal center of mass (CoM) is an important process that is used in the control of self-paced treadmills, as well as in clinical and scientific biomechanical analysis. Many laboratories use motion-capture to estimate CoM, while others use force-plate based estimates, either because they cannot access motion-capture or they do not want to be taxed with post-processing optoelectronic data. Three force-plate derived center of mass estimation algorithms were compared against a benchmark motion-capture technique. Two of them have recently been reported in the literature, and both rely on numerical integration of 2nd-order differential equations. We propose a third technique that uses an algebraic equation to directly relate center of pressure to center of mass without numerical drift. Twenty-four healthy adults participated in a five-minute steady-state walking test to compare these algorithms. The sample-by-sample standard deviation of the three force-plate based algorithms from the motion-capture benchmark algorithm was evaluated. The algebraic technique provided less error than either of the two more common integration techniques (p<0.05). The results of this study support the viability of using only ground reaction forces for self-paced treadmills and also show that a simple algebraic model is preferred to integration approaches. The use of an algebraic estimation simplifies control implementation for self-paced treadmill applications and eliminates the need for event-based drift recalibration.

Optimized control mapping through user-tuned cost of effort, time, and reliability.

Humans consistently coordinate their joints to perform a variety of tasks. Computational motor control theory explains these stereotypical behaviors using optimal control. Several cost functions have been used to explain specific movements, which suggests that the brain optimizes for a combination of costs and just varies their relative weights to perform different tasks. In the case of tunable human-machine interfaces, we hypothesize that the human-machine interface should be optimized according to the costs that the user cares about when making the movement. Here, we study how the relative weights of individual cost functions in a composite movement cost affect the optimal control signal produced by the user and the mapping between the user's control signals and the machine's output, using prosthesis control as a specific example. This framework was tested by building a hierarchical optimization model that independently optimized for the user control signal and the virtual dynamics of the device. Our results indicate the feasibility of the approach and show the potential for using such a model in prosthesis tuning. This method could be used to allow clinicians and users to tune their prosthesis based on costs they actually care about; and allow the platforms to be customized for the unique needs of every patient.

Crossmodal congruency effect scores decrease with repeat test exposure.

The incorporation of feedback into a person's body schema is well established. The crossmodal congruency task (CCT) is used to objectively quantify incorporation without being susceptible to experimenter biases. This visual-tactile interference task is used to calculate the crossmodal congruency effect (CCE) score as a difference in response time between incongruent and congruent trials. Here we show that this metric is susceptible to a learning effect that causes attenuation of the CCE score due to repeated task exposure sessions. We demonstrate that this learning effect is persistent, even after a 6 month hiatus in testing. Two mitigation strategies are proposed: 1. Only use CCE scores that are taken after learning has stabilized, or 2. Use a modified CCT protocol that decreases the task exposure time. We show that the modified and shortened CCT protocol, which may be required to meet time or logistical constraints in laboratory or clinical settings, reduced the impact of the learning effect on CCT results. Importantly, the CCE scores from the modified protocol were not significantly more variable than results obtained with the original protocol. This study highlights the importance of considering exposure time to the CCT when designing experiments and suggests two mitigation strategies to improve the utility of this psychophysical assessment.

Joint Speed Discrimination and Augmentation For Prosthesis Feedback.

Sensory feedback is critical in fine motor control, learning, and adaptation. However, robotic prosthetic limbs currently lack the feedback segment of the communication loop between user and device. Sensory substitution feedback can close this gap, but sometimes this improvement only persists when users cannot see their prosthesis, suggesting the provided feedback is redundant with vision. Thus, given the choice, users rely on vision over artificial feedback. To effectively augment vision, sensory feedback must provide information that vision cannot provide or provides poorly. Although vision is known to be less precise at estimating speed than position, no work has compared speed precision of biomimetic arm movements. In this study, we investigated the uncertainty of visual speed estimates as defined by different virtual arm movements. We found that uncertainty was greatest for visual estimates of joint speeds, compared to absolute rotational or linear endpoint speeds. Furthermore, this uncertainty increased when the joint reference frame speed varied over time, potentially caused by an overestimation of joint speed. Finally, we demonstrate a joint-based sensory substitution feedback paradigm capable of significantly reducing joint speed uncertainty when paired with vision. Ultimately, this work may lead to improved prosthesis control and capacity for motor learning.

Author Correction: Assessing the quality of supplementary sensory feedback using the crossmodal congruency task.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Assessing the quality of supplementary sensory feedback using the crossmodal congruency task.

Advanced neural interfaces show promise in making prosthetic limbs more biomimetic and ultimately more intuitive and useful for patients. However, approaches to assess these emerging technologies are limited in scope and the insight they provide. When outfitting a prosthesis with a feedback system, such as a peripheral nerve interface, it would be helpful to quantify its physiological correspondence, i.e. how well the prosthesis feedback mimics the perceived feedback in an intact limb. Here we present an approach to quantify this aspect of feedback quality using the crossmodal congruency effect (CCE) task. We show that CCE scores are sensitive to feedback modality, an important characteristic for assessment purposes, but are confounded by the spatial separation between the expected and perceived location of a stimulus. Using data collected from 60 able-bodied participants trained to control a bypass prosthesis, we present a model that results in adjusted-CCE scores that are unaffected by percept misalignment which may result from imprecise neural stimulation. The adjusted-CCE score serves as a proxy for a feedback modality's physiological correspondence or 'naturalness'. This quantification approach gives researchers a tool to assess an aspect of emerging augmented feedback systems that is not measurable with current motor assessments.

Illusory movement perception improves motor control for prosthetic hands.

To effortlessly complete an intentional movement, the brain needs feedback from the body regarding the movement's progress. This largely nonconscious kinesthetic sense helps the brain to learn relationships between motor commands and outcomes to correct movement errors. Prosthetic systems for restoring function have predominantly focused on controlling motorized joint movement. Without the kinesthetic sense, however, these devices do not become intuitively controllable. We report a method for endowing human amputees with a kinesthetic perception of dexterous robotic hands. Vibrating the muscles used for prosthetic control via a neural-machine interface produced the illusory perception of complex grip movements. Within minutes, three amputees integrated this kinesthetic feedback and improved movement control. Combining intent, kinesthesia, and vision instilled participants with a sense of agency over the robotic movements. This feedback approach for closed-loop control opens a pathway to seamless integration of minds and machines.

The effects of control signal noise on simultaneous submovements.

Understanding the stereotypical characteristics of human movement can better inform rehabilitation practices by providing a template of healthy and expected human motor control. Multiplicative noise is inherent in goal-directed movement, such as reaching to grasp an object. Multiplicative noise plays an important role in computational motor control models to help support phenomena such as stereotypical kinematic profiles in time-constrained and unconstrained tasks. Most tasks are not carried out along an isolated degree-of-freedom (DOF), and modelling the contribution of noise can be difficult. Here we add a noise term proportional to the degree of simultaneity for multi-DOF tasks to approximate the contribution of system noise. With this approach, we are able to explain previously observed motor phenomena including the presence of submovements in multi-DOF tasks, and the transition from simultaneous to sequential control of joints without the presence of feedback. Inclusion of a simultaneous multiplicative noise term presents a simple theory that expands on previous research in order to describe characteristics of multiple-DOF movements. This model can be used as a guide to compare healthy human motor control to the movements of patients receiving rehabilitation in an effort to improve their motor planning.

Joint-based velocity feedback to virtual limb dynamic perturbations.

Despite significant research developing myoelectric prosthesis controllers, many amputees have difficulty controlling their devices due in part to reduced sensory feedback. Many attempts at providing supplemental sensory feedback have not significantly aided control. We hypothesize this is because the feedback provided contains redundant information already provided by vision. However, whereas vision provides egocentric, position-based feedback, sensory feedback tied to joint coordinates may provide information complementary to vision. In this study, we tested if providing audio feedback of joint velocities can improve performance and adaptation to dynamic perturbations while controlling a virtual limb. While subjects performed time-controlled center-out reaches, we perturbed the dynamics of the system and measured the rate subjects adapted to this change. Our results suggest that initial errors were reduced in the presence of audio feedback, and we theorize this is due to subjects identifying the perturbed limb dynamics sooner. We also noted other possible benefits including improved muscle activation detection.

A third arm - Design of a bypass prosthesis enabling incorporation.

A variety of factors affect the performance of a person using a myoelectric prosthesis, including increased control noise, reduced sensory feedback, and muscle fatigue. Many studies use able-bodied subjects to control a myoelectric prosthesis using a bypass socket in order to make comparisons to movements made with intact limbs. Depending on the goals of the study, this approach can also allow for greater subject numbers and more statistical power in the analysis of the results. As we develop assessment tools and techniques to evaluate how peripheral nerve interfaces impact prosthesis incorporation, involving normally limbed subjects in the studies becomes challenging. We have designed a novel bypass prosthesis to allow for the assessment of prosthesis incorporation in able-bodied subjects. Incorporation of a prosthetic hand worn by a normally limbed subject requires that the prosthesis is a convincing, functional extension of their own body. We present the design and development of the bypass prosthesis with special attention to mounting position and angle of the prosthetic hand, the quality of the control system and the responsiveness of the feedback. The bypass prosthesis has been fitted with a myoelectrically-controlled hand that has been instrumented to measure the forces applied to the thumb, index, and middle fingers. The prosthetic hand was mounted on the bypass socket such that it is the same length as the subject's intact limb but at a medial rotation angle of 20° to prevent visual occlusion of the prosthetic hand. Force feedback is provided in the form of electrical stimulation, vibration, or force applied to the intact limb with milliseconds of delay. Preliminary data results from a cross-modal congruency task are included showing evidence of prosthesis incorporation in able-bodied subjects. This bypass will allow able-bodied subjects to participate in research studies that require the use of a prosthetic limb while also allowing the subjects to sense that the prosthesis is an extension of the body.

Design and evaluation of voluntary opening and voluntary closing prosthetic terminal device.

Body-powered prostheses use a cable-operated system to generate forces and move prosthetic joints. However, this control system can only generate forces in one direction, so current body-powered prehensor designs allow the user either to voluntarily open or voluntarily close the tongs. Both voluntary opening (VO) and voluntary closing (VC) modes of operation have advantages for certain tasks, and many end-users desire a terminal device that can switch between the two modes. However, such a terminal device must maintain the same thumb position (i.e., point of Bowden cable attachment) and movement direction in both modes in order to avoid the need to readjust the harness after every mode switch. In this study, we demonstrate a simple design that fulfills these requirements while allowing the user to switch easily between modes. We describe the design concept, describe a rugged split-hook prototype, provide specifications (size, weight, efficiency, etc.), and present a pilot study in which five subjects with intact arms and two subjects with amputation used the VO and VC split-hook prehensor to perform the Southampton Hand Assessment Procedure. Subjects performed an average of 4 to 7 (+/- 0.2) points better when they could choose to switch between modes on a task-by-task basis than when they were constrained to using only VO or VC modes.

Importance of proximal A2 and A4 pulleys to maintaining kinematics in the hand: a biomechanical study.

PURPOSE: The A2 and A4 pulleys have been shown to be important in finger flexor tendon function. Other authors have suggested either reconstruction or venting of portions of these pulleys in an attempt to preserve finger function in certain clinical situations. This study examines the effects of partial incision of these pulleys on finger flexion kinematics and biomechanics. METHODS: The index and ring fingers of 16 cadaveric hands were studied. The flexor digitorum profundus tendon was isolated and attached to a computer driven servo-motor. Micro-potentiometers measured flexion angles of the metacarpophalangeal, proximal inter-phalangeal and distal inter-phalangeal joints. Joint inertial torques were calculated making use of this experimental kinematic data. RESULTS: Proximal 50 % incisions of either the A2 or the A4 pulleys resulted in a statistically significant decrease in overall finger motion. This effect was greatest in the proximal inter-phalangeal joint, with a decrease in joint motion, as well as an earlier time to initiation of motion. These changes in finger motion were more pronounced with A2 pulley incision than they were with A4 pulley incision, but the changes were statistically significant in either case. No significant changes in joint inertial torques were shown. CONCLUSIONS: Our data provides evidence to the importance of the proximal portions of the A2 and A4 pulleys, and may support partial distal incision of these pulleys in certain clinical situations.