Deans' stroke musings: AI-Driven Hybrid Rehabilitation: Synergizing Robotics and Electrical Stimulation for Upper-Limb Recovery After Stroke

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Tuesday, June 17, 2025

AI-Driven Hybrid Rehabilitation: Synergizing Robotics and Electrical Stimulation for Upper-Limb Recovery After Stroke

You'll have to depend on your competent? doctor to get this. Do you have a functioning stroke doctor or not?

AI-Driven Hybrid Rehabilitation: Synergizing Robotics and Electrical Stimulation for Upper-Limb Recovery After Stroke

Ismail Ben Abdallah¹

Yassine Bouteraa^2*

Ahmed Alotaibi³

¹Advanced Technologies in Medicine and Signals (ATMS), Ecole Nationale d’Ingénieurs de Sfax (ENIS), University of Sfax, Sfax 3038, Tunisia, Sfax, Tunisia
²Department of Computer Engineering, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia, Riadh, Saudi Arabia
³Department of Mechanical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia., Taif, Saudi Arabia

This study presents an AI-enhanced hybrid rehabilitation system that integrates a dual-arm robotic platform with electromyography (EMG)-guided neuromuscular electrical stimulation (NMES) to support upper-limb motor recovery in stroke survivors. The system features a symmetrical robotic arm with real-time anatomical adaptation for bilateral therapy and incorporates a Support Vector Machine (SVM)-based model for continuous muscle fatigue detection using time-frequency features extracted from EMG signals. A ROS2-based architecture enables real-time signal processing, adaptive control, and remote supervision by clinicians. The system dynamically adjusts stimulation parameters based on fatigue classification results, allowing personalized and responsive therapy. Preliminary clinical validation with three post-stroke patients demonstrated a 44% increase in range of motion, 45% enhancement in active torque, and 36% reduction in passive torque. The SVM model achieved a 95% accuracy in fatigue detection, and initial patient results suggest the feasibility and potential benefits of this intelligent, closed-loop rehabilitation approach.