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Tremor in Parkinson's disease (PD) is caused by synchronized activation bursts in limb muscles. Deep Brain Stimulation (DBS) is an effective clinical therapy for inhibiting tremor and improving movement disorders in PD patients. However, the neural mechanism of how tremor symptom is suppressed by DBS at motor unit (MU) level remains unclear. This paper developed a data acquisition platform for collecting physiological data in PD patients. Both high-density surface Electromyography (HD-sEMG) and kinematics data were collected concurrently before and after DBS surgery. The MU behaviors were obtained via HD-sEMG decomposition algorithm to reveal the effect of DBS on PD tremor. A data set of one tremor dominant PD patient acquired in pre-operation and post-operation (DBS-on) phases was analyzed. Preliminary results showed significant changes in MU firing rate and MU synchronization. The analysis approach introduced in this paper provides a novel perspective for studying the neural mechanism of DBS as revealed by MU activities. Clinical Relevance- This study presented an approach to investigate the effect of DBS therapy on improving tremor disorder of PD patients.

Background This paper describes the design and test of an automated functional electrical stimulation (FES) system for poststroke rehabilitation training. The aim of automated FES is to synchronize electrically induced movements to assist residual movements of patients. Methods In the design of the FES system, an accelerometry module detected movement initiation and movement performed by post-stroke patients. The desired movement was displayed in visual game module. Synergy-based FES patterns were formulated using a normal pattern of muscle synergies from a healthy subject. Experiment 1 evaluated how different levels of trigger threshold or timing affected the variability of compound movements for forward reaching (FR) and lateral reaching (LR). Experiment 2 explored the effect of FES duration on compound movements. Results Synchronizing FES-assisted movements with residual voluntary movements produced more consistent compound movements. Matching the duration of synergy-based FES to that of patients could assist slower movements of patients with reduced RMS errors. Conclusions Evidence indicated that synchronization and matching duration with residual voluntary movements of patients could improve the consistency of FES assisted movements. Automated FES training can reduce the burden of therapists to monitor the training process, which may encourage patients to complete the training.

Current control of prosthetic hands is ineffective when grasping deformable, irregular, or heavy objects. In humans, grasping is achieved under spinal reflexive control of the musculotendon skeletal structure, which produces a hand stiffness commensurate with the task. We hypothesize that mimicking reflex on a prosthetic hand may improve grasping performance and safety when interacting with human. Here, we present a design of compliant controller for prosthetic hand with a neuromorphic model of human reflex. The model includes 6 motoneuron pools containing 768 spiking neurons, 1 muscle spindle with 128 spiking afferents, and 1 modified Hill-type muscle. Models are implemented using neuromorphic hardware with 1 kHz real-time computing. Experimental tests showed that the prosthetic hand could sustain a 40 N load compared to 95 N for an adult. Stiffness range was adjustable from 60 to 640 N/m, about 46.6% of that of human hand. The grasping velocity could be ramped up to 14.4 cm/s, or 24% of the human peak velocity. The complaint control could switch between free movement and contact force when pressing a deformable beam. The amputee can achieve a 47% information throughput of healthy humans. Overall, the reflex-enabled prosthetic hand demonstrated the attributes of human compliant grasping with the neuromorphic model of spinal neuromuscular reflex. Electronic supplementary material The online version of this article (10.1007/s10439-020-02596-9) contains supplementary material, which is available to authorized users.

Objective. Evoked tactile sensation (ETS) elicited by transcutaneous electrical nerve stimulation (TENS) is promising to convey digit-specific sensory information to amputees naturally and non-invasively. Fitting ETS-based sensory feedback to amputees entails customizing coding of multiple sensory information for each stimulation site. This study was to elucidate the consistency of percepts and qualities by TENS at multiple stimulation sites in amputees retaining ETS. Approach. Five transradial amputees with ETS and fourteen able-bodied subjects participated in this study. Surface electrodes with small size (10 mm in diameter) were adopted to fit the restricted projected finger map on the forearm stump of amputees. Effects of stimulus frequency on sensory types were assessed, and the map of perceptual threshold for each sensation was characterized. Sensitivity for vibration and buzz sensations was measured using distinguishable difference in stimulus pulse width. Rapid assessments for modulation ranges of pulse width at fixed amplitude and frequency were developed for coding sensory information. Buzz sensation was demonstrated for location discrimination relating to prosthetic fingers. Main results. Vibration and buzz sensations were consistently evoked at 20 Hz and 50 Hz as dominant sensation types in all amputees and able-bodied subjects. Perceptual thresholds of different sensations followed a similar strength-duration curve relating stimulus amplitude to pulse width. The averaged distinguishable difference in pulse width was 12.84 ± 7.23 μs for vibration and 15.21 ± 6.47 μs for buzz in able-bodied subjects, and 14.91 ± 10.54 μs for vibration and 11.30 ± 3.42 μs for buzz in amputees. Buzz coding strategy enabled five amputees to discriminate contact of individual fingers with an overall accuracy of 77.85%. Significance. The consistency in perceptual qualities of dominant sensations can be exploited for coding multi-modality sensory feedback. A fast protocol of sensory coding is possible for fitting ETS-based, non-invasive sensory feedback to amputees.

Restoring neuromuscular reflex properties in the control of a prosthetic hand may potentially approach human-level grasp functions in the prosthetic hand. Previous studies have confirmed the feasibility of real-time emulation of a monosynaptic spinal reflex loop for prosthetic control. This study continues to explore how well the biomimetic controller could enable the amputee to perform force-control tasks that required both strength and error-tolerance. The biomimetic controller was programmed on a neuromorphic chip for real-time emulation of reflex. The model-calculated force of finger flexor was used to drive a torque motor, which pulled a tendon that flexed prosthetic fingers. Force control ability was evaluated in a “press-without-break” task, which required participants to press a force transducer toward a target level, but never exceeding a breakage threshold. The same task was tested either with the index finger or the full hand; the performance of the biomimetic controller was compared to a proportional linear feedback (PLF) controller, and the contralateral normal hand. Data from finger pressing task in 5 amputees showed that the biomimetic controller and the PLF controller achieved 95.8% and 66.9% the performance of contralateral finger in success rate; 50.0% and 25.1% in stability of force control; 59.9% and 42.8% in information throughput; and 51.5% and 38.4% in completion time. The biomimetic controller outperformed the PLF controller in all performance indices. Similar trends were observed with full-hand grasp task. The biomimetic controller exhibited capacity and behavior closer to contralateral normal hand. Results suggest that incorporating neuromuscular reflex properties in the biomimetic controller may provide human-like capacity of force regulation, which may enhance motor performance of amputees operating a tendon-driven prosthetic hand.

Virtual environments are commonly used in system validation and pre-wear training for prosthetic hand systems. In this study, we developed a human-like tendon-driven virtual hand system in MuJoCo emulation environment. The virtual hand was integrated with external neuromorphic models of flexor and extensor muscles acting on digit tendons. Contact pressures at prosthetic fingers were conveyed to an external sensory feedback system. The neuromorphic model emulated a monosynaptic neuromuscular reflex loop. A pair of $\alpha$ motor commands derived from EMG signals of amputee's arm activated neuromorphic muscles via motoneuron pools that were also regulated simultaneously by spiking afferents from muscle spindles. Using the integrated virtual hand system, we showed that control of equilibrium positions (EPs) of fingertip can be achieved by co-contracting $\alpha$ motor commands of antagonist neuromorphic muscles. Responses to force perturbations applied to the fingertip during maintenance of EP allowed calculation of stiffness ellipses at the fingertip. The biomimetic controller could switch automatically between position and force control, or stiffness regulation during stable grasping of a spring with different stiffness. It was demonstrated that the virtual hand platform is useful for amputees to explore biomimetic neuromuscular control of hand grasp with real-time tactile sensory feedback.

Prosthetic and therapeutic devices have been developed to ameliorate the quality of daily living for people with amputation or neurological disorders. However, many of them fall short of functional benefits, and therefore, are frequently rejected by users due to awkward control, or no awareness of interaction during tasks. Traditional wisdom in the design of prosthetic and therapeutic devices may have emphasized the need to provide users with apparatus that replace or assist motor ability. Rather, the notion to achieve neural compatibility with the existing sensorimotor system has not been well recognized. We argue that providing biomimetic control and sensing capacity to prosthetic and therapeutic devices can enhance their neural compatibility, and therefore, can yield greater functionality in performing activities of daily lives, or in rehabilitation training. In this paper, the authors will present a range of neural technologies that may allow implementation of biomimetic sensorimotor control, including natural sensory feedback, neuromuscular like compliant control, natural module of synergy-based control, as well as advanced neural signal processing techniques. Based on the evidence in our research and in literature, we propose that achieving neural compatibility with the existing human sensorimotor system should be the ultimate goal of prosthetic and therapeutic devices.

The ability to perceive prosthetic grasping may enable amputees to better interact with external objects. This may require customized coding of multiple sensory feedback for each amputee. This study developed a protocol to determine optimal modulation ranges of sensations elicited by transcutaneous electrical nerve stimulation (TENS). These sensations that were referred to the lost fingers provided the possibility for restoring multi-modalities of sensory feedback for amputees with evoked tactile sensation (ETS) non-invasively. To match the restricted projected finger map area, smaller electrodes must be used to deliver electrical stimulation for multi-channel sensory information, which resulted in fewer types of sensations. Our protocol provided comprehensive information for optimal selection of amplitude and frequency in a personalized, pulse-width encoding paradigm. The good sensitivity for vibration and buzz in both able-bodied and amputee subjects suggested that perceptual intensity can be effectively modulated to convey sensory information via either of the sensations. The efficacy of this protocol in sensory coding for forearm amputees was demonstrated in finger-specific identification experiment. This protocol may allow customization of ETS-based sensory feedback with an optimal encoding strategy for individual amputees.

Voluntary movement could be initiated in spite of involuntary resting tremor in patients with Parkinson's disease (PD). It is unknown how the central nervous system (CNS) transits from the ongoing involuntary motor program of tremor to the execution of voluntary reaching movement. In this paper, muscle synergy analysis was used to unveil the motor module transitions from resting tremor to compound movement. Three tremor symptom dominant PD patients performed tasks of targeted forward reaching movements with background tremor. Kinematics and surface electromyography (EMG) of six muscles were recorded. Synergy vectors and time profiles were analyzed using EMG data during resting tremor and forward reaching. Results revealed that the representative vector of tremor remained unchanged during performance of voluntary movement. Other synergy vectors of tremor were modified to accommodate vectors of movement synergies. The merge of tremor module with movement module could be explained by a procedure of linear combination. The distribution of timing of movement initiation with respect to tremor cycle displayed a weak sign of clusters. The analysis suggested that the CNS combined two motor modules in order to initiate a voluntary movement with background tremor. More extensive analysis with a larger number of patients needs to be carried out to confirm these findings.

Integrating a prosthetic hand to amputees with seamless neural compatibility presents a grand challenge to neuroscientists and neural engineers for more than half century. Mimicking anatomical structure or appearance of human hand does not lead to improved neural connectivity to the sensorimotor system of amputees. The functions of modern prosthetic hands do not match the dexterity of human hand due primarily to lack of sensory awareness and compliant actuation. Lately, progress in restoring sensory feedback has marked a significant step forward in improving neural continuity of sensory information from prosthetic hands to amputees. However, little effort has been made to replicate the compliant property of biological muscle when actuating prosthetic hands. Furthermore, a full-fledged biorealistic approach to designing prosthetic hands has not been contemplated in neuroprosthetic research. In this perspective article, we advance a novel view that a prosthetic hand can be integrated harmoniously with amputees only if neural compatibility to the sensorimotor system is achieved. Our ongoing research supports that the next-generation prosthetic hand must incorporate biologically realistic actuation, sensing, and reflex functions in order to fully attain neural compatibility.

The objective of this study is to develop an experimental protocol to define the range of modulation for different sensory modalities elicited by transcutaneous electrical nerve stimulation (TENS) in amputees with evoked tactile sensation (ETS). Modulation ranges of sensory modalities, such as vibration, buzz, tingling etc., are essential for designing a coding strategy for incoming sensory information from prosthetic hands for each amputee. Here, the modulation ranges of different modalities in pulse width at fixed stimulus frequencies were evaluated. Four healthy subjects and three transradial amputee subjects were recruited to participate in this preliminary test. A single skin site in healthy subjects and five finger areas of the projected finger map (PFM) on the stump skin in amputee subjects were stimulated for evaluation. Then, a finger identification test was conducted to show the feasibility of this sensory coding strategy in one amputee subject. The sensitivity of different sensory modalities was also measured to quantify the minimum pulse width change that subject could distinguish. Results showed that vibration and buzz sensations had wider modulation ranges in pulse width for both healthy and amputee subjects at 20Hz and 50Hz of stimulation, respectively. The average accuracy of finger identification was 91.66% in the amputee subject. The minimum pulse width changes distinguishable for both vibration and buzz sensation were below 20 (us). Results indicated that the protocol of evaluating pulse width modulation ranges for different sensory modalities was effective, and the coding strategy could provide accurate finger-specific sensory information for amputees with ETS.Clinical Relevance— This protocol establishes a guideline for customizing the coding strategy of evoked tactile sensory feedback for each amputee.

Biomimetic flexible tactile sensors endow prosthetics with the ability to manipulate objects, similar to human hands. However, it is still a great challenge to selectively respond to static and sliding friction forces, which is crucial tactile information relevant to the perception of weight and slippage during grasps. Here, inspired by the structure of fingerprints and the selective response of Ruffini endings to friction forces, we developed a biomimetic flexible capacitive sensor to selectively detect static and sliding friction forces. The sensor is designed as a novel plane-parallel capacitor, in which silver nanowire–3D polydimethylsiloxane (PDMS) electrodes are placed in a spiral configuration and set perpendicular to the substrate. Silver nanowires are uniformly distributed on the surfaces of 3D polydimethylsiloxane microcolumns, and silicon rubber (Ecoflex®) acts as the dielectric material. The capacitance of the sensor remains nearly constant under different applied normal forces but increases with the static friction force and decreases when sliding occurs. Furthermore, aiming at the slippage perception of neuroprosthetics, a custom-designed signal encoding circuit was designed to transform the capacitance signal into a bionic pulsed signal modulated by the applied sliding friction force. Test results demonstrate the great potential of the novel biomimetic flexible sensors with directional and dynamic sensitivity of haptic force for smart neuroprosthetics.

Restoring sensory functions for limbs and prosthetic devices is essential to bidirectional information communication between devices and the central nervous system of humans. Progress in neural interface technologies has bridged the gap of information deficits and improved the function of neural prostheses. The physiology of sensory information coding, its central processing, and its representation underline the possible ways the sensory nervous system can be accessed. Technical constraints and functional benefits may dominate the tradeoff for selecting interface sites that may require noninvasive to moderately invasive technologies. This chapter reviews the significant advances in sensory neural prosthesis technologies made in past decades. Many neural interface technologies show promise for sensory information feedback, particularly peripheral nerve cuff stimulation.

Background Recent study suggests that tremor signals are transmitted by way of multi-synaptic corticospinal pathway. Neurophysiological studies have also demonstrated that cutaneous afferents exert potent inhibition to descending motor commands by way of spinal interneurons. We hypothesize in this study that cutaneous afferents could also affect the transmission of tremor signals, thus, inhibit tremor in patients with PD. Methods We tested this hypothesis by activating cutaneous afferents in the dorsal hand skin innervated by superficial radial nerve using transcutaneous electrical nerve stimulation (TENS). Eight patients with PD having tremor dominant symptom were recruited to participate in this study using a consistent experimental protocol for tremor inhibition. Resting tremor and electromyogram (EMG) of muscles in the upper extremity of these subjects with PD were recorded, while surface stimulation was applied to the dorsal skin of the hand. Fifteen seconds of data were recorded for 5 s prior to, during and post stimulation. Power spectrum densities (PSDs) of tremor and EMG signals were computed for each data segment. The peak values of PSDs in three data segments were compared to detect evidence of tremor inhibition. Results At stimulation intensity from 1.5 to 1.75 times of radiating sensation threshold, apparent suppressions of tremor at wrist, forearm and upper arm and in the EMGs were observed immediately at the onset of stimulation. After termination of stimulation, tremor and rhythmic EMG bursts reemerged gradually. Statistical analysis of peak spectral amplitudes showed a significant difference in joint tremors and EMGs during and prior to stimulation in all 8 subjects with PD. The average percentage of suppression was 61.56% in tremor across all joints of all subjects, and 47.97% in EMG of all muscles. The suppression appeared to occur mainly in distal joints and muscles. There was a slight, but inconsistent effect on tremor frequency in the 8 patients with PD tested. Conclusions Our results provide direct evidence that tremor in the upper extremity of patients with PD can be inhibited to a large extent with evoked cutaneous reflexes via surface stimulation of the dorsal hand skin area innervated by the superficial radial nerve.

Objective Resting tremor may compound the effects of bradykinesia to further prolong the initiation of voluntary movement in patients with Parkinson's disease (PD). However, the interaction between resting tremor and voluntary movements in these PD patients has not been well understood. Recently, we demonstrated that cutaneous afferents evoked by surface stimulation of superficial radial nerve can inhibit resting tremor effectively. The inhibition appears to take effect via spinal interneuronal pathways. This study evaluates how evoked cutaneous afferents would impact the performance of voluntary movements in PD subjects when tremor is inhibited. Approach Ten PD patients with tremor and eight age-matched control subjects were recruited to participate in this study. Both groups of subjects performed fast reaching movements, while cutaneous stimulation was delivered during reaching tasks on or off randomly. Kinematic performance, such as reaction time (RT), movement time (MT), and movement variability, as well as muscle synergy of tasks were evaluated and compared to assess the impact of evoked cutaneous afferents on movement performances. Main results Results indicated that the cutaneous stimulation significantly reduced RT in PD patients by 17.7%; but had an insignificant effect on RT in control subjects. Cutaneous stimulation, however, caused a significantly longer MT both in control subjects (8.6%) and in PD subjects (15.7%). Movement variability was not significantly altered in both groups of subjects by the cutaneous stimulation. Muscle synergy analysis revealed that cutaneous stimulation affected the power spectral densities (PSD) of time profiles of muscle synergies more significantly than the vector patterns of synergies in both control subjects and PD subjects. Significance These findings provide evidence that tremor increases the RT of voluntary motor control in PD patients, and demonstrate that cutaneous stimulation reduces the RT of voluntary movements significantly, in addition to suppressing tremor, yet without interrupting voluntary control of movements.

Background A large population of patients with Parkinson’s disease (PD) displays the symptom of resting tremor. However, the extent that resting tremor may affect the performance of movement control has not been evaluated specifically. This study aims at establishing methods to quantitatively evaluate motor performance in PD patients with tremor, and at analyzing the interfering effects of tremor on control of reaching movements. Methods Ten PD patients with tremor and Ten healthy control subjects were recruited to participate in this study. All patients and healthy control subjects performed point-to-point reaching movements with their tremor affected arm or preferred arm. We verified that a smoothing model of minimum-jerk trajectory (MJT) can be used to extract voluntary movement trajectory from tremor-corrupted movement trajectory in the reaching tasks by the patients. Performance indices of reaction time (RT) and movement time (MT) of reaching movements by the PD subjects with tremor were evaluated using MJT trajectories. Differences of RT and MT between the recorded trajectories and MJT in PD and control subjects were calculated to investigate the extent that tremor may affect their motor performance. Linear mixed-effects model was used to identify the contributions of tremor, bradykinesia and rigidity to the performance indices of RT and MT based on UPDRS scores. The power spectrum densities (PSD) of tremor were also evaluated using hand velocities to represent tremor intensity and to analyze their correlations with RT and MT. Results The MJT model demonstrated good fit to recorded trajectory with a more consistent estimation of motor performance for both PD and control subjects. The RT and MT of patients were found to be 43.4 and 79.5% longer respectively than those of healthy control subjects. Analysis of the linear mixed-effects model was not able to reveal that tremor, bradykinesia and rigidity each had a significant contribution to RT or MT in PD patients with tremor. However, the PSD of tremor was found to correlate significantly to RT, but not to MT, in both linear regression and linear mixed-effects model. Conclusions The minimum-jerk trajectory and power spectrum densities are effective quantitative tools for evaluating motor performance for PD patients with tremor. Resting tremor is one of the factors prolonging the initiation of voluntary reaching movement in these patients.

Resting tremor affects voluntary reaching movements in patients with Parkinson’s disease (PD). Previously, we found that cutaneous afferents evoked by electrically simulating the superficial radial nerve could inhibit tremor activity [3]. Yet, the mechanism that cutaneous stimulation affects tremor as well as voluntary movements remains unclear. In this paper, we used the method of muscle synergy analysis to further investigate the muscle activation patterns of tremor and reaching movements. Three PD patients with tremor dominant symptom participated in this preliminary study. The patients performed targeted reaching movements with no visual feedback of their hands, while transcutaneous electrical stimulation was delivered to inhibit tremor activity. Kinematics and EMGs of six muscles were recorded during resting and reaching tasks. Muscle synergy analysis was performed with data during resting and task stages with and without cutaneous stimulation. Results showed that during resting state the time profiles of muscle synergy in the tremor cycle displayed two main alternating components that were distributed to antagonistic muscle pairs in upper arm, forearm and wrist. Cutaneous stimulation affected the vector patterns and time profiles of muscle synergies for tremor and reaching movements differently. Our results indicate that muscle synergies are sensitive to central descending drives of muscles, as well as evoked peripheral afferents.

Evoked tactile sensation (ETS) is induced with stimulation of areas in the projected finger map (PFM) in the stump skin of forearm amputees. The aim of the present study is to further explore the neural correlation of the ETS with central activities in the somatosensory cortex (SI). Two forearm amputees were recruited to participate in this study. The neuroimaging technique of Magnetoencephalography (MEG) was employed to reveal the activities in the somatosensory cortex (SI), while the thumb and little finger areas in the PFM and the thumb and little finger of the contralateral hand were stimulated with a bi-phasic current pulse train. In one subject, local anesthesia was applied to the skin areas of the thumb and little finger of the PFM to examine the effects of blocking peripheral nerve transmission on the central activities in SI. Results obtained in the two subjects indicated that stimulation of the thumb and little finger areas in the PFM of amputated side produced the similar neural activities in the somatosensory cortex as those of stimulating the thumb and little finger of the contralateral hand, both of which were consistent with the homunculus organization of the SI cortex. The intensity of SI cortical activities was proportional to the intensity of the amplitude of peripheral stimulation. In particular, local anesthesia reduced the intensity of central activities in SI as revealed by the MEG response, as well as the sensitivity of ETS as reported by the subject. This neural correlation appears to suggest that the finger areas in the PFM in the stump skin are neuroanatomically connected to the finger areas of the somatosensory cortex. Thus, electrical stimulation of the PFM can induce natural sensation as that of normal fingers. This establishes the neural basis of natural sensory feedback from the prosthetic hand to the forearm amputee with finger-to-finger specificity.

Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

The objective of this study was to test the hypothesis that electrical stimulation of projected finger map (PFM) in the stump skin of forearm amputees activates concurrently the corresponding finger areas in the primary somatosensory cortex (S1). The technique of magnetoencephalo-graphy (MEG) was used to detect S1 activities, while electrical stimulation pulses or trains were delivered to three sites: (1) the thumb and little finger areas of the PFM on the stump skin of an amputee subject; (2) the thumb and little finger of the contralateral hand of the subject; and (3) the contralateral forearm skin areas matching the PFM in the amputated stump. Result indicated that at single pulse stimulus (1Hz) to the thumb and little fingers in the PFM and contralateral hand, symmetric areas in S1 corresponding to the thumb (more lateral) and little finger (lateral) in both sides could be identified. With stimulation train (50Hz and duty cycle of 50%) to the thumb and little finger in the PFM and contralateral hand, the subject experienced pressure sensations similarly at both sites, and the same symmetric areas of the thumb (more lateral) and little finger (lateral) in S1 were activated. With stimulation at the third site, the activation area in S1 was located towards more medial (elbow) segment. MEG results indicated that PFM stimulation evoked S1 activation consistent with homunculus organization. This may imply that the thumb and little finger areas in the PFM on the stump skin are connected neuroanatomically to the thumb and little finger areas in S1 before amputation.

More than 70% of patients suffering Parkinson's disease (PD) exhibit resting tremor in their extremities, hampering their ability to perform daily activities. Based on our earlier studies on corticospinal transmission of tremor signals [10,11], we hypothesize that cutaneous afferents evoked by surface stimulation can produce an inhibitory effect on propriospinal neurons (PN), which in turn will suppress tremor signals passing through the PN. This paper presents the development of a closed-loop system for tremor suppression by transcutaneous electrical nerve stimulation (TENS) of sensory fibers beneath the skin. The closed-loop system senses EMGs of forearm muscles, and detects rhythmic bursting in the EMG signal. When a tremor is detected by the system, a command signal triggers a stimulator to output a train of bi-phasic, current regulated pulses to a pair of surface electrodes. The stimulation electrode is placed on the dorsal hand skin near the metacarpophalangeal joint of index finger, which is innervated by the superficial radial nerve that projects an inhibitory afferent to PNs of forearm muscles. We tested the closed-loop system in 3 normal subjects to verify the algorithm and in 2 tremor dominated PD subjects for feasibility of tremor detecting and suppression. Preliminary results indicate that the closed-loop system can detect tremor in all subjects, and tremor in PD patients was suppressed significantly by electrical stimulation of cutaneous afferents.

Neuromuscular electrical stimulation (NMES) is a promising assistive technology for stroke rehabilitation. Here we present the design and development of a multimuscle stimulation system as an emerging therapy for people with paretic stroke. A network-based multichannel NMES system was integrated based on dual bus architecture of communication and an H-bridge current regulator with a power booster. The structure of the system was a body area network embedded with multiple stimulators and a communication protocol of controlled area network to transmit muscle stimulation parameter information to individual stimulators. A graphical user interface was designed to allow clinicians to specify temporal patterns and muscle stimulation parameters. We completed and tested a prototype of the hardware and communication software modules of the multichannel NMES system. The prototype system was first verified in nondisabled subjects for safety, and then tested in subjects with stroke for feasibility with assisting multijoint movements. Results showed that synergistic stimulation of multiple muscles in subjects with stroke improved performance of multijoint movements with more natural velocity profiles at elbow and shoulder and reduced acromion excursion due to compensatory trunk rotation. The network-based NMES system may provide an innovative solution that allows more physiological activation of multiple muscles in multijoint task training for patients with stroke.

It has been hypothesized that propriospinal neurons (PNs) in the C3-C4 spinal cord mediates cortical motor commands to the peripheral muscles during tremor in patients with Parkinson's disease (PD). However, there has been no direct evidence so far to support the role of PN in transmitting tremor commands. In this paper, we report the positive correlation of cutaneous afferents with reduction in tremor amplitude and frequency in PD patients. Resting tremor and EMGs of biceps, triceps, flexor digitorum superficialis (FDS), extensor digitorum (ED), flexor carpi ulnaris (FCU) and extensor carpi radialis (ECR) muscles were recorded while transcutaneous electrical stimulation (TES) was applied to the dorsal hand skin of PD subjects. We observed instant suppression of tremor amplitude and EMGs occurring immediately at the start of electrical stimulation. However at the end of stimulation, the tremor amplitude and EMGs showed a quick recovery to the level prior to stimulation. Spectral analysis indicated that cutaneous afferents also have a long-lasting memory effect on the tremor frequency, i.e. the tremor frequency post stimulation did not recover to the value prior to stimulation. Preliminary results implied that the reduction in tremor amplitude and EMGs could be due to the inhibitory effects of cutaneous afferents to PNs, supporting the hypothesis that the PN network is involved in transmission of cortical tremor commands to peripheral muscles.

In this paper, a novel experimental method was developed to study planar arm movement control in tremor dominant Parkinson's (PD) patients. The method utilized a ball-bearing supported fiberglass brace apparatus against gravity to maintain the upper extremity in the horizontal plane. Subjects can perform postural and movement tasks with minimum damping effects. Arm movements were recorded using the MotionMonitor II system concurrently with EMGs of multiple muscles. Testing results in normal subjects with and without the brace support showed that the inertia and damping effects were negligible for oscillatory arm movement at maximum voluntary frequency (MVF). The tremor behaviors in horizontal posture maintenance and reaching movement in three PD subjects were also obtained with this method. The average frequency of postural tremor was 4.34 ± 0.15 Hz in all arm positions tested. However, the tremor magnitudes changed significantly with posture locations. In performing reaching movements, the tremor was inhibited prior to reaching, but resumed after reaching. These results may provide interesting insights into the pathological mechanisms of Parkinsonian tremor, as well as the modular nature of neural control of movements.

Cortical oscillatory signals of single and double tremor frequencies act together to cause tremor in the peripheral limbs of patients with Parkinson's disease (PD). But the corticospinal pathway that transmits the tremor signals has not been clarified, and how alternating bursts of antagonistic muscle activations are generated from the cortical oscillatory signals is not well understood. This paper investigates the plausible role of propriospinal neurons (PN) in C3-C4 in transmitting the cortical oscillatory signals to peripheral muscles. Kinematics data and surface electromyogram (EMG) of tremor in forearm were collected from PD patients. A PN network model was constructed based on known neurophysiological connections of PN. The cortical efferent signal of double tremor frequencies were integrated at the PN network, whose outputs drove the muscles of a virtual arm (VA) model to simulate tremor behaviors. The cortical efferent signal of single tremor frequency actuated muscle spindles. By comparing tremor data of PD patients and the results of model simulation, we examined two hypotheses regarding the corticospinal transmission of oscillatory signals in Parkinsonian tremor. Hypothesis I stated that the oscillatory cortical signals were transmitted via the mono-synaptic corticospinal pathways bypassing the PN network. The alternative hypothesis II stated that they were transmitted by way of PN multi-synaptic corticospinal pathway. Simulations indicated that without the PN network, the alternating burst patterns of antagonistic muscle EMGs could not be reliably generated, rejecting the first hypothesis. However, with the PN network, the alternating burst patterns of antagonist EMGs were naturally reproduced under all conditions of cortical oscillations. The results suggest that cortical commands of single and double tremor frequencies are further processed at PN to compute the alternating burst patterns in flexor and extensor muscles, and the neuromuscular dynamics demonstrated a frequency dependent damping on tremor, which may prevent tremor above 8 Hz to occur.

It has been shown that normal cyclic movement of human arm and resting limb tremor in Parkinson's disease (PD) are associated with the oscillatory neuronal activities in different cerebral networks, which are transmitted to the antagonistic muscles via the same spinal pathway. There are mono-synaptic and multi-synaptic corticospinal pathways for conveying motor commands. This study investigates the plausible role of propriospinal neuronal (PN) network in the C3-C4 levels in multi-synaptic transmission of cortical commands for oscillatory movements. A PN network model is constructed based on known neurophysiological connections, and is hypothesized to achieve the conversion of cortical oscillations into alternating antagonistic muscle bursts. Simulations performed with a virtual arm (VA) model indicate that without the PN network, the alternating bursts of antagonistic muscle EMG could not be reliably generated, whereas with the PN network, the alternating pattern of bursts were naturally displayed in the three pairs of antagonist muscles. Thus, it is suggested that oscillations in the primary motor cortex (M1) of single and double tremor frequencies are processed at the PN network to compute the alternating burst pattern in the flexor and extensor muscles.

This paper describes a Functional Electrical Stimulation (FES) system based on the distributed network structure for rehabilitation of stroke patients. This FES system performs surface stimulation to activate the nerve of paretic muscles for training stroke patients to relearn motor functions. The main components of the networked FES system include a master unit (MU), a distributed stimulation-sensor unit (DSSU), and a clinical computer. In this system, the MU can drive a set of DSSUs, which is located at the node on the distributed network structure. The MU also stores the stimulation plan of rehabilitation training prescribed by clinicians. The DSSU serves as a single channel stimulator whose current amplitude, duration and frequency can be modulated by the MU. This system has two distinctive characters. First, since a stimulator is designed as a node on the network, the number of stimulation channels could be expanded according to specific needs. Second, a sensor component can be incorporated in the DSSU to allow monitoring physiological variables. The two features of system design make the networked FES system practical and flexible in clinical applications. We have completed a prototype of system including hardware and software. The evaluation test indicates that the system performance meets design specifications.