About

Jacob Anthony George, PhD, is a faculty member in the Department of Physical Medicine & Rehabilitation at the Spencer Fox Eccles School of Medicine. His academic background includes an undergraduate degree from The University of Texas at Austin, where he also completed his graduate training with a Master of Science degree. He earned his PhD from the University of Utah. Dr. George's professional focus is within the field of physical medicine and rehabilitation, contributing to the academic and clinical missions of the university. His research interests and specific contributions are not detailed in the provided page text.

Research topics

• Medicine
• Neuroscience
• Physical medicine and rehabilitation
• Psychology
• Biomedical engineering
• Computer Science
• Audiology
• Artificial Intelligence
• Computer vision
• Cognitive psychology
• Simulation
• Chemistry
• Engineering
• Pathology
• Physics

Selected publications

• An Intuitive, Bidirectional, and Adaptive Functional Electrical Stimulation System for Hand Rehabilitation

  IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2026-01-01

  articleOpen accessSenior author

  After a neuromotor injury, such as a stroke or spinal cord injury, patients are faced with decreased independence and quality of life due to limited hand function. Functional electrical stimulation (FES) therapy can improve patients' recovery. However, this technology is underutilized in clinics due to complex and long setup times, and there is a distinct lack of commercially available FES systems for hand therapy. In this work, we present a closed-loop, bidirectional FES system specifically designed for grasping rehabilitation. The proposed FES system leverages a first-order, adapting local model of muscle activation dynamics to control grip force by modulating the FES amplitude. We demonstrate with 12 healthy participants that the adaptive controller provides more accurate control than an autotuned PID controller. We also validate that the FES system works with a C5 spinal cord injury (SCI) participant exhibiting a typical upper motor neuron pattern of spasticity. Each participant also completed a longer-duration fatiguing experiment, and we observed that not only does the controller adapt to accurately control contractions as the activated muscles fatigue, but the model parameters are strongly correlated with fatigue and could be used to measure fatigue in real time. Finally, we show that a previously untrained user can set up the FES system in under 5 minutes. These results demonstrate the benefits of using adaptive models for FES control and can be used as a guide to design effective, translatable FES systems.

  PublisherDOI

• The Electronic Grip Gauge (EGG): Automated Assessment of Sensorimotor Hand Function Using an Instrumented Fragile Object

  IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2026-01-01

  articleOpen accessSenior author

  Hand dexterity assessments play a crucial role in informing the rehabilitative care of individuals with upper-limb hemiparesis. However, current assessments often struggle to evaluate the hand's ability to precisely control grip force, a skill vital for daily activities like handling fragile objects. Here we describe the design of the Electronic Grip Gauge (EGG), an adjustable-weight, instrumented "fragile" object that measures grip force, load force, acceleration, orientation, and relative position. Embedded sensors enable automatic segmentation and analysis of EGG transfers in various modes. In "Non-Fragile" mode, there is no break threshold; the EGG serves as an automated variant of the Box-and-Blocks test. In "Fragile" mode, the EGG simulates fragility by playing a "break" noise if grip force exceeds a set threshold, requiring grip control to prevent breaks. In "Fragile-Feedback" mode, audio-visual feedback is provided proportional to applied grip force to supplement potentially impaired tactile feedback. Demonstrating functionality, we evaluated sensorimotor differences between 26 hemiparetic and 26 age-matched healthy participants. In "Fragile" mode, paretic hands were significantly slower, applied excessive force, and broke the EGG more frequently than contralateral and healthy control hands. In "Fragile-Feedback" mode, a subset of paretic hands improved, transferring the EGG faster and/or with less force. This work demonstrates the EGG's utility in automatically quantifying sensorimotor deficits and that, for a subset of hemiparetic patients, audiovisual feedback could potentially coach and rehabilitate hand function. Collectively, this work showcases the EGG's potential as both an assessment and rehabilitation device for grip force control-a critical skill in hand therapy.

  PublisherDOI

• Predicting Motor Intent from Residual Neck Muscle Activity in Individuals with Neck Weakness from ALS

  2025-07-14 · 2 citations

  articleOpen accessSenior author

  The long-term goal of this work is to restore dexterous and intuitive head-neck motion to patients with Amyotrophic Lateral Sclerosis (ALS). ALS is an idiopathic disease characterized by progressive paralysis. Some patients experience neck weakness such that their heads permanently drop to their chests, causing pain and extreme difficulty eating, navigating, and socializing. We previously developed the Utah Neck Exoskeleton, a powered neck brace that supports the head and uses electric motors to move the head in a large range of motion, counteracting head drop. However, the exoskeleton has been controlled either with a joystick or gaze tracking, both of which are difficult to use for parts of the ALS population. Here, we show that the residual neck muscles of ALS patients with neck weakness can be used to determine intended neck position and motion. Electromyographic (EMG) signals were recorded from the neck muscles of two individuals with ALS, low clinical functional scores, and self-reported neck weakness. EMG was then mapped to either steady-state head position or the direction of head motion using convolutional neural networks. Despite the patients having neck weakness and limited range of motion, EMG signals were sufficient to accurately classify both steady-state head position and the direction of head motion (97.1% and 83.12% median accuracy, respectively). As such, this work demonstrates that EMG may serve as a dexterous and intuitive control modality for real-time head-neck movement, and in conjunction with the Utah Neck Exoskeleton, may ultimately improve quality of life for individuals with head drop.Clinical RelevanceResidual neck muscle activity in ALS patients can be recorded via surface EMG and potentially used to reliably predict intended head position and motion.

  PublisherOA PDFDOI

• Reinforcement Learning Agent Trained as FES Controller in Modified Xia-Law Simulation Robustly Controls Grip Force

  2025-07-14

  articleOpen accessSenior author

  The long-term goal of this research is to improve the adoption of functional electrical stimulation (FES) therapy in rehabilitation clinics. FES has been demonstrated to be an effective tool for rehabilitating stroke and spinal cord injury patients. However, it is not frequently used in clinics, mainly due to long setup times and unfamiliarity with choosing stimulation parameters to get acceptable muscle activation. Here, we develop an FES controller that performs across a range of stimulation parameters without a loss in performance. We trained a reinforcement learning agent with a novel FES-muscle activation model to control contraction by modulating the stimulation amplitude such that control is unaffected by stimulation parameter choice. The trained FES agent was then used to control the grip force of healthy participants using a range of pulse widths, and the root-mean-square error (RMSE) was used to quantify the FES agent's accuracy with each pulse width. The FES agent was tested using 200 μs, 300 μs, and 400 μs pulse widths and achieved root-mean-square errors of 3.50% of the maximum evoked contraction (MEC), 3.59% MEC, and 3.45 % MEC, respectively. We found that the agent's control of grip force was robust and unaffected by the selected pulse width. These results can help guide the development of FES systems that are not only accurate but also simple to use.Clinical Relevance- This reduces the complexity of FES systems, which will decrease the time and training required to set up FES systems and increase clinical acceptance of FES therapy.

  PublisherOA PDFDOI

• Improved Prediction of Activities of Daily Living from Wrist Electromyography Using Intermediate Gesture Classification

  2025-07-14

  articleOpen accessSenior author

  The long-term goal of this research is to automatically, remotely, and noninvasively identify Activities of Daily Living (ADLs) using muscle activity at the wrist. Alzheimer's Dementia is a widespread condition affecting patients' memory and ability to care for themselves. A wrist-worn device capable of monitoring precise ADLs could increase patient independence and provide caretakers with detailed information regarding the patient's wellbeing. Here, we investigate the use of an intermediate hand gesture classifying algorithm to predict ADLs using wrist electromyography (EMG). We show that predicted gestures are well-represented within the span of ADLs, and that the repertoire of predicted gestures appears distinct among ADLs. Importantly, we show that a simple linear discriminant analysis of predicted gestures provides better and more efficient classification accuracy relative to a state-of-the-art neural network that predicts ADLs directly from EMG. Accurate and efficient classification of ADLs from a wrist-worn device can provide a foundation for remote monitoring of patients in a socially acceptable formfactor. More broadly, a better understanding of human behavior via ADL tracking can enable new assistive technologies that improve quality of life.Clinical Relevance-Monitoring activities of daily living with an electromyographic smart watch can provide insights into patient behavior and wellbeing.

  PublisherOA PDFDOI

• Quantifying the Cognitive Demand of Controlling a Prosthesis with a Secondary Detection Response Task

  2025-07-14

  articleOpen accessSenior author

  Up to 44% of upper-limb amputees abandon their prosthesis due to difficulty with control. More intuitive control is needed, but innovation is difficult without a valid and reliable way to measure intuitiveness. Here, we validate a secondary detection-response task (DRT) as a method to objectively measure the cognitive load of using a prosthesis. The DRT is a simple, yet sensitive measure of cognitive resource allocation based on response rate and reaction time to vibratory stimuli. Participants completed a primary task involving moving objects with varying fragility over a barrier without breaking them with their intact hand and with a prosthetic hand controlled by electromyography. While completing the primary task, participants also completed the secondary DRT in which they responded to randomly delivered vibratory stimuli as quickly as possible by pushing a button with their contralateral limb. Participants also completed the NASA Task Load Index, a survey commonly used to assess subjective workload. Results showed that response time and rate were reliable indicators of cognitive load, suggesting that the DRT can objectively measure cognitive load in prosthesis use, thereby guiding future innovation for more intuitive prosthetic control.Clinical Relevance- This research establishes the use of a secondary detection response task as a valid and reliable assessment of cognitive load during prosthesis use.

  PublisherOA PDFDOI

• Multi-Channel Functional Electrical Stimulation to Improve Specificity of Hand Extension

  2025-07-14

  articleOpen accessSenior author

  The long-term goal of this research is to improve the functionality of non-invasive transcutaneous functional electrical stimulation (FES) by improving specificity in upper extremity paralysis. Spinal cord injuries result in an estimated 10,000 new cases of upper extremity paralysis yearly. FES has been used extensively to assist and rehabilitate individuals with lower-limb paralysis, but it has not been widely adopted for upper-limb paralysis. This is in part due to the complex setup necessary to target the right combination of small muscles densely packed in the forearm to create a desired hand gesture. To address this challenge, here we introduce a new multichannel FES system that enables complex current steering with a high compliance voltage to selectively recruit small extrinsic hand muscles in isolation or in combination. Using this system with real-time motion capture data of the hand, we stimulated unique electrode configurations each second to rapidly identify a rich repertoire of hand gestures. Additionally, as an initial demonstration of the unique current steering capabilities, we show that FES involving three active electrodes, instead of the traditional 2-electrode setup, provides greater specificity and redundancy, which in turn could support more therapeutic motions and interleaved stimulation to reduce fatigue Thus, this work constitutes an important step towards more efficient, dexterous, and robust upper-limb FES to improve neurorehabilitation outcomes for people with spinal cord injuries.Clinical Relevance- A new multichannel FES system can rapidly configure FES stimulation to evoke a variety of single-digit and multi-digit hand gestures.

  PublisherOA PDFDOI

• Cold Tissue Temperature Decreases Electrocutaneous Sensory Perception and Discriminability

  2025-07-14

  articleOpen accessSenior author

  The long-term goal of this research is to design robust haptic feedback systems for prostheses. Limb loss significantly affects quality of life, and current prosthetic systems often fail to work across the diverse environmental conditions experienced in our day-to-day lives. Prior work has demonstrated the utility of electrocutaneous (EC) stimulation as a form of haptic feedback and sensory restoration. Here, we explore the impact of tissue temperature on the perception of sensations evoked by EC stimulation. We show that tissue temperature significantly influences perceived intensity and sensory thresholds during EC stimulation, with colder temperatures reducing perceived intensity and elevating detection thresholds compared to normal body temperatures. On average, perceived intensity was 20% less for cold conditions (0.921 ± 0.154, warm; 0.739 ± 0.270, cold), and detection threshold was 27% higher for cold tissue (2.44 ± 0.66mA, warm; 3.09 ± 1.05mA, cold). Subjective reports also indicated some qualitative changes in sensations between cold and warm conditions. These findings suggest that environmental temperature directly impacts the efficacy of haptic feedback systems, providing critical insights for robust prosthetic design.Clinical Relevance- Artificial sensory feedback used in prostheses is less effective in cold temperatures.

  PublisherOA PDFDOI

• Functional and Structural Neural Plasticity Following sEMG Control of a Virtual Prosthetic Hand in an Individual with Bilateral Upper-Limb Congenital Amputation

  2025-07-14

  articleOpen access

  Here we document cortical neural connectivity changes associated with several weeks of prosthetic use in an individual with bilateral upper-limb congenital amputation. Secondly, we explore how those changes relate to prosthetic performance over time. Previous research in unilateral aplasia has shown that functional brain connectivity and activations can be disrupted in the missing hand area, and that prosthetic use can normalize those abnormalities. Functional connectivity and prosthetic use related brain changes in individuals with bilateral congenital upper limb amputations have not been defined. Here, we describe functional and structural connectivity changes measured with MRI after 10-weeks' unilateral use of an sEMG-controlled virtual prosthetic in an individual with aplasia born without either arm. We find that both functional connectivity and structural connectivity change with sEMG prosthetic use. Specifically, functional connectivity of motor regions tends to lateralize and become more hemisphere specific. Additionally, structural connectivity of motor cortico-spinal white matter projections and interhemispheric commissural projections increase after sEMG prosthetic use. These functional connectivity changes are different from those previously reported for one-handed congenital amputees, where prosthetic use normalized, not lateralized, imbalanced interhemispheric motor connectivity. Alongside these neural changes, sEMG virtual prosthetic performance both increased and decreased over time, depending on the action performed. Our results suggest that neural representations of bilateral congenital amputation and subsequent neural adaptions with unilateral prosthetic use may be distinct from those of unilateral congenital and traumatic upper-limb amputees. Consideration of condition-specific neurobiology may be critical in developing effective neuro-prostheses.Clinical Relevance- This describes the neural changes induced by sEMG prosthetic control in a congenital bilateral amputee.

  PublisherOA PDFDOI

• A Low-Profile High-Density Electromyography Neckband for Recording Neck Muscle Activity

  2025-07-14 · 2 citations

  articleOpen accessSenior author

  The predominant use of electromyography (EMG) with the extremities has led to specific form factors conducive to the arms and legs. Here, we describe the design and validation of a new wearable for recording EMG from the neck. EMG from the neck is useful for intraoperative neuromonitoring, outpatient monitoring of disease progression, and control of assistive technology. The current approach of using adhesive electrodes is time consuming and not practical for extended at-home use. Here, we introduce a low-profile, high-density EMG neckband that supports the unique requirements of the neck. The EMG neckband ensures broad muscle coverage across a range of neck sizes without hindering neck mobility or function (e.g., breathing, eating, speaking). Relative to the clinical and research standard of adhesive electrodes, the EMG neckband provides significantly faster donning and doffing times (seconds instead of minutes) and comparable signal quality and myoelectric control. This work constitutes an important step towards the translation of neck EMG as an assistive and diagnostic wearable, which in turn may improve quality of life for individuals with neuromuscular impairments.

  PublisherOA PDFDOI

Recent grants

• Patient-centered rehabilitation and dexterous assistive devices for stroke patients using bionic exoskeletons controlled by non-invasive electromyography

  NIH · $2.1M · 2020–2026

Frequent coauthors

• Gregory A. Clark

  University of Utah

  35 shared

• Mark R. Brinton

  Salt Lake Community College

  18 shared

• Tyler S. Davis

  University of Utah

  17 shared

• Christopher C. Duncan

  University of Utah

  11 shared

• Douglas T. Hutchinson

  University of Utah

  10 shared

• Michael D. Paskett

  University of Utah

  10 shared

• Connor D. Olsen

  University of Utah

  8 shared

• Troy N. Tully

  University of Utah

  8 shared

Education

• B.S.

  The University of Texas at Austin