Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia

• Published in: Cerebellum (London, England) Vol. 21; no. 3; pp. 368 - 379
• Main Authors: Khan, Nergis C., Pandey, Vineet, Gajos, Krzysztof Z., Gupta, Anoopum S.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2022; Springer Nature B.V
• Subjects: Ataxia; Biomarkers; Biomedical and Life Sciences; Biomedicine; Children; Gait; Motor activity; Motor task performance; Neurobiology; Neurological diseases; Neurology; Neurosciences; Original; Original Article; Sensors; Wrist; Biomarkers; Wearable devices; Ataxia-telangiectasia
• ISSN: 1473-4230; 1473-4222; 1473-4230
• DOI: 10.1007/s12311-021-01306-y

With disease-modifying approaches under evaluation in ataxia-telangiectasia and other ataxias, there is a need for objective and reliable biomarkers of free-living motor function. In this study, we test the hypothesis that metrics derived from a single wrist sensor worn at home provide accurate, reliable, and interpretable information about neurological disease severity in children with A-T. A total of 15 children with A-T and 15 age- and sex-matched controls wore a sensor with a triaxial accelerometer on their dominant wrist for 1 week at home. Activity intensity measures, derived from the sensor data, were compared with in-person neurological evaluation on the Brief Ataxia Rating Scale (BARS) and performance on a validated computer mouse task. Children with A-T were inactive the same proportion of each day as controls but produced more low intensity movements ( p  < 0.01; Cohen’s d  = 1.48) and fewer high intensity movements ( p  < 0.001; Cohen’s d  = 1.71). The range of activity intensities was markedly reduced in A-T compared to controls ( p  < 0.0001; Cohen’s d  = 2.72). The activity metrics correlated strongly with arm, gait, and total clinical severity ( r : 0.71–0.87; p  < 0.0001), correlated with specific computer task motor features ( r : 0.67–0.92; p  < 0.01), demonstrated high reliability ( r : 0.86–0.93; p  < 0.00001), and were not significantly influenced by age in the healthy control group. Motor activity metrics from a single, inexpensive wrist sensor during free-living behavior provide accurate and reliable information about diagnosis, neurological disease severity, and motor performance. These low-burden measurements are applicable independent of ambulatory status and are potential digital behavioral biomarkers in A-T.