Functional reaching is impaired in dystonia. Here, we analyze upper extremity kinematics to quantify timing and coordination abnormalities during unimanual reach-to-grasp movements in individuals with childhood-onset unilateral wrist dystonia. Kinematics were measured during movements of both upper limbs in a patient group (n = 11, age = 17.5 ± 5 years), and a typically developing control group (n = 9, age = 16.6 ± 5 years). Hand aperture was computed to study the coordination of reach and grasp. Time-varying joint synergies within one upper limb were calculated using a novel technique based on principal component analysis to study intra-limb coordination.
In the non-dominant arm, results indicate reduced coordination between reach and grasp in patients who could not lift the grasped object compared to those who could lift it. Lifters exhibit incoordination in distal upper extremity joints later in the movement and non-lifters lacked coordination throughout the movement and in the whole upper limb. The amount of atypical coordination correlates with dystonia severity in patients. Reduced coordination during movement may reflect deficits in the execution of simultaneous movements, motor planning, or muscle activation. Rehabilitation efforts can focus on particular time points when kinematic patterns deviate abnormally to improve functional reaching in individuals with childhood-onset dystonia.
Cerebral palsy; coordination; dystonia; kinematics; reach-to-grasp
This study presents a progressive FastICA peel-off (PFP) framework for high density surface electromyogram (EMG) decomposition. The novel framework is based on a shift-invariant model for describing surface EMG. The decomposition process can be viewed as progressively expanding the set of motor unit spike trains, which is primarily based on FastICA. To overcome the local convergence of FastICA, a “peel off” strategy (i.e. removal of the estimated motor unit action potential (MUAP) trains from the previous step) is used to mitigate the effects of the already identified motor units, so more motor units can be extracted. Moreover, a constrained FastICA is applied to assess the extracted spike trains and correct possible erroneous or missed spikes. These procedures work together to improve the decomposition performance. The proposed framework was validated using simulated surface EMG signals with different motor unit numbers (30, 70, 91) and signal to noise ratios (SNRs) (20, 10, 0 dB). The results demonstrated relatively large numbers of extracted motor units and high accuracies (high F1-scores). The framework was also tested with 111 trials of 64-channel electrode array experimental surface EMG signals during the first dorsal interosseous (FDI) muscle contraction at different intensities. On average 14.1 ± 5.0 motor units were identified from each trial of experimental surface EMG signals.
FastICA; constrained FastICA; high density surface EMG; decomposition; motor unit spike train; MUAP waveform estimation
Clinically available myoelectric control does not enable simultaneous proportional control of prosthetic degrees of freedom. Multiple studies have proposed systems that provide simultaneous control, though few have investigated whether subjects voluntarily use simultaneous control or how they implement it. Additionally, few studies have explicitly evaluated the effect of providing proportional velocity control. The objective of this study was to evaluate factors influencing when and how subjects use simultaneous myoelectric control, including the ability to proportionally control the velocity and the required task precision. Five able-bodied subjects used simultaneous myoelectric control systems with and without proportional velocity control in a virtual Fitts’ Law task. Though subjects used simultaneous control to a substantial degree when proportional velocity control was present, they used very little simultaneous control when using constant-velocity control. Furthermore, use of simultaneous control varied significantly with target distance and width, reflecting a strategy of using simultaneous control for gross cursor positioning and sequential control for fine corrective movements. These results provide insight into how users take advantage of simultaneous control and highlight the need for real-time evaluation of simultaneous control algorithms, as the potential benefit of providing simultaneous control may be affected by other characteristics of the myoelectric control system.
Prosthesis control; Intramuscular electromyography; Fitts’ Law
In this paper, we analyze the correlations between four clinical measures (Fugl–Meyer upper extremity scale, Motor Activity Log, Action Research Arm Test, and Jebsen-Taylor Hand Function Test) and four robotic measures (smoothness of movement, trajectory error, average number of target hits per minute, and mean tangential speed), used to assess motor recovery. Data were gathered as part of a hybrid robotic and traditional upper extremity rehabilitation program for nine stroke patients. Smoothness of movement and trajectory error, temporally and spatially normalized measures of movement quality defined for point-to-point movements, were found to have significant moderate to strong correlations with all four of the clinical measures. The strong correlations suggest that smoothness of movement and trajectory error may be used to compare outcomes of different rehabilitation protocols and devices effectively, provide improved resolution for tracking patient progress compared to only pre-and post-treatment measurements, enable accurate adaptation of therapy based on patient progress, and deliver immediate and useful feedback to the patient and therapist.
Haptic feedback; motor function recovery; movement intermittency; rehabilitation robotics; stroke measures; therapeutic robots
The inability to maintain balance during varying postural control conditions can lead to falls, a significant cause of mortality and serious injury among older adults. However, our understanding of the underlying dynamical and stochastic processes in human postural control have not been fully explored. To further our understanding of the underlying dynamical processes, we examine a novel conceptual framework for studying human postural control using the center of pressure (COP) velocity autocorrelation function (COP-VAF) and compare its results to Stabilogram Diffusion Analysis (SDA). Eleven healthy young participants were studied under quiet unipedal or bipedal standing conditions with eyes either opened or closed. COP trajectories were analyzed using both the traditional posturographic measure SDA and the proposed COP-VAF. It is shown that the COP-VAF leads to repeatable, physiologically meaningful measures that distinguish postural control differences in unipedal versus bipedal stance trials with and without vision in healthy individuals. More specifically, both a unipedal stance and lack of visual feedback increased initial values of the COP-VAF, magnitude of the first minimum, and diffusion coefficient, particularly in contrast to bipedal stance trials with open eyes. Use of a stochastic postural control model, based on an Ornstein-Uhlenbeck process that accounts for natural weight-shifts, suggests an increase in spring constant and decreased damping coefficient when fitted to experimental data. This work suggests that we can further extend our understanding of the underlying mechanisms behind postural control in quiet stance under varying stance conditions using the COP-VAF and provides a tool for quantifying future neurorehabilitative interventions.
Postural Control Model; Velocity Autocorrelation Function; Center of Pressure; Stochastic Dynamics
This paper presents the pediAnklebot, an impedance-controlled low-friction, backdriveable robotic device developed at the Massachusetts Institute of Technology that trains the ankle of neurologically impaired children of ages 6-10 years old. The design attempts to overcome the known limitations of the lower extremity robotics and the unknown difficulties of what constitutes an appropriate therapeutic interaction with children. The robot's pilot clinical evaluation is on-going and it incorporates our recent findings on the ankle sensorimotor control in neurologically intact subjects, namely the speed-accuracy tradeoff, the deviation from an ideally smooth ankle trajectory, and the reaction time. We used these concepts to develop the kinematic and kinetic performance metrics that guided the ankle therapy in a similar fashion that we have done for our upper extremity devices. Here we report on the use of the device in at least 9 training sessions for 3 neurologically impaired children. Results demonstrated a statistically significant improvement in the performance metrics assessing explicit and implicit motor learning. Based on these initial results, we are confident that the device will become an effective tool that harnesses plasticity to guide habilitation during childhood.
Robotic training; sensorimotor therapy; assist-as-needed; cerebral palsy; ankle
P300 spellers can provide a means of communication for individuals with severe neuromuscular limitations. However, its use as an effective communication tool is reliant on high P300 classification accuracies (>70%) to account for error revisions. Error-related potentials (ErrP), which are changes in EEG potentials when a person is aware of or perceives erroneous behavior or feedback, have been proposed as inputs to drive corrective mechanisms that veto erroneous actions by BCI systems. The goal of this study is to demonstrate that training an additional ErrP classifier for a P300 speller is not necessary, as we hypothesize that error information is encoded in the P300 classifier responses used for character selection. We perform offline simulations of P300 spelling to compare ErrP and non-ErrP based corrective algorithms. A simple dictionary correction based on string matching and word frequency significantly improved accuracy (35–185%), in contrast to an ErrP-based method that flagged, deleted and replaced erroneous characters (−47 – 0%). Providing additional information about the likelihood of characters to a dictionary-based correction further improves accuracy. Our Bayesian dictionary-based correction algorithm that utilizes P300 classifier confidences performed comparably (44–416%) to an oracle ErrP dictionary-based method that assumed perfect ErrP classification (43–433%).
Brain–computer interface (BCI); electroencephalogram; error-related potential (ErrP); noisy channel model; P300 speller
Unilateral lower-limb amputees exhibit asymmetry in many gait features, such as ground force, step time, step length, and joint mechanics. Although these asymmetries result from weak prosthetic-side push-off, there is no proven mechanistic explanation of how that impairment propagates to the rest of the body. We used a simple dynamic walking model to explore possible consequences of a unilateral impairment similar to that of a transtibial amputee. The model compensates for reduced push-off work from one leg by performing more work elsewhere, for example during the middle of stance by either or both legs. The model predicts several gait abnormalities, including slower forward velocity of the body center-of-mass (COM) during intact-side stance, greater energy dissipation in the intact side, and more positive work overall. We tested these predictions with data from unilateral transtibial amputees (N = 11) and non-amputee control subjects (N = 10) walking on an instrumented treadmill. We observed several predicted asymmetries, including forward velocity during stance phases and energy dissipation from the two limbs, as well as greater work overall. Secondary adaptations, such as to reduce discomfort, may exacerbate asymmetry, but these simple principles suggest that some asymmetry may be unavoidable in cases of unilateral limb loss.
Amputation; gait; gait asymmetry; push-off; unilateral amputee; walking; walking model
Individuals with high spinal cord injuries are unable to operate a keyboard and mouse with their hands. In this experiment, we compared two systems using surface electromyography (sEMG) recorded from facial muscles to control an onscreen keyboard to type five-letter words. Both systems used five sEMG sensors to capture muscle activity during five distinct facial gestures that were mapped to five cursor commands: move left, move right, move up, move down, and “click”. One system used a discrete movement and feedback algorithm in which the user produced one quick facial gesture, causing a corresponding discrete movement to an adjacent letter. The other system was continuously updated and allowed the user to control the cursor’s velocity by relative activation between different sEMG channels. Participants were trained on one system for four sessions on consecutive days, followed by one crossover session on the untrained system. Information transfer rates (ITRs) were high for both systems compared to other potential input modalities, both initially and with training (Session 1: 62.1 bits/min, Session 4: 105.1 bits/min). Users of the continuous system showed significantly higher ITRs than the discrete users. Future development will focus on improvements to both systems, which may offer differential advantages for users with various motor impairments.
human-machine-interfaces; electromyography; communication rate
Effective clinical trials for neuroprotective interventions for Parkinson’s disease (PD) require a way to quantify an individual’s motor symptoms and analyze the change in these symptoms over time. Clinical scales provide a global picture of function but cannot precisely measure specific aspects of motor control. We have used commercially available sensors to create a protocol called Advanced Sensing for Assessment of Parkinson’s disease (ASAP) to obtain a quantitative and reliable measure of motor impairment in early to moderate PD. The ASAP protocol measures grip force as an individual tracks a sinusoidal or pseudorandom target force under three conditions of increasing cognitive load. Thirty individuals with PD have completed the ASAP protocol. The ASAP data for 26 of these individuals were summarized in terms of 36 variables, and modified regression techniques were used to predict an individual’s score on the Unified Parkinson Disease Rating Scale based on ASAP data. We observed a mean prediction error of approximately 3.5 UPDRS points, and the predicted score accounted for approximately 76% of the variability of the UPDRS. These results demonstrate that the ASAP protocol can measure differences for individuals who are clinically different. This indicates that the ASAP protocol may be able to measure changes with time in the motor signs of an individual with PD.
Event-related desynchronization (ERD) of sensori-motor rhythms (SMR) can be used for online brain–machine interface (BMI) control, but yields challenges related to the stability of ERD and feedback strategy to optimize BMI learning. Here, we compared two approaches to this challenge in 20 right-handed healthy subjects (HS, five sessions each, S1–S5) and four stroke patients (SP, 15 sessions each, S1–S15). ERD was recorded from a 275-sensor MEG system. During daily training, motor imagery-induced ERD led to visual and proprioceptive feedback delivered through an orthotic device attached to the subjects’ hand and fingers. Group A trained with a heterogeneous reference value (RV) for ERD detection with binary feedback and Group B with a homogenous RV and graded feedback (10 HS and 2 SP in each group). HS in Group B showed better BMI performance than Group A (p < 0.001) and improved BMI control from S1 to S5 (p = 0.012) while Group A did not. In spite of the small n, SP in Group B showed a trend for a higher BMI performance (p = 0.06) and learning was significantly better (p < 0.05). Using a homogeneous RV and graded feedback led to improved modulation of ipsilesional activity resulting in superior BMI learning relative to use of a heterogeneous RV and binary feedback.
Brain–machine interface; event-related desynchronization; neurorehabilitation; stroke
Future generations of brain-machine interface (BMI) will require more dexterous motion control such as hand and finger movements. Since a population of neurons in the primary motor cortex (M1) area is correlated with finger movements, neural activities recorded in M1 area are used to reconstruct an intended finger movement. In a BMI system, decoding discrete finger movements from a large number of input neurons does not guarantee a higher decoding accuracy in spite of the increase in computational burden. Hence, we hypothesize that selecting neurons important for coding dexterous flexion/extension of finger movements would improve the BMI performance. In this paper, two metrics are presented to quantitatively measure the importance of each neuron based on Bayes risk minimization and deflection coefficient maximization in a statistical decision problem. Since motor cortical neurons are active with movements of several different fingers, the proposed method is more suitable for a discrete decoding of flexion-extension finger movements than the previous methods for decoding reaching movements. In particular, the proposed metrics yielded high decoding accuracies across all subjects and also in the case of including six combined two-finger movements. While our data acquisition and analysis was done off-line and post processing, our results point to the significance of highly coding neurons in improving BMI performance.
Brain-machine interfaces (BMI); neural decoding; neural prosthesis; neuron selection
Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for partial-hand applications.
Electromyography (EMG); intrinsic hand muscle; myoelectric control; partial-hand amputee; pattern recognition
A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An Unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user’s avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman’s rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs.
Patient rehabilitation; occupational therapy; virtual reality; human computer interaction; human motion tracking; human motor performance
Many power wheelchair control interfaces are not sufficient for individuals with severely limited upper limb mobility. The majority of controllers that do not rely on coordinated arm and hand movements provide users a limited vocabulary of commands and often do not take advantage of the user’s residual motion. We developed a body-machine interface (BMI) that leverages the flexibility and customizability of redundant control by using high dimensional changes in shoulder kinematics to generate proportional controls commands for a power wheelchair. In this study, three individuals with cervical spinal cord injuries were able to control the power wheelchair safely and accurately using only small shoulder movements. With the BMI, participants were able to achieve their desired trajectories and, after five sessions driving, were able to achieve smoothness that was similar to the smoothness with their current joystick. All participants were twice as slow using the BMI however improved with practice. Importantly, users were able to generalize training controlling a computer to driving a power wheelchair, and employed similar strategies when controlling both devices. Overall, this work suggests that the BMI can be an effective wheelchair control interface for individuals with high-level spinal cord injuries who have limited arm and hand control.
Characterization of the joint torque coupling strategies used in the lower extremity to generate maximal and submaximal levels of torque at either the hip, knee or ankle is lacking. Currently, there are no available isometric devices that quantify all concurrent joint torques in the hip, knee and ankle of a single leg during maximum voluntary torque generation. Thus, joint-torque coupling strategies in the hip, knee and concurrent torques at ankle and/or coupling patterns at the hip and knee driven by the ankle have yet to be quantified. This manuscript describes the design, implementation and validation of a multiple degree of freedom, lower extremity isometric device (the MultiLEIT) that accurately quantifies simultaneous torques at the hip, knee and ankle. The system was mechanically validated and then implemented with two healthy control individuals and two post-stroke individuals to test usability and patient acceptance. Data indicated different joint torque coupling strategies used by both healthy individuals. In contrast, data showed the same torque coupling patterns in both post-stroke individuals, comparable to those described in the clinic. Successful implementation of the MultiLEIT can contribute to the understanding of the underlying mechanisms responsible for abnormal movement patterns and aid in the design of therapeutic interventions.
Coupling; Joint Torques; Lower Extremity; Stroke
A quantitative approach to virtual-lesion physiology is presented which integrates event-related fMRI, image-guided, repetitive, transcranial magnetic stimulation (irTMS), and simultaneous recording of 3-D movement kinematics. By linking motor neuroscience with clinical disorders of motor function, our method allows development of a healthy, human system model of disorders of skilled action.
Apraxia; brain imaging; kinematics; motor control
Multivariable dynamic ankle mechanical impedance in two coupled degrees-of-freedom (DOFs) was quantified when muscles were active. Measurements were performed at five different target activation levels of tibialis anterior and soleus, from 10% to 30% of maximum voluntary contraction (MVC) with increments of 5% MVC. Interestingly, several ankle behaviors characterized in our previous study of the relaxed ankle were observed with muscles active: ankle mechanical impedance in joint coordinates showed responses largely consistent with a second-order system consisting of inertia, viscosity, and stiffness; stiffness was greater in the sagittal plane than in the frontal plane at all activation conditions for all subjects; and the coupling between dorsiflexion–plantarflexion and inversion–eversion was small—the two DOF measurements were well explained by a strictly diagonal impedance matrix. In general, ankle stiffness increased linearly with muscle activation in all directions in the 2-D space formed by the sagittal and frontal planes, but more in the sagittal than in the frontal plane, resulting in an accentuated “peanut shape.” This characterization of young healthy subjects’ ankle mechanical impedance with active muscles will serve as a baseline to investigate pathophysiological ankle behaviors of biomechanically and/or neurologically impaired patients.
Ankle joint; ankle joint stiffness; ankle stiffness; human ankle; impedance structure; multivariable impedance; multivariable stiffness; stiffness anisotropy
Magnetic stimulation delivered via 0.5-mm diameter coils was recently shown to activate retinal neurons; the small coil size raises the possibility that micromagnetic stimulation (μMS) could underlie a new generation of implanted neural prosthetics. Such an approach has several inherent advantages over conventional electric stimulation, including the potential for selective activation of neuronal targets as well as less susceptibility to inflamma-tory responses. The viability of μMS for some applications, e.g., deep brain stimulation (DBS), may require suppression (rather than creation) of neuronal activity, however, and therefore we explore here whether (μMS) could, in fact, suppress activity. While single pulses elicited weak and inconsistent spiking in neurons of the mouse subthalamic nucleus (in vitro), repetitive stimulation effectively suppressed activity in ~70% of targeted neurons. This is the same percentage suppressed by conventional electric stimulation; with both modalities, suppression occurred only after an initial increase in spiking. The latency to the onset of suppression was inversely correlated to the energy of the stimulus waveform: larger amplitudes and lower frequencies had the fastest onset of suppression. These findings continue to support the viability of μMS as a next-generation implantable neural prosthetic.
Deep brain stimulation (DBS); magnetic stimulation; neural prosthesis; Parkinson's disease (PD); repetitive transcranial magnetic stimulation (rTMS); subthalamic nucleus (STN)
Neurological or biomechanical disorders may distort ankle mechanical impedance and thereby impair locomotor function. This paper presents a quantitative characterization of multivariable ankle mechanical impedance of young healthy subjects when their muscles were relaxed, to serve as a baseline to compare with pathophysiological ankle properties of biomechanically and/or neurologically impaired patients. Measurements using a highly backdrivable wearable ankle robot combined with multi-input multi-output stochastic system identification methods enabled reliable characterization of ankle mechanical impedance in two degrees-of-freedom (DOFs) simultaneously, the sagittal and frontal planes. The characterization included important ankle properties unavailable from single DOF studies: coupling between DOFs and anisotropy as a function of frequency. Ankle impedance in joint coordinates showed responses largely consistent with a second-order system consisting of inertia, viscosity, and stiffness in both seated (knee flexed) and standing (knee straightened) postures. Stiffness in the sagittal plane was greater than in the frontal plane and furthermore, was greater when standing than when seated, most likely due to the stretch of bi-articular muscles (medial and lateral gastrocnemius). Very low off-diagonal partial coherences implied negligible coupling between dorsiflexion-plantarflexion and inversion-eversion. The directions of principal axes were tilted slightly counterclockwise from the original joint coordinates. The directional variation (anisotropy) of ankle impedance in the 2-D space formed by rotations in the sagittal and frontal planes exhibited a characteristic “peanut” shape, weak in inversion-eversion over a wide range of frequencies from the stiffness dominated region up to the inertia dominated region. Implications for the assessment of neurological and biomechanical impairments are discussed.
Ankle joint; ankle joint stiffness; ankle stiffness; human ankle; impedance structure; multivariable impedance; multivariable stiffness; stiffness anisotropy
Following two decades of design and clinical research on robot-mediated therapy for the shoulder and elbow, therapeutic robotic devices for other joints are being proposed: several research groups including ours have designed robots for the wrist, either to be used as stand-alone devices or in conjunction with shoulder and elbow devices. However, in contrast with robots for the shoulder and elbow which were able to take advantage of descriptive kinematic models developed in neuroscience for the past 30 years, design of wrist robots controllers cannot rely on similar prior art: wrist movement kinematics has been largely unexplored. This study aimed at examining speed profiles of fast, visually evoked, visually guided, target-directed human wrist pointing movements. One thousand three-hundred ninety-eight (1398) trials were recorded from seven unimpaired subjects who performed center-out flexion/extension and abduction/adduction wrist movements and fitted with 19 models previously proposed for describing reaching speed profiles. A nonlinear, least squares optimization procedure extracted parameters’ sets that minimized error between experimental and reconstructed data. Models’ performances were compared based on their ability to reconstruct experimental data. Results suggest that the support-bounded log-normal is the best model for speed profiles of fast, wrist pointing movements. Applications include design of control algorithms for therapeutic wrist robots and quantitative metrics of motor recovery.
Motor control; rehabilitation robotics; stroke; wrist movement
Both the American Heart Association and the VA/DoD endorse upper-extremity robot-mediated rehabilitation therapy for stroke care. However, we do not know yet how to optimize therapy for a particular patient’s needs. Here, we explore whether we must train patients for each functional task that they must perform during their activities of daily living or alternatively capacitate patients to perform a class of tasks and have therapists assist them later in translating the observed gains into activities of daily living. The former implies that motor adaptation is a better model for motor recovery. The latter implies that motor learning (which allows for generalization) is a better model for motor recovery. We quantified trained and untrained movements performed by 158 recovering stroke patients via 13 metrics, including movement smoothness and submovements. Improvements were observed both in trained and untrained movements suggesting that generalization occurred. Our findings suggest that, as motor recovery progresses, an internal representation of the task is rebuilt by the brain in a process that better resembles motor learning than motor adaptation. Our findings highlight possible improvements for therapeutic algorithms design, suggesting sparse-activity-set training should suffice over exhaustive sets of task specific training.
Kinematics; motor adaptation; motor learning; rehabilitation robotics; stroke
This study investigated the effects of altering foot placement on the strategies used by able-bodied subjects to perform reaching tasks while standing. The motivation for this study was to consider the results in the context of a person with a spinal cord injury using a functional neuromuscular stimulation (FNS) system to stand while reaching. Three foot placement conditions were compared as subjects reached to the left, right, and center. Centers of pressure (COP), joint angles, and joint moments were calculated as postural parameters using force platform and video marker data. Side-by-side and wide foot placements resulted in similar postural parameters. In contrast, the modified tandem stance (feet spaced at pelvic width with one foot shifted forward) resulted in anterior/posterior COP excursions that were larger in magnitude and more consistent across reach directions when compared to the other foot placement conditions. Furthermore, the movement patterns used during the tandem stance were more consistent and may be more readily achievable with FNS than the movement patterns utilized with the side-by-side and wide stances. These results suggest that the modified tandem stance may enhance the functionality of FNS standing systems and may also be useful in other standing rehabilitation programs.
Biomechanics; kinematics; neuromuscular stimulation; posture; spinal-cord injury (SCI)
We present a novel demonstration of real-time dynamic interaction between an oscillatory spinal cord (isolated lamprey nervous system) and electronic hardware that mimics the spinal motor pattern generating circuitry. The spinal cord and the neuromorphic circuit were interfaced in unidirectional and bidirectional modes. Bidirectional coupling resulted in stable, persistent oscillations. This experimental platform offers a unique paradigm to examine the intrinsic dynamics of neural circuitry. The neuromorphic analog very large scale integration (aVLSI) design and real-time capabilities of this approach may provide a particularly powerful means of restoring complex neuromotor function using neuroprostheses.
Analog very large scale integration (aVLSI); lamprey; locomotor control; neural engineering; neuromorphic design; neuroprostheses; pattern generator; spinal cord
An ideal myoelectric prosthetic hand should have the ability to continuously morph between any posture like an anatomical hand. This paper describes the design and validation of a morphing myoelectric hand controller based on principal component analysis of human grasping. The controller commands continuously morphing hand postures including functional grasps using between two and four surface electromyography (EMG) electrodes pairs. Four unique maps were developed to transform the EMG control signals in the principal component domain. A preliminary validation experiment was performed by 10 nonamputee subjects to determine the map with highest performance. The subjects used the myoelectric controller to morph a virtual hand between functional grasps in a series of randomized trials. The number of joints controlled accurately was evaluated to characterize the performance of each map. Additional metrics were studied including completion rate, time to completion, and path efficiency. The highest performing map controlled over 13 out of 15 joints accurately.
Biomechatronics; electromyography (EMG); myoelectric control; principal component analysis; transradial prosthesis