Browsing by Author "Bhattacharya, Sutapa"

Stroke is a leading cause of adult death and disability, often followed by muscle weakness, loss of control and coordination in limbs and movement disorders. Rehabilitation is critically important to restore function in damaged body parts and help the stroke-surviving individuals regain ability to independently perform everyday activities. Continuing post-stroke rehabilitative therapy at the hospital is difficult due to economic pressure and limited resources of the health care system. Also, taking help of an always-present therapist is too expensive for many patients. A relatively new approach towards stroke rehabilitation is developing technology-assisted rehabilitative system. In this study we developed a Virtual Reality based system to enhance the endurance and coordination skill of stroke patients with forearm movement disorder. This system can be used by the patient at home as per his convenience, with minimal dependency on a physiotherapist or a caregiver. Our paper describes the system design of this proof-of-concept application. The preliminary results of testing and feasibility studies suggest that the endurance and coordination skill of the participants (two able-bodied and one stroke-surviving person) improved with repeated attempts. This indicates that our system is a definite step towards becoming a simple, technology-assisted solution for rehabilitation of upper-limb movement disorder. © 2013 IEEE.

Stroke is a leading cause of adult death and disability, often followed by muscle weakness, loss of control and coordination in limbs and movement disorders. Consequently, stroke-surviving individuals with hemiplegia are often unable to perform simple tasks like opening and closing of their affected (unhealthy) hand, making them dependent on a caregiver for day-to-day activities. At the same time their healthy hand retains ability for normal activities. Rehabilitation aims to improve their ability to use their affected hand similar to their use of healthy hand. The degree of closure (flexion) of one’s hand can be mapped from surface Electromyogram (sEMG) signal of Flexor Carpi Radialis muscle present on the anterior side of one’s forearm. The different degrees of flexion can be classified with the help of Support Vector Machines (SVM) using the sEMG signals from the Flexor Carpi Radialis muscle. In this study we developed a proof-of-concept Virtual Reality based real-time rehabilitative system for post-stroke hand movement disorder. Our developed system uses the sEMG data obtained from the healthy hand of stroke-surviving individuals as training dataset for classifying the degree of flexion of their respective stroke-affected hand while they interact with the VR-based tasks, and triggers therapeutic electrical stimulation to be applied to the muscles of the unhealthy hand of the stroke-surviving individuals based on their performance feedback. This system can be used by the patient at home as per his convenience, with minimal dependency on a physiotherapist or a caregiver. The preliminary results of testing and feasibility studies suggest that the hand flexion and extension skills of the participants (six able-bodied and two stroke-surviving persons) improved with repeated attempts. This indicates that our system has the potential to take a definite step towards becoming a simple, technology-assisted solution for rehabilitation of hand movement disorder.

Neurological disorders often manifest themselves in the form of movement deficit on the part of the patient. Conventional rehabilitation often used to address these deficits, though powerful are often monotonous in nature. Adequate audio-visual stimulation can prove to be motivational. In the research presented here we indicate the applicability of audio-visual stimulation to rehabilitation exercises to address at least some of the movement deficits for upper and lower limbs. Added to the audio-visual stimulation, we also use Functional Electrical Stimulation (FES). In our presented research we also show the applicability of FES in conjunction with audio-visual stimulation delivered through VR-based platform for grasping skills of patients with movement disorder.