Openly accessible

A comprehensive scheme for the objective upper body assessments of subjects with cerebellar ataxia

Tran, Ha, Nguyen, Khoa Dinh, Pathirana, Pubudu N, Horne, Malcolm K, Power, Laura and Szmulewicz, David J 2020, A comprehensive scheme for the objective upper body assessments of subjects with cerebellar ataxia, Journal of neuroengineering and rehabilitation, vol. 17, no. 1, pp. 1-15, doi: 10.1186/s12984-020-00790-3.

Attached Files
Name Description MIMEType Size Downloads

Title A comprehensive scheme for the objective upper body assessments of subjects with cerebellar ataxia
Author(s) Tran, Ha
Nguyen, Khoa DinhORCID iD for Nguyen, Khoa Dinh orcid.org/0000-0002-9122-0599
Pathirana, Pubudu NORCID iD for Pathirana, Pubudu N orcid.org/0000-0001-8014-7798
Horne, Malcolm K
Power, Laura
Szmulewicz, David J
Journal name Journal of neuroengineering and rehabilitation
Volume number 17
Issue number 1
Article ID 162
Start page 1
End page 15
Total pages 15
Publisher BioMed Central
Place of publication London, Eng.
Publication date 2020
ISSN 1743-0003
1743-0003
Keyword(s) Science & Technology
Technology
Life Sciences & Biomedicine
Engineering, Biomedical
Neurosciences
Rehabilitation
Engineering
Neurosciences & Neurology
Cerebellar ataxia
Finger chase
Finger tapping
Finger to nose
Dysdiadochokinesia
Objective assessment
Feed backward feature elimination
Summary Background Cerebellar ataxia refers to the disturbance in movement resulting from cerebellar dysfunction. It manifests as inaccurate movements with delayed onset and overshoot, especially when movements are repetitive or rhythmic. Identification of ataxia is integral to the diagnosis and assessment of severity, and is important in monitoring progression and improvement. Ataxia is identified and assessed by clinicians observing subjects perform standardised movement tasks that emphasise ataxic movements. Our aim in this paper was to use data recorded from motion sensors worn while subjects performed these tasks, in order to make an objective assessment of ataxia that accurately modelled the clinical assessment. Methods Inertial measurement units and a Kinect© system were used to record motion data while control and ataxic subjects performed four instrumented version of upper extremities tests, i.e. finger chase test (FCT), finger tapping test (FTT), finger to nose test (FNT) and dysdiadochokinesia test (DDKT). Kinematic features were extracted from this data and correlated with clinical ratings of severity of ataxia using the Scale for the Assessment and Rating of Ataxia (SARA). These features were refined using Feed Backward feature Elimination (the best performing method of four). Using several different learning models, including Linear Discrimination, Quadratic Discrimination Analysis, Support Vector Machine and K-Nearest Neighbour these extracted features were used to accurately discriminate between ataxics and control subjects. Leave-One-Out cross validation estimated the generalised performance of the diagnostic model as well as the severity predicting regression model. Results The selected model accurately (96.4%) predicted the clinical scores for ataxia and correlated well with clinical scores of the severity of ataxia (rho = 0.8, p < 0.001). The severity estimation was also considered in a 4-level scale to provide a rating that is familiar to the current clinically-used rating of upper limb impairments. The combination of FCT and FTT performed as well as all four test combined in predicting the presence and severity of ataxia. Conclusion Individual bedside tests can be emulated using features derived from sensors worn while bedside tests of cerebellar ataxia were being performed. Each test emphasises different aspects of stability, timing, accuracy and rhythmicity of movements. Using the current models it is possible to model the clinician in identifying ataxia and assessing severity but also to identify those test which provide the optimum set of data. Trial registration Human Research and Ethics Committee, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia (HREC Reference Number: 11/994H/16).
Language eng
DOI 10.1186/s12984-020-00790-3
Indigenous content off
Field of Research 0903 Biomedical Engineering
1109 Neurosciences
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30146442

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

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.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 17 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Wed, 06 Jan 2021, 09:32:34 EST

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.