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Quantitative assessment of ADL: a pilot study of upper extremity reaching tasks

Li, Saiyi, Pathirana, Pubudu N., Galea, Mary P., Ottmann, Goetz and Khan, Fary 2015, Quantitative assessment of ADL: a pilot study of upper extremity reaching tasks, Journal of sensors, vol. 2015, Article Number : 236474, pp. 1-13, doi: 10.1155/2015/236474.

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Title Quantitative assessment of ADL: a pilot study of upper extremity reaching tasks
Author(s) Li, Saiyi
Pathirana, Pubudu N.
Galea, Mary P.
Ottmann, Goetz
Khan, Fary
Journal name Journal of sensors
Volume number 2015
Season Article Number : 236474
Start page 1
End page 13
Total pages 13
Publisher Hindawi Publishing Corporation
Place of publication New York , N.Y.
Publication date 2015
ISSN 1687-725X
1687-7268
Keyword(s) Science & Technology
Technology
Engineering, Electrical & Electronic
Instruments & Instrumentation
Engineering
PARKINSONS-DISEASE
RATING-SCALE
TARDIVE-DYSKINESIA
MOVEMENT SMOOTHNESS
STROKE
QUESTIONNAIRE
RELIABILITY
RECOVERY
VALIDITY
SYSTEM
Summary 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 p < 0.05) 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.
Language eng
DOI 10.1155/2015/236474
Field of Research 119999 Medical and Health Sciences not elsewhere classified
Socio Economic Objective 929999 Health not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30074895

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.