This paper examines the usefulness of psychophysiological measurements in a biocooperative feedback loop that adjusts the difficulty of an upper extremity rehabilitation task. Psychophysiological measurements (heart rate, skin conductance, respiration, and skin temperature) were used both by themselves and in combination with task performance and biomechanics. Data fusion was performed with discriminant analysis, and a special adaptive version was implemented that can gradually adapt to a subject. Both healthy subjects and hemiparetic patients participated in the study. The accuracy of the biocooperative controller was defined as the percentage of times it matched the subjects' preferences. The highest accuracy rate was obtained for task performance (approximately 82% for both healthy subjects and patients), with psychophysiological measurements yielding relatively low accuracy (approximately 60%). The adaptive approach increased accuracy of psychophysiological measurements to 76.4% for healthy subjects and 68.8% for patients. Combining psychophysiology with task performance yielded an accuracy rate of 84.7% for healthy subjects and 89.4% for patients. Results suggest that psychophysiological measurements are not reliable as a primary data source in motor rehabilitation, but can provide supplementary information. However, it is questionable whether the amount of additional information justifies the increased complexity of the system.
© 2011 IEEE