UP releases study on robotic assisted stroke rehabilitation

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March 29, 2026 | 12:00am

MANILA, Philippines — Researchers achieved an 86-percent response accuracy rate for a hand orthosis for stroke rehabilitation, using surface electromyography signals, a study released by University of the Philippines (UP) Diliman Office of the Vice President for Academic Affairs showed.

Authors Micah Angelo Bacani and Manuel Ramos Jr. of the Electrical and Electronics Engineering Institute of UP Diliman said loss of control in gripping with the hand is a possible long-term effect of stroke and that recovery is possible through rehabilitation.

According to the study, robotic assistive technology can be used for such rehabilitation.

“Using surface electromyography (sEMG) signals from the arm, the recovering stroke patient can control the robotic assistive device for rehabilitation. This is the myoelectric hand orthosis,” the authors said.

The research noted that based on studies conducted in the early 2000s, patients who lose or experience impaired motor function in the upper limb are more likely to recover if the therapy includes active patient participation on a neurological level, rather than passively following a predetermined set of movements with an assistive device.

“Thus, robotic assistive technology needs to function on a stimulus or control initiated by the patient. Surface electromyography is a non-invasive technique that detects muscle activity and translates it as an electrical signal that can be measured in the frequency spectrum, amplitude or the action potential,” the research said.

The authors added that using sEMG has proven to be an accurate control signal in the context of robotic assistive technology in rehabilitation, by using an array of electrodes to cover the major muscle groups involved in the movement being allowed and aided by the assistive technology.

“This work explored the potential of using the magnitude of the sEMG signal to control the force exerted by the hand orthosis and to make it proportional to the user’s intended force. Testing results showed a linear, directly proportional relationship between the user’s applied force and the magnitude of the electromyography signal, enabling this control signal to be used in force-control applications of the prototype,” the authors added.