Development of a multimodal participation assessment system for upper limb rehabilitation


Thesis Type: Doctorate

Institution Of The Thesis: Cukurova University, Fen Bilimleri Enstitüsü, Elektrik-Elektronik Mühendisliği, Turkey

Approval Date: 2022

Thesis Language: English

Student: ERKAN ÖDEMİŞ

Supervisor: Cabbar Veysel Baysal

Abstract:

In conventional and robotic rehabilitation, the patient's active participation in
exercises is crucial for maximum functional output to be received from therapy. In
rehabilitation exercises performed with robotic devices, the difficulty levels of therapy
tasks and the device assistance are adjusted based on the patient's therapy performance
to improve active participation. However, the existing therapy performance evaluation
methods are based on either some specific device designs or certain therapy tasks,
which limits their widespread use. Hence, there is a requirement to develop an
independent performance measurement system. In this thesis, 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 level and
slacking, which are substantial factors affecting the therapy performance. The designed
system is tested with healthy subjects and clinically with frozen shoulder syndrome
patients. The experimental results showed that the proposed system evaluates subjects'
participation successfully and adjusts the therapy tasks and difficulty levels of tasks
according to subjects' performance and tiredness