Extracting Pattern of Arm Movements based on EMG Signal for Stroke Therapy

This paper presents the investigation pattern of arm movements for the purpose of the rehabilitation for a stroke patient in the virtual reality (VR) environments. The investigation results are used to design the virtual objects in the virtual environments. The muscle activities are analyzed by using electromyography (EMG). Six EMG channel are attached to the right arm of the subject, which is at the location of deltoid anterior fibres, deltoid middle fibres, bicep, triceps, flexor and extensor while performing arm movements. The electrical signals acquired from EMG are analyzed to extract the signal’s pattern by using signal processing technique. In the studies, several fundamental arm movements are performed by the subject and the acquired patterns of EMG signals are defined as muscle activities. The experimental results show that deltoid, bicep and triceps move with a significant value compared with flexor and extensor and are used to investigate the muscle activities, which is suitable to the stroke therapy.