Assessment of gait and balance in people with spinocerebellar ataxia using wearable sensors


Topic:

Other

Poster Number: 94

Author(s):

He Zhou, PhD, BioSensics, Ana Enriquez, BS, BioSensics, Michael Curtis, PhD, Cadent Therapeutics, Timothy Piser, PhD, Cadent Therapeutics, Christopher Kenny, MD, Cadent Therapeutics, Christopher D. Stephen, MBChB, Ataxia Center, Department of Neurology, Massachusetts General Hospital, Anoopum Gupta, MD, PhD, Ataxia Center, Department of Neurology, Massachusetts General Hospital, Jeremy Schmahmann, MD, Ataxia Center, Department of Neurology, Massachusetts General Hospital, Ashkan Vaziri, PhD, BioSensics LLC

"Background: Spinocerebellar ataxias (SCA) are neurodegenerative disorders resulting from degeneration of the cerebellum. Ataxia rating scales are the preferred method to use in clinical trials. Although they have high inter-rater reliability, they are inherently subjective and may not be sufficiently sensitive to incremental but clinically meaningful changes. There are growing efforts to use wearable sensor to develop digital biomarkers that are more sensitive to detect changes in motor dysfunction in SCA. Assessment tools, based on wearable sensor, can help expedite the development of novel therapies through quick and objective measurement of ataxia endpoints that are clinically meaningful.
Objectives: To explore the use of wearable sensors for objective assessment of motor impairment in SCA patient during clinical assessments of gait and balance.
Methods: 14 patients (age=61.6 ± 8.6 years old) with a genetically-confirmed diagnoses of SCA and 4 healthy controls (age=49.0 ± 16.4) were recruited through the MGH Neurological Clinical Research Institute. Participant donned 7 inertial sensors while performing two trials of the gait and balance assessment from the SARA and BARS2. Multivariate analysis of covariance was used to identify features of motor function that discriminate between control and SCA group. Multivariate linear regression model was used to estimate the subjective in-person rating of the SARA and BARS2. Spearman’s correlation coefficient was used to evaluate the performance of the model.
Results: Results showed that that stride length variability, stride duration, cadence, stance phase, pelvis sway, and turn duration were significantly different between SCA and controls (p<0.050). Similarly sway and sway velocity of the ankle, hip, and center of mass show significant difference between control and SCA group (p<0.05). Using these features, linear regression model showed strong correlation to the gait score given by the in-person rater during gait (r=0.919,p<0.001) and balance (r=0.872, p<0.001) assessment of the SARA and gait assessment of the BARS2 (r=0.931, p<0.001).
Conclusion: This study confirms that gait and balance performance measured by wearable sensors were different in patients with SCA and controls. Furthermore, the model developed shows the capability of using sensor to automatically rate the severity of SCA using sensor. This could potentially be used to improve patient care and conduct of clinical trial in ataxia. "