Quantifying the Performance of Wireless Data Acquisition System to Assess Upper Limb Spasticity

• Published in: 2022 IEEE 5th International Symposium in Robotics and Manufacturing Automation, ROMA 2022
• Main Author: Othman N.A.; Zakaria N.A.C.; Hanapiah F.A.; Hashim N.M.; Johar K.; Low C.Y.; Yee J.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141584020&doi=10.1109%2fROMA55875.2022.9915667&partnerID=40&md5=d9e2c5bd1440d40169d2327d6e95d92f

Performance of a data acquisition system is very important to ensure consistency of the device in collecting quantitative data from patient with spasticity. This study is conducted by two raters with different years of experience, using Wireless Data Acquisition Systems from Biometrics Ltd in compliance with Modified Ashworth Scale (MAS) as a measurement tool. Clinical data from 6 samples of patient with spasticity with different MAS score were analyzed using (i) Levene's test to compare the quantitative data by analyzing the homogeneity of the variance and, (ii) Pearson Correlation Coefficient (PCC) to determine the correlation of force exerted by the raters during clinical assessment. Objectives of this study are, (i) to evaluate the variance of the equality of the quantitative data, and (ii) to define the correlation of force exerted between Rater 1 and Rater 2. From the conducted research, the homogeneity of angle variance and force is not significant due to inconsistence stretch period during slow and fast stretch. The r-score from PCC analysis for force is showing an unsatisfied correlation due to the different force exerted by the rater. Consequently, an experienced rater has an important role in assisting patients with spasticity. Withstanding by the result obtained, the Wireless Data Acquisition Systems by Biometrics Ltd is attested to be a data acquisition system for clinical usage. It is suggested to improve the quantitative data by increase the number of patients with spasticity. © 2022 IEEE.