Guo Tian, Li Guo, Yuyu Gao, Weili Deng, Shenglong Wang, Tianpei Xu, Lu Peng, Binbin Zhang, Tao Yang, Boling Lan, Yue Sun, Yong Ao, Longchao Huang, Yang Liu, Xuelan Li, Long Jin, Weiqing Yang, Xinge Yu
{"title":"A wearable all-in-one obstructive sleep apnea management system with flexible piezoelectric monitoring and soft magnetoelastic stimulating","authors":"Guo Tian, Li Guo, Yuyu Gao, Weili Deng, Shenglong Wang, Tianpei Xu, Lu Peng, Binbin Zhang, Tao Yang, Boling Lan, Yue Sun, Yong Ao, Longchao Huang, Yang Liu, Xuelan Li, Long Jin, Weiqing Yang, Xinge Yu","doi":"10.1016/j.matt.2025.102323","DOIUrl":null,"url":null,"abstract":"Obstructive sleep apnea (OSA), a widespread disorder afflicting hundreds of millions worldwide, requires real-time monitoring and intervention solutions. Although polysomnography (PSG) is the gold standard for diagnosing apnea, its clinical limitations necessitate the development of portable sleep management electronics. In response, we develop a wearable sensing-stimulative apnea management system (AMS) featuring a customized piezoelectric composite sensor for continuous monitoring of physiological signals and a soft magnetoelastic actuator delivering non-invasive mechanical stimulation. A machine learning algorithm is leveraged to analyze the collected data, enabling real-time apnea detection accuracy of 92.7%. Rigorous laboratory and clinical studies on patients demonstrate that the developed AMS is on par with the clinical gold standard, PSG, in identifying apnea events. The parallel comparison signals from AMS and PSG also confirm the efficacy of feedback stimulation. This research pioneers a closed-loop sensing-stimulative system for OSA management, creating a promising paradigm in personalized sleep care.","PeriodicalId":388,"journal":{"name":"Matter","volume":"68 1","pages":""},"PeriodicalIF":17.3000,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Matter","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1016/j.matt.2025.102323","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Obstructive sleep apnea (OSA), a widespread disorder afflicting hundreds of millions worldwide, requires real-time monitoring and intervention solutions. Although polysomnography (PSG) is the gold standard for diagnosing apnea, its clinical limitations necessitate the development of portable sleep management electronics. In response, we develop a wearable sensing-stimulative apnea management system (AMS) featuring a customized piezoelectric composite sensor for continuous monitoring of physiological signals and a soft magnetoelastic actuator delivering non-invasive mechanical stimulation. A machine learning algorithm is leveraged to analyze the collected data, enabling real-time apnea detection accuracy of 92.7%. Rigorous laboratory and clinical studies on patients demonstrate that the developed AMS is on par with the clinical gold standard, PSG, in identifying apnea events. The parallel comparison signals from AMS and PSG also confirm the efficacy of feedback stimulation. This research pioneers a closed-loop sensing-stimulative system for OSA management, creating a promising paradigm in personalized sleep care.
期刊介绍:
Matter, a monthly journal affiliated with Cell, spans the broad field of materials science from nano to macro levels,covering fundamentals to applications. Embracing groundbreaking technologies,it includes full-length research articles,reviews, perspectives,previews, opinions, personnel stories, and general editorial content.
Matter aims to be the primary resource for researchers in academia and industry, inspiring the next generation of materials scientists.