Muhammad Ahmed Khan, PhD

A systematic review on functional electrical stimulation-based rehabilitation systems for upper limb post-stroke recovery

M.A. Khan, H. Fares, H. Ghayvat, I. Brunner, S. Puthusserypady, B. Razavi, M. Lansberg, A. Poon and K. J. Meador

Frontiers in Neurology, 2023, 14:1272992, DOI: 10.3389/fneur.2023.1272992

SmartRehab - Hybrid BCI and EMG-Based functional electrical stimulation system for stroke rehabilitation

M.A. Khan, B. Razavi, M. Lansberg, I. Brunner, S. Puthusserypady and K. J. Meador

Journal of Neural Engineering. (Under Review)

AI Meets Neurorehabilitation: Deep Convolutional Neural Network for Motor Imagery Task Classification in Stroke Patients Using EEG Signals

M.A. Khan, C. Uyanik, I. Brunner, S. Puthusserypady

IEEE Transactions on Neural Networks and Learning Systems (Under Review)

Myoelectrically-Controlled Functional Electrical Stimulation System (Myo-FES) with Integrated Flex Sensor for Home-Based Stroke Rehabilitation and Functional Recovery Monitoring: A Pilot Study

M. Saibene, M.A. Khan, C. Uyanik, S. Puthusserypady

10th International Conference on Intelligent Informatics and BioMedical Sciences, Dec. 2025 (Accepted)

AiCarePWP: Deep learning-based novel research for Freezing of Gait forecasting in Parkinson

H. Ghayvat, M.Awais, R. Geddam, M.A. Khan, L. Nkenyereye, G. Fortino, and K. Dev

Computer Methods & Programs in Biomedicine, Sept. 2024, DOI: 10.1016/j.cmpb.2024.108254

Next-Generation Wearable Wireless EEG Recorder: The future of accessible neural applications, from mental health monitoring to a noninvasive brain–computer interface

C. Chen, J. Yang, J. Sands, M.A. Khan, A. S. Y. Poon

IEEE Solid-State Circuits Magazine, vol. 14, no. 4, pp. 37-50, Nov. 2022, DOI: 10.1109/MSSC.2022.3202738

Emergence of flexible technology in developing advanced systems for post-stroke rehabilitation: a comprehensive review

M.A. Khan, M. Saibene, R. Das, I. Brunner, S. Puthusserypady

Journal of Neural Engineering, 2021, vol. 18, DOI: https://doi.org/10.1088/1741-2552/ac36aa

Motor Imagery EEG Signal Classification for Stroke Survivors Rehabilitation

A. E. Voinas, R. Das, M.A. Khan, I. Brunner and S. Puthusserypady

2022 10th International Winter Conference on Brain-Computer Interface (BCI), 2022, DOI: 10.1109/BCI53720.2022.9734837

Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: From designing to application

M.A. Khan, R. Das, H.K. Iversen, S. Puthusserypady

Computers in Biology and Medicine, Aug 2020; DOI: 10.1016/j.compbiomed.2020.103843

Implantable Autonomous Device for Wireless Force Measurement in Total Knee Prosthesis

M.A. Khan, M. Borghetti, M. Serpelloni, E. Sardini

IEEE Instrumentation & Measurement Magazine, Feb. 2019, Vol. 22, Issue 1: 39-47, DOI: 10.1109/MIM.2019.8633351

EEG-based BCI systems for neurorehabilitation applications

M.A. Khan, R. Das, J.P. Hansen, and S. Puthusserypady

Brain and Behavior Computing, 189-219, Jan. 2021