![]() The objective measurements can provide more consistent evaluations and are crucial when specialists are unavailable. This evaluation and scoring system is prone to bias and inaccurate assessment owing to its subjective evaluation, and it is potentially compounded if the same clinician does not consistently evaluate the patient. For instance, the SARA stipulates the overshoot or undershoot distance between the patient’s finger and the clinician’s finger in the FCT. However, these scales must be administered by a neurologist with particular expertise in ataxia and are subjective. In addition to the SARA, other assessment scales, including the Brief Ataxia Rating Scale (BARS) and the International Cooperative Ataxia Rating Scale, can effectively determine specific aspects of disease severity. Among current methods to assess SCA, the Scale for the Assessment and Rating of Ataxia (SARA) is widely used and includes the finger chasing test (FCT), finger-to-nose test (FNT), and alternating hand movement assessment for dysdiadochokinesia (DDKT). Over time, several motor tasks were designed and standardized to evaluate these motor disturbances in terms of accuracy, timing, rhythmicity, and stability, and corresponding impairments were termed dysmetria, dyssynergia, and dysrhythmia. SCA-related motor dysfunction often manifests as abnormal limb coordination, speech difficulties, oculomotor abnormalities, and gait disorder, with impaired postural control during walking or standing. Spinocerebellar ataxia (SCA) is characterized by motor dysfunction caused by degenerative changes in the cerebellum. The proposed wearable-based platform has the potential to eliminate subjectivity and inter-rater variabilities in assessing ataxia. Our findings pave the way to enhance the utility of objective measures of SCA assessments. 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. 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. The proposed technique was validated on a dataset comprising the seventeen ( n = 17) participants’ assessments. Additionally, we developed models to predict the severity of symptoms based on the FNT. We extracted multiple features from the detected cycles and identified features and parameters correlated with the SARA scores. First, we developed an algorithm for detecting/extracting the cycles of the finger-to-nose test (FNT). 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). ![]()
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