Xiaogang Hu

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Assistant Professor

University of North Carolina at Chapel Hill

United States

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Xiaogang Hu is an Assistant Professor at the University of North Carolina at Chapel Hill, USA. His research areas include surface electromyography, neural decoding for finger motion, and applications in medical technology. His recent articles focus on efficient motor unit activity predictions, dexterous finger force control, and the implications of nerve stimulation strategies.

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Using surface electromyography to assess motor unit structural change post stroke

Open Date: 2014-06-01

Close Date: 2016-06-01

Xiaogang Hu

Research Interests

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About

Recent Grants

Articles (20)

Cross-person decomposition of surface electromyogram for efficient motor unit activity predictions

Robust and Lightweight Decoder for Unsupervised Multifinger Force Predictions Toward the Internet-of-Medical-Things-Based Applications

Spatial-Temporal Dynamics of Evoked Action in Finger Flexors: Implications for Optimizing Transcutaneous Nerve Stimulation

Unsupervised Neural Decoding to Predict Dexterous Multi-Finger Flexion and Extension Forces

Long-Term Finger Force Predictions Using Motoneuron Discharge Activities

Minimizing Sensory Habituation in Nerve Stimulation Through Strategic Temporal Stimulation Patterns

Real-Time Myoelectric-Based Neural-Drive Decoding for Concurrent and Continuous Control of Robotic Finger Forces

Quantifying Muscle Co-Activation for Impaired Finger Independence in Stroke Survivors

Decomposing Task-Relevant Information From Surface Electromyogram for User-Generic Dexterous Finger Force Decoding

Modified motor unit properties in residual muscle following transtibial amputation

Offline Evaluation Matters: Investigation of the Influence of Offline Performance on Real-Time Operation of Electromyography-Based Neural-Machine Interfaces

Concurrent and Continuous Prediction of Finger Kinetics and Kinematics via Motoneuron Activities

Asynchronous axonal firing patterns evoked via continuous subthreshold kilohertz stimulation

Optimized Model Selection for Concurrent Decoding of Finger Kinetics and Kinematics

Finger Force Estimation Using Motor Unit Discharges Across Forearm Postures

Resembled Tactile Feedback for Object Recognition Using a Prosthetic Hand

Evoked Tactile Feedback and Control Scheme on Functional Utility of Prosthetic Hand

Adaptive Real-Time Decomposition of Electromyogram During Sustained Muscle Activation: A Simulation Study

Object Recognition via Evoked Sensory Feedback during Control of a Prosthetic Hand

Closed-loop control of a prosthetic finger via evoked proprioceptive information

Collaborators (2)

Katherine Saul

He Huang

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