使用可穿戴传感器在长时间连续监测中识别精神病患者和对照组之间的身体活动和自主神经功能模式的差异
Identifying differences in physical activity and autonomic function patterns between psychotic patients and controls over a long period of continuous monitoring using wearable sensors
摘要：
数字表型是一个新兴的多学科领域，有可能彻底改变精神病学及其临床实践。在本文中，我们提出了一个严格的统计分析，从可穿戴数据中提取的短期功能，在长期连续监测精神障碍患者和健康对照同行。我们的新分析确定了两组之间显著波动的特征，并提供了对区分它们的几个因素的见解，这些因素可以在未来用于预防复发和个性化援助。
英文摘要：
Digital phenotyping is a nascent multidisciplinary field that has the potential to revolutionize psychiatry and its clinical practice. In this paper, we present a rigorous statistical analysis of short-time features extracted from wearable data, during long-term continuous monitoring of patients with psychotic disorders and healthy control counterparts. Our novel analysis identifies features that fluctuate significantly between the two groups, and offers insights on several factors that differentiate them, which could be leveraged in the future for relapse prevention and individualized assistance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
