dc.contributor.author | Mohammadi-Ghazi, Reza | |
dc.contributor.author | Nguyen, Hung | |
dc.contributor.author | Mishra, Ram Kinker | |
dc.contributor.author | Enriquez, Ana | |
dc.contributor.author | Najafi, Bijan | |
dc.contributor.author | Stephen, Christopher D. | |
dc.contributor.author | Gupta, Anoopum S. | |
dc.contributor.author | Schmahmann, Jeremy D. | |
dc.contributor.author | Vaziri, Ashkan | |
dc.date.accessioned | 2022-10-26T17:35:26Z | |
dc.date.available | 2022-10-26T17:35:26Z | |
dc.date.issued | 2022-10-20 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/145995 | |
dc.description.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 (<i>n</i> = 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. | en_US |
dc.publisher | Multidisciplinary Digital Publishing Institute | en_US |
dc.relation.isversionof | http://dx.doi.org/10.3390/s22207993 | en_US |
dc.rights | Creative Commons Attribution | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
dc.source | Multidisciplinary Digital Publishing Institute | en_US |
dc.title | Objective Assessment of Upper-Extremity Motor Functions in Spinocerebellar Ataxia Using Wearable Sensors | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Sensors 22 (20): 7993 (2022) | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. Laboratory for Infrastructure Science and Sustainability | |
dc.identifier.mitlicense | PUBLISHER_CC | |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2022-10-26T11:07:58Z | |
dspace.date.submission | 2022-10-26T11:07:58Z | |
mit.license | PUBLISHER_CC | |
mit.metadata.status | Authority Work and Publication Information Needed | en_US |