Objective Assessment of Upper-Extremity Motor Functions in Spinocerebellar Ataxia Using Wearable Sensors
Name
sensors-22-07993.pdf
Size
1.09 MB
Format
Adobe PDF
Checksum (MD5)
264ef643d04d49be0131eed805e439f0
Author(s)
Mohammadi-Ghazi, Reza
Nguyen, Hung
Mishra, Ram Kinker
Enriquez, Ana
Najafi, Bijan
Stephen, Christopher D.
Gupta, Anoopum S.
Schmahmann, Jeremy D.
Vaziri, Ashkan
Date Issued
October 20, 2022
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Sensors 22 (20): 7993 (2022)
Version
Final published version
Abstract
The study presents a novel approach to objectively assessing the upper-extremity motor symptoms in spinocerebellar ataxia (SCA) using data collected via a wearable sensor worn on the patient’s wrist during upper-extremity tasks associated with the Assessment and Rating of Ataxia (SARA). First, we developed an algorithm for detecting/extracting the cycles of the finger-to-nose test (FNT). We extracted multiple features from the detected cycles and identified features and parameters correlated with the SARA scores. Additionally, we developed models to predict the severity of symptoms based on the FNT. The proposed technique was validated on a dataset comprising the seventeen (n = 17) participants’ assessments. The cycle detection technique showed an accuracy of 97.6% in a Bland–Altman analysis and a 94% accuracy (F1-score of 0.93) in predicting the severity of the FNT. Furthermore, the dependency of the upper-extremity tests was investigated through statistical analysis, and the results confirm dependency and potential redundancies in the upper-extremity SARA assessments. Our findings pave the way to enhance the utility of objective measures of SCA assessments. The proposed wearable-based platform has the potential to eliminate subjectivity and inter-rater variabilities in assessing ataxia.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. Laboratory for Infrastructure Science and Sustainability
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/s22207993
