Akademik Veri Yönetim Sistemi
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, cilt.70, sa.1, ss.1-27, 2021 (SCI-Expanded)
The patient’s active participation in exercises is a crucial factor to increase the functional outputs received from
therapy. For improving the patient’s active and voluntary involvement, the difficulty levels of therapy tasks and
the device assistance are adjusted based on the patient’s therapy performance. However, the existing performance
evaluation methods are based on either some specific device designs or certain therapy tasks. In this work,
a patient performance evaluation method is proposed based on a multimodal sensor fusion formed by the trajectory
tracking error signal and the patient’s physiological responses (heart rate and skin conductance) during
the upper extremity rehabilitation. The novelty of the system is assessing the patient’s performance independently
from any device designs or therapy tasks. The developed system also evaluates the patient’s tiredness and
slacking, which are substantial factors affecting the therapy performance. The patient’s upper limb joints’ angles
are measured via inertial measurement unit sensors. Arm movements of the patient are estimated by an upper
limb kinematic module for evaluating the trajectory tracking. The patient’s performance, tiredness, and slacking
are assessed by a fuzzy inference system using physiological responses and exercise profile. The developed
system is tested experimentally with healthy subjects on five therapy tasks. Also, for demonstrating the proposed
method efficacy, additional experiments have been performed for different cases while measuring the sEMG
signals of the subjects. The experimental results showed that the proposed system estimates subjects’ participation
successfully and adjusts the therapy tasks according to subjects’ performance and tiredness.