萧条(经济学)
可穿戴计算机
躯体化
可穿戴技术
医学
风险分析(工程)
计算机科学
精神科
心理健康
嵌入式系统
经济
宏观经济学
作者
Jiaju Yin,Xinyuan Jia,Haorong Li,Bingchen Zhao,Yi Yang,Tian‐Ling Ren
出处
期刊:Biosensors
[Multidisciplinary Digital Publishing Institute]
日期:2024-08-30
卷期号:14 (9): 422-422
被引量:1
摘要
Depression is currently a major contributor to unnatural deaths and the healthcare burden globally, and a patient's battle with depression is often a long one. Because the causes, symptoms, and effects of medications are complex and highly individualized, early identification and personalized treatment of depression are key to improving treatment outcomes. The development of wearable electronics, machine learning, and other technologies in recent years has provided more possibilities for the realization of this goal. Conducting regular monitoring through biosensing technology allows for a more comprehensive and objective analysis than previous self-evaluations. This includes identifying depressive episodes, distinguishing somatization symptoms, analyzing etiology, and evaluating the effectiveness of treatment programs. This review summarizes recent research on biosensing technologies for depression. Special attention is given to technologies that can be portable or wearable, with the potential to enable patient use outside of the hospital, for long periods.
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