Project Grant 2330862

Award Date 10/1/22
Completion Date 11/30/25
Dollars Obligated $750K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Penn State University, PA 16802, USA
Similar Awards
This $365,758 Project Grant from the National Science Foundation Division of Chemical, Bioengineering, Environmental, and Transport Systems under the Engineering federal grant program (CFDA 47.041) will fund research at Penn State University to develop robust neural decoding approaches for human-machine interactions. The Principal Investigator will work to decode the neural command for individual finger movements by analyzing muscle electrical signals obtained non-invasively from the skin...
The National Institute of Child Health and Human Development (NICHD) awarded a $655,924 Project Grant (CFDA 93.865 - Child Health and Human Development Extramural Research) to The Regents of the University of California, San Francisco (UCSF) to develop methods for enabling patients with severe paralysis to directly control a complex robotic arm and hand. The project aims to leverage the stability of electrocorticography (ECoG) signals to establish robust and intuitive neuroprosthetic control...
The National Science Foundation (NSF) is providing a $170,617 Project Grant under its Engineering program (CFDA 47.041) to the University of Illinois to advance the scientific study of brain functional changes after a stroke and pioneer a tailored rehabilitation strategy that fits each individual's needs. The 5-year project aims to combine different imaging methods to guide electrical brain stimulation that improves the recovery of movement for stroke patients, potentially benefiting over half a...
This federal Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS), under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) program, provides $577,880 to the Regents of the University of Michigan to develop advanced deep learning algorithms for continuous control of finger and wrist movements using implantable electromyography (EMG) signals. The key objectives are to: 1) utilize deep learning techniques to enable...
This $750,000 Project Grant from the National Science Foundation's Technology, Innovation, and Partnerships program will fund the development of appropriate rehabilitation technology for stroke survivors through passive tactile stimulation. The Leland Stanford Junior University will lead an interdisciplinary team including universities, hospitals, and community organizations to finalize the team composition, generate use cases, and develop a comprehensive research plan including initial...
This $317,119 Project Grant award from the National Institute of Child Health and Human Development (CFDA 93.865 - Child Health and Human Development Extramural Research) to the University of Texas at Austin aims to demonstrate the feasibility of a real-time, personalized brain state-dependent transcranial magnetic stimulation (TMS) system to enhance post-stroke hand rehabilitation. The key objectives are to: 1) Establish the feasibility of delivering TMS stimulation only during personalized...
This Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS) under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) program provides $652,497 over a 5-year period from May 1, 2025 to April 30, 2030. The primary objectives are to: (1) determine the neuroanatomical and neurophysiological signatures of proximal upper extremity motor control after stroke, (2) define changes in motor control induced by targeted...
This $997,735 cooperative agreement from the National Science Foundation will support Neurotechr3 Inc.'s development of a personalized telerehabilitation solution for individuals recovering from stroke-related arm and hand impairments. The awardee will advance its machine learning-driven telerehabilitation system through new exergames, personalized rehabilitation plans synchronized with patient recovery trajectories, and clinical evaluations. The system aims to improve access to effective...
This $800,000 National Science Foundation project grant will fund research at Florida Atlantic University to develop technology enabling disabled individuals to control advanced prosthetic devices. Specifically, the grant will support exploration of novel bimodal skin sensors, investigation of machine learning algorithms to classify user intent, and creation of a reinforcement learning paradigm for customized muscle training exercises. The goal is to empower those with upper limb deficiencies to...
This Project Grant award for $465,840 from the National Institute of Child Health and Human Development (NICHD), under the Child Health and Human Development Extramural Research program (CFDA 93.865), aims to develop and evaluate a novel data-driven, model predictive functional electrical stimulation (FES) controller that utilizes ultrasound-derived feedback for improving post-stroke gait. The key products or services to be delivered through this funding include: 1) developing a new...

HCC: MEDIUM: A NOVEL NEURAL INTERFACE FOR USER-DRIVEN CONTROL OF REHABILITATION OF FINGER INDIVIDUATION -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.

Posted 8/4/23, 12:00 AM