He Yangliuqing, Liang Fenrong, Wang Yiming, Wei Yuhan, Ma Tianpei
Clinical Medicine College of Guizhou Medical University, Guiyang, 550000.
Department of Psychiatry, the Affiliated Hospital of Guizhou Medical University, Guiyang, 550000.
Zhongguo Yi Liao Qi Xie Za Zhi. 2024 Jul 30;48(4):407-412. doi: 10.12455/j.issn.1671-7104.230630.
Depression's high recurrence rate and severe consequences pose significant challenges to public health. To address this issue effectively, this review explores the innovative application of wearable devices in monitoring and intervening in depression, surpassing the limitations of traditional subjective assessments and patient self-reports. The paper systematically analyzes recent studies utilizing wearable devices to monitor physiological and behavioral indicators of depression, categorizing them by different technological types and evaluating their practical effectiveness in early diagnosis and intervention. The findings indicate that wearable devices can continuously monitor physiological indicators and behavioral patterns related to depression, potentially enabling early detection of depressive episodes and supporting timely interventions. Despite challenges such as data privacy and user acceptance, wearable technology holds immense potential in enhancing clinical outcomes in depression treatment.
抑郁症的高复发率和严重后果给公共卫生带来了重大挑战。为有效解决这一问题，本综述探讨了可穿戴设备在抑郁症监测和干预中的创新应用，突破了传统主观评估和患者自我报告的局限性。本文系统分析了利用可穿戴设备监测抑郁症生理和行为指标的近期研究，按不同技术类型对其进行分类，并评估其在早期诊断和干预中的实际效果。研究结果表明，可穿戴设备能够持续监测与抑郁症相关的生理指标和行为模式，有可能实现对抑郁发作的早期检测并支持及时干预。尽管存在数据隐私和用户接受度等挑战，但可穿戴技术在改善抑郁症治疗临床结果方面具有巨大潜力。
