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Quantification of Motor Function in Huntington Disease Patients Using Wearable Sensor Devices

机译:使用可穿戴传感器设备量化亨廷顿病患者的运动功能

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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.
机译:先前的研究表明可穿戴式传感器作为帕金森氏病和原发性震颤运动障碍的客观指标的可行性和前景。但是,很少有已发表的研究对亨廷顿病(HD)的这种应用进行了研究。该报告评估了使用可穿戴传感器数据客观量化HD患者的舞蹈病的潜力。数据来自2期Open-PRIDE-HD研究的子研究,其中筛选了17位患者,有15位患者参加了该子研究,最终10位患者提供了足够的可穿戴传感器数据。该子研究旨在提供高分辨率数据,以指导舞蹈病量化的预测算法的设计。在为期6个月的研究的整个过程中,除了来自18项诊所评估的chorea评分,890项家庭评估以及对每日提醒的1,388条响应之外,还从可穿戴智能手表和智能手机中连续捕获了33,000小时的高分辨率加速度计数据。尽管样本量有限,但我们的研究表明,可以在静态评估过程中使用加速度计数据来表征手臂舞蹈症。但是,样本量小限制了模型的通用性。基于传感器的模型可以量化与与临床医生和患者报告的舞蹈病严重程度高度相关的舞蹈病水平。此外,我们的分析表明,患者之间的舞蹈病数字签名有所不同。这项工作表明,数字可穿戴传感器具有支持运动障碍(例如舞蹈病)患者临床开发药物的潜力。但是,在有或没有干预的情况下,需要大量的全范围舞蹈病严重程度(无至严重)的HD患者,需要额外的数据来验证这种潜在的预测技术。

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