Quantification of Motor Function in Huntington Disease Patients Using Wearable Sensor Devices
| Autor: | Igor D. Grachev, Pippa S. Loupe, Spyros Papapetropoulos, Leehee Navon-Perry, Juha-Matti Savola, Shai Fine, Michael R. Hayden, Itzik Mazeh, Ralf Reilmann, Nicholas Gross, Mark Forrest Gordon, Yonatan Dolan |
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| Rok vydání: | 2019 |
| Předmět: |
congenital
hereditary and neonatal diseases and abnormalities medicine.medical_specialty Movement disorders Essential tremor business.industry Medicine (miscellaneous) Wearable computer Health Informatics Chorea medicine.disease Digital health nervous system diseases Computer Science Applications Research Reports - Research Article Smartwatch Physical medicine and rehabilitation Sample size determination mental disorders medicine Generalizability theory medicine.symptom business |
| Zdroj: | Digital Biomarkers. 3:103-115 |
| ISSN: | 2504-110X |
| DOI: | 10.1159/000502136 |
| Popis: | Previous studies have demonstrated the feasibility and promise of wearable sensors as objective measures of motor impairment in Parkinson disease and essential tremor. However, there are few published studies that have examined such an application in Huntington disease (HD). This report provides an evaluation of the potential to objectively quantify chorea in HD patients using wearable sensor data. Data were derived from a substudy of the phase 2 Open-PRIDE-HD study, where 17 patients were screened and 15 patients enrolled in the substudy and ultimately 10 patients provided sufficient wearable sensor data. The substudy was designed to provide high-resolution data to inform design of predictive algorithms for chorea quantification. During the entire course of the 6-month study, in addition to chorea ratings from 18 in-clinic assessments, 890 home assessments, and 1,388 responses to daily reminders, 33,000 h of high-resolution accelerometer data were captured continuously from wearable smartwatches and smartphones. Despite its limited sample size, our study demonstrates that arm chorea can be characterized using accelerometer data during static assessments. Nonetheless, the small sample size limits the generalizability of the model. The sensor-based model can quantify the chorea level with high correlation to the chorea severity reported by both clinicians and patients. In addition, our analysis shows that the chorea digital signature varies between patients. This work suggests that digital wearable sensors have the potential to support clinical development of medications in patients with movement disorders, such as chorea. However, additional data would be needed from a larger number of HD patients with a full range of chorea severity (none to severe) with and without intervention to validate this potentially predictive technology. |
| Databáze: | OpenAIRE |
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