Engineering HDR Seminar Series 4, 2011: EMG Driven Musculoskeletal Model for Robot Assisted Stroke Rehabilitation System

Ms. Veronica Lestari Jauw, RAM postgraduate student

Date: 2011-05-06
Time: 10:00 to 11:00
Venue: Meeting Room 1, 5-4-22, School of Engineering


Neurorehabilitation aims to aid the recovery/rehabilitation of neurological patients following strokes, spinal cord injuries, traumatic brain injuries as well as other neurological diseases and injuries. This research is primarily aimed at developing an automated and predictive rehabilitation therapy concept for individuals who have suffered strokes resulting specifically in arm impairment. The utilization of a rehabilitative robot can offer a repetitive and intensive rehabilitation training which helps improve the recovery rate and introduce a channel for patients to train independently or with minimal supervision. The developed system will leverage on electromyography (EMG) to measure the electrical activity of the muscles in question during contraction allowing data analysis and thus decision making. This can then drive the force/torque output to control the kinematic movement of the rehabilitation robot driven by an artificial neural network (ANN) adaptive system. The ANN will be optimized using both simulated annealing (SA) and genetic algorithm (GA) to map the EMG signals of the muscles into force/torque produced by the shoulder and elbow movement. Full wave rectification and adaptive noise filter are also introduced in this paper to attain clearer picture of muscle effort. In addition to that, a database repository is maintained to carry out data analysis and processing, signal processing, performance evaluation for each patient. The main focus on this research is to develop a prototype rehabilitative robot leveraging on an artificial neural network adaptive system to map EMG signals from 16 muscles into the force/torque control and establish the appropriate control system.

About the Speaker

Ms Veronica Lestari Jauw is a postgraduate student in the School of Engineering, who commenced her Master candidature since 1st May 2010. She is currently pursuing her postgraduate study in "EMG Driven Musculoskeletal of Upper Extremities for Stroke Rehabilitation" under the supervisions of Dr S. Parasuraman, Dr Arosha Senanayake (external) and Associate Professor Bijan Shirinzadeh (MUA). Her primary research focus is on the fundamental studies of the behavior of the muscles by means of EMG system with aims at establishing the control system controlling the rehabilitation arm. This research work is aligned to Campus Research Strength: Robotics, Automation and Manufacturing (RAM) and the seminar is organized as part of the Faculty’s requirement for candidature conversion from Masters to PhD.