Xiaogang Hu - US grants

DESCRIPTION (provided by applicant): Muscular weakness is one of the major impairments limiting motor function following a hemispheric stroke. One mechanism that can contribute to muscle weakness is the structural changes of the motor unit, including reduction of fiber diameter, muscle fiber loss, and even motor axon loss and motoneuron reinnervation of paretic muscles. Currently, our knowledge of the extent of such motor unit structural change post-stroke is limited by the constraints associated with intramuscular recording techniques, which are both invasive and inefficient. A novel surface electromyogram (sEMG) recording and decomposition technique for motor unit analysis has recently been developed and tested in neurologically intact individuals. The system utilizes a unique surface electrode that is non-invasive and efficient, potentially yielding a large number of motor units simultaneously. Accordingly, the aims of this proposal are 1) To quantify the degree and frequency of the reduction in motor unit size in paretic muscle post-stroke. 2) To establish robust markers of motoneuron reinnervation in paretic muscle of stroke survivors. We will record the sEMG signals of both paretic and contralateral first dorsal interosseous muscles of 32 stroke survivors during isometric contractions at specified force levels, and we will also record the sEMG of 32 neurologically intact age-matched control subjects. We will extract single motor unit discharge activities using the novel sEMG decomposition algorithm, and estimate motor unit shape characteristics using the spike triggered averaging techniques. To address Aim 1, we will calculate key motor unit action potential (MUAP) parameters, including peak-peak amplitude, duration, and root mean squared values, as estimates the motor unit size. To address Aim 2, we will quantify the polyphasic properties (i.e., the number of peaks) of the MUAP as an estimate of motoneuron reinnervation. We will also examine the association between the structural changes in motor units and the severity of motor impairment. We hypothesize that the motor unit size in the paretic muscle is reduced, because of fiber size reduction and muscle fiber loss, and that the polyphasic changes (i.e., a larger number of peaks) in the MUAP are also more visible in the paretic muscle following a stroke. The proposed research will provide important information regarding the role of peripheral motor unit structural changes in muscle weakness. The novel and non-invasive techniques used here will provide an efficient way to systematically examine changes in motor unit characteristics, and can potentially serve as a diagnostic tool to distinguish central vs. peripheral origins of muscle weakness in stroke. The proposed work can thus provide a rationale for differentially targeted rehabilitation therapies with a potential to maximize functional recovery of stroke survivors. i

Hand amputation can severely limit the quality of life, for example by making it impossible to sense and manipulate objects, or to express gestures. Many robotic prosthetic hands have been developed to date, some of which have dexterity approaching that of a human hand, but a key factor limiting acceptance of these devices is the lack of natural and reliable sensory feedback to the user; the substitution of un-natural stimuli such as skin vibration, visual or audio cues doesn't really cut it. The PI's goal in this research is to explore the use of non-invasive grid electrodes for electrically stimulating the peripheral sensory nerves so they transmit natural (high resolution) haptic sensations to the central nervous system. Success of this project will revolutionize the way in which human beings communicate with robotic prostheses and transform research in close-loop prosthesis control, shifting amputee haptic sensation feedback from invasive implant techniques to non-invasive surface probing techniques. The non-invasive nature of the new technology presents the potential for rapid clinical translations with high functional efficiency and user acceptance. Thus, the research will lead to dramatic improvements in hand amputees' quality of life. In addition, the work will be integrated into graduate and undergraduate student education at the PI's institution, and outreach programs for K-12 students (especially underrepresented STEM students) will expose them to this innovative science.

This highly creative project adopts an approach that is completely different from the existing techniques for providing sensory restoration/augmentation, and which is supported by the team's preliminary studies. First, the investigators will design a novel, non-invasive nanowire sensor array that will provide natural sensation of the missing hand. The thin-film electrode grid will be self-adhesive and highly stretchable. The multifunctional electrodes will be able not only to provide targeted nerve stimulation but also to record pressures applied on the prosthetic hand, so they can both obtain a rich set of haptic information and also deliver this information to the user accurately and precisely, while inducing minimal interference such as skin discomfort, added weight due to the device, and control signal interference. Second, the team will create a new way of affording sensory restoration by developing a dynamic stimulation scheme that encodes spatially distinct haptic sensations in the digits and palm. This will be achieved by selectively recruiting the various afferent fibers innervating different regions of the hand. The investigators believe that with high spatial resolution based on hand region mapping, the haptic feedback could for the first time enable users to truly perceive the environment by "using" their lost hand, and thereby push the sense of embodiment to a new level. Lastly, new knowledge will be obtained by quantifying the effect of the sensorimotor integration process on closed-loop control of a dexterous prosthetic hand in amputees.

Following a stroke incident, a majority of stroke survivors lose the ability to use their hand to perform a variety of tasks despite months of therapy. In an effort to restore hand dexterity, advanced assistive devices (e.g., exoskeletons) have been developed. Unfortunately, only few of these novel devices have been used effectively by stroke survivors. One critical factor limiting user acceptance is the lack of reliable method that allows stroke survivors to intuitively control the device. The overarching objective of the project is to combine novel decoding of neurological signals that drive the muscles with a personalized musculoskeletal model of the upper limb to provide intuitive control of an assistive hand exoskeleton. The control strategy will be robust in handling different arm postures and movements. This personalized approach will improve hand functional performance in stroke survivors, with the overall goal of improving their ability to live independently. The computational approaches employed here will also produce a research tool to study human-robot interactions. The researchers will make the computational model available over online repository system, SimTK.org, as a simulation platform for other researcher working on hand function and control of rehabilitative devices. The project will provide educational and training opportunities. The research concepts will be integrated into existing courses. Summer projects incorporating the techniques will be offered to undergraduate and high school students and local school and community college instructors. Outreach programs will be developed to disseminate the proposed research outcomes to underrepresented students.

The goal of this project is to develop a personalized hybrid (neural data-based and model-based) interface that combines the decoded neural command with a musculoskeletal model. The developed interface will be used to control a soft-hard hybrid exoskeleton to enable dexterous finger movements in stroke survivors. The research team will first develop a real-time neural decoding algorithm based on populational firing probability of the motoneurons, extracted from motor unit decomposition of high-density electromyographic (HD-EMG) signals. Through incorporation of binary neuron discharge events, the decoded neural drive signals will be robust to changes in muscle activity features, background noise, and motion artifact. The research team will then employ a personalized musculoskeletal model of the limb, which will be calibrated to the unique musculoskeletal structure and activation parameters of stroke survivors. The model-based controller will be able to compensate for limb posture, movement dynamics, and subject-specific impairments that could otherwise disturb the mapping between user input and desired output. Finally, the research team will evaluate the developed interface for control of an advanced hand exoskeleton, allowing users to control flexion or extension assistance independently for each digit. The assistive forces will reinforce beneficial muscle activation while compensating for abnormal activation patterns. Collectively, the outcomes will restore hand dexterity in stroke survivors, thereby enabling them to perform daily activities and live independently.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

After a limb amputation, both motor and sensory functions associated with the limb are lost. Substantial effort has been devoted to restore lost motor functions. In contrast, there has been less advancement in restoring sensory function. Although earlier works have used sensory substitution or nerve stimulation techniques to elicit a single type of artificial sensation, there is limited understanding of how the human brain integrates different sources of artificial sensation, when multiple sensory stimulations are provided. This project will help understand the integration principles of different artificially evoked sensations of joint movements. By identifying key factors that determine the integration principle of multiple sources of artificial sensation, this project can generate potentially transformative outcomes for human-robot interactions, specifically developing brain-inspired sensory stimulation strategies that can enable intuitive interactions of assistive devices. The project will provide educational opportunities. Different project components will be integrated into existing undergraduate courses. Summer projects incorporating the sensory stimulation techniques will be offered to local school and community college students. Outreach programs associated with the research outcomes will be developed targeting underrepresented students.

The goal of this project is to understand the integration principles of different artificially evoked proprioceptive feedback. The research team will combine psychophysical testing, behavioral modeling, and brain signal recordings to understand the integration principle of artificial sensory signals. Proprioceptive feedback of the joint kinematics will be evoked using vibrotactile stimulation and peripheral nerve stimulation. Both upper and lower limbs will be investigated to evaluate whether the integration principle is task or end-effector dependent. The research team will use a Bayesian integration model and electroencephalogram (EEG) recordings to quantify how uncertainty and intuitiveness-associated attentional bias of artificial feedback impact sensory integration. The project outcomes will provide a theoretical basis for developing artificial sensory feedback for intuitive human-robot interactions, and will also provide a research platform for studying sensory perception.

This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NCS), a multidisciplinary program jointly supported by the Directorates for Biology (BIO), Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.