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Journal of Sensors
Volume 2015 (2015), Article ID 236474, 13 pages
Research Article

Quantitative Assessment of ADL: A Pilot Study of Upper Extremity Reaching Tasks

1School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia
2Department of Medicine, Royal Melbourne Hospital, Parkville, VIC 3052, Australia
3School of Nursing and Midwifery, Deakin University, Burwood, VIC 3125, Australia
4Royal Melbourne Hospital, Parkville, VIC 3052, Australia

Received 1 March 2015; Accepted 26 May 2015

Academic Editor: Fanli Meng

Copyright © 2015 Saiyi Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Effective telerehabilitation technologies enable patients with certain physiological disabilities to engage in rehabilitative exercises for performing Activities of Daily Living (ADLs). Therefore, training and assessment scenarios for the performance of ADLs are vital for the promotion for telerehabilitation. In this paper we investigate quantitatively and automatically assessing patient’s kinematic ability to perform functional upper extremity reaching tasks. The shape of the movement trajectory and the instantaneous acceleration of kinematically crucial body parts, such as wrists, are used to compute the approximate entropy of the motions to represent stability (smoothness) in addition to the duration of the activity. Computer simulations were conducted to illustrate the consistency, sensitivity and robustness of the proposed method. A preliminary experiment with kinematic data captured from healthy subjects mimicking a reaching task with dyskinesia showed a high degree of correlation (Cohen’s kappa 0.85 with ) between a human observer and the proposed automatic classification tool in terms of assigning the datasets to various levels to represent the subjects’ kinematic abilities to perform reaching tasks. This study supported the use of Microsoft Kinect to quantitatively evaluate the ability of individuals with involuntary movements to perform an upper extremity reaching task.