Publication Date
10-20-2022
Journal
Sensors
DOI
10.3390/s22207993
PMID
36298343
PMCID
PMC9609238
PubMedCentral® Posted Date
10-20-2022
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Keywords
Humans, Spinocerebellar Ataxias, Cerebellar Ataxia, Ataxia, Upper Extremity, Wearable Electronic Devices, movement disorder, telemedicine, care in place, remote patient monitoring, digital biomarker, scale for the assessment and rating of ataxia, dysdiadochokinesia
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.