Yantao Xing, Yang Yang, Kaiyuan Yang, Albert Lu, Luyi Xing, Ken Mackie, Feng Guo
{"title":"Intelligent sensing devices and systems for personalized mental health.","authors":"Yantao Xing, Yang Yang, Kaiyuan Yang, Albert Lu, Luyi Xing, Ken Mackie, Feng Guo","doi":"10.1007/s44258-025-00057-3","DOIUrl":null,"url":null,"abstract":"<p><p>Mental disorders disturb the cognition, emotion, and behavior of a diverse patient population, and can reduce their quality of life and even cause death. Despite significant advances in the diagnosis and treatment of mental disorders, challenges remain in achieving objective understanding, accurate assessment, and timely intervention for personalized conditions. Here, we review the recent development of intelligent sensing devices and systems for advancing the diagnosing, monitoring, and managing of mental disorders, with a special emphasis on personalized mental healthcare. We first introduce the mechanisms and clinical symptoms of mental disorders and related diagnostic principles. Then, we discuss the working principle and application of wearable sensors and systems to track various physiological parameters and markers for long-term monitoring, early screening, and treatment evaluation. Furthermore, we highlight recent emerging advancements in Artificial Intelligence (AI) and digital health and give perspectives on their integration with sensing technologies to address the emergent challenges of personalized mental healthcare. We believe innovative intelligent sensing technologies may significantly improve the patient's quality of life, enhance the efficiency and robustness of current healthcare systems, and reduce the socioeconomic burden for mental disorders and other diseases.</p>","PeriodicalId":74169,"journal":{"name":"Med-X","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12363438/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Med-X","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s44258-025-00057-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/2 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Mental disorders disturb the cognition, emotion, and behavior of a diverse patient population, and can reduce their quality of life and even cause death. Despite significant advances in the diagnosis and treatment of mental disorders, challenges remain in achieving objective understanding, accurate assessment, and timely intervention for personalized conditions. Here, we review the recent development of intelligent sensing devices and systems for advancing the diagnosing, monitoring, and managing of mental disorders, with a special emphasis on personalized mental healthcare. We first introduce the mechanisms and clinical symptoms of mental disorders and related diagnostic principles. Then, we discuss the working principle and application of wearable sensors and systems to track various physiological parameters and markers for long-term monitoring, early screening, and treatment evaluation. Furthermore, we highlight recent emerging advancements in Artificial Intelligence (AI) and digital health and give perspectives on their integration with sensing technologies to address the emergent challenges of personalized mental healthcare. We believe innovative intelligent sensing technologies may significantly improve the patient's quality of life, enhance the efficiency and robustness of current healthcare systems, and reduce the socioeconomic burden for mental disorders and other diseases.