Article(id=1321967890316768199, tenantId=1146029695717560320, journalId=1220038251117760515, issueId=1321967818057298402, articleNumber=null, orderNo=null, doi=10.11868/j.issn.1001-4381.2025.000686, pmid=null, cstr=32421.14.j.issn.1001-4381.2025.000686, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1764086400000, receivedDateStr=2025-11-26, revisedDate=null, revisedDateStr=null, acceptedDate=1769529600000, acceptedDateStr=2026-01-28, onlineDate=1793111306027, onlineDateStr=2026-10-27, pubDate=1781884800000, pubDateStr=2026-06-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793111306027, onlineIssueDateStr=2026-10-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793111306027, creator=13701087609, updateTime=1793111306027, updator=13701087609, issue=Issue{id=1321967818057298402, tenantId=1146029695717560320, journalId=1220038251117760515, year='2026', volume='54', issue='6', pageStart='1', pageEnd='248', issueExtLink='null', onlineDate='null', pubDate='1781884800000', pubDateStr='2026-06-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793111288799, creator='13701087609', updateTime=1793111414358, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321968344765411750, tenantId=1146029695717560320, journalId=1220038251117760515, issueId=1321967818057298402, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321968344765411751, tenantId=1146029695717560320, journalId=1220038251117760515, issueId=1321967818057298402, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=13, endPage=24, ext={EN=ArticleExt(id=1321967890530677704, articleId=1321967890316768199, tenantId=1146029695717560320, journalId=1220038251117760515, language=EN, title=Application and research progress in flexible wearable intelligent materials for 24 h physical behavior monitoring, columnId=1321967818942296547, journalTitle=Journal of Materials Engineering, columnName=INTELLIGENT MATERIALS FOR FLEXIBLE AND WEARABLE DEVICES COLUMN, runingTitle=null, highlight=null, articleAbstract=

Modern lifestyles are associated with significant public health concerns, including sedentary behavior and sleep disorders. Flexible wearable intelligent materials, characterized by excellent biocompatibility and continuous signal acquisition capabilities, are becoming a pivotal technology for the precise 24 h monitoring of physical behaviors (e.g., activity, sedentariness, and sleep). This review aims to dissect the current research landscape in this field, from theoretical foundations to engineering applications. It first explores the use of flexible electronic interfaces in physical activity monitoring, highlighting how material innovations have enabled the expansion from macroscopic biomechanical sensing to microscopic metabolite tracking. The role of these materials in identifying sedentary behaviors is then analyzed, focusing on high-sensitivity designs for capturing postural transitions and assessing physiological load. For sleep health, the discussion centers on unobtrusive material systems for long-term monitoring of respiratory and sleep rhythms. Furthermore, to support the extended operation of such wearable devices, this review synthesizes advanced self-powering and energy storage solutions, such as triboelectric nanogenerators, photovoltaics, and biofuel cells. Persistent challenges are identified, including the lack of standardized validation, limited battery life, and insufficient understanding of the complex correlations between behavior and physiology. Future progress is expected to depend on the convergence of material innovation, multimodal sensor fusion, optimized artificial intelligence algorithms, and large-scale clinical trials, ultimately contributing to a comprehensive smart health management ecosystem.

, authors=Jia GUO1, Jiakai TANG1, Shaoqing HOU1, Dong ZHANG2, Chunmei CAO1, authorsList=Jia GUO, Jiakai TANG, Shaoqing HOU, Dong ZHANG, Chunmei CAO, authorCompany=null, correspAuthors=Chunmei CAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321967891436647375, articleId=1321967890316768199, tenantId=1146029695717560320, journalId=1220038251117760515, language=CN, title=面向24 h身体行为监测应用的柔性可穿戴智能材料应用研究进展, columnId=1321967819202343397, journalTitle=材料工程, columnName=面向柔性可穿戴器件的智能材料专栏, runingTitle=null, highlight=null, articleAbstract=

现代生活方式带来了久坐、睡眠障碍等公众健康问题,柔性可穿戴智能材料凭借其较好的生物相容性与信号采集连续性,成为24 h身体行为(体力活动、久坐行为、睡眠)精准监测的核心技术支柱。本文旨在剖析该领域从基础理论到工程应用的研究现状,探讨了柔性电子界面在体力活动监测中的应用,阐述了传感器的材料创新实现从宏观生物力学感知到微观代谢产物追踪的演变;进一步分析了柔性电子材料在识别久坐行为中的作用,重点介绍了如何利用高灵敏度材料捕捉人体的姿势变化及评估生理负荷;在睡眠健康领域,则聚焦于无感化材料对睡眠呼吸与节律的监测。此外,还梳理了支撑设备长效续航的自供能及高效储能技术,如摩擦电、光伏及生物燃料电池等前沿方案。同时指出当前该领域仍面临标准化验证缺失、设备续航不足、行为与生理深层关系模糊等挑战。未来需通过材料创新、多模态传感融合、人工智能算法优化及大规模临床验证,以期构建全生命周期的智能化健康管理生态。

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曹春梅(1977—),女,副教授,博士,研究方向:运动生物力学、运动训练与机能监控,联系地址:北京市海淀区清华大学北体育馆(100084),E-mail:
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detection[J].Talanta,2022,241:123187., articleTitle=Wearable hydrogel patch with noninvasive,electrochemical glucose sensor for natural sweat detection, refAbstract=null), Reference(id=1321967907567939662, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, doi=null, pmid=null, pmcid=null, year=2018, volume=1, issue=null, pageStart=2, pageEnd=null, url=null, language=null, rfNumber=[75], rfOrder=76, authorNames=LEE S P, HA G, WRIGHT D E, journalName=npj Digital Medicine, refType=null, unstructuredReference=LEE S P,HA G, WRIGHT D E,et al.Highly flexible,wearable,and disposable cardiac biosensors for remote and ambulatory monitoring[J].npj Digital Medicine,2018,1:2., articleTitle=Highly flexible,wearable,and disposable cardiac biosensors for remote and ambulatory monitoring, refAbstract=null), Reference(id=1321967907647631439, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, doi=null, pmid=null, pmcid=null, year=2016, volume=10, issue=8, pageStart=8097, pageEnd=8103, url=null, language=null, rfNumber=[76], rfOrder=77, authorNames=SONG W X, GAN B H, JIANG T, journalName=ACS Nano, refType=null, unstructuredReference=SONG W X, GAN B H, JIANG T,et al.Nanopillar arrayed triboelectric nanogenerator as a self-powered sensitive sensor for a sleep monitoring system[J].ACS Nano,2016,10(8):8097-8103., articleTitle=Nanopillar arrayed triboelectric nanogenerator as a self-powered sensitive sensor for a sleep monitoring system, refAbstract=null), Reference(id=1321967907714740304, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, doi=null, pmid=null, pmcid=null, year=2025, volume=31, issue=10, pageStart=3394, pageEnd=3403, url=null, language=null, rfNumber=[77], rfOrder=78, authorNames=KHASENTINO J, BELYAEVA A, LIU X, journalName=Nature Medicine, refType=null, unstructuredReference=KHASENTINO J, BELYAEVA A, LIU X,et al.A personal health large language model for sleep and fitness coaching[J].Nature Medicine,2025,31(10):3394-3403., articleTitle=A personal health large language model for sleep and fitness coaching, refAbstract=null), Reference(id=1321967907794432081, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, doi=null, pmid=null, pmcid=null, year=2020, volume=12, issue=19, pageStart=22212, pageEnd=22224, url=null, language=null, rfNumber=[78], rfOrder=79, authorNames=SHARMA S, CHHETRY A, SHARIFUZZAMAN M, journalName=ACS Applied Materials & Interfaces, refType=null, unstructuredReference=SHARMA S, CHHETRY A, SHARIFUZZAMAN M,et al.Wearable capacitive pressure sensor based on MXene composite nanofibrous scaffolds for reliable human physiological signal acquisition[J].ACS Applied Materials & Interfaces,2020,12(19):22212-22224., articleTitle=Wearable capacitive pressure sensor based on MXene composite nanofibrous scaffolds for reliable human physiological signal acquisition, refAbstract=null), Reference(id=1321967907861540946, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, doi=null, pmid=null, pmcid=null, year=2020, volume=14, issue=10, pageStart=14126, pageEnd=14133, url=null, language=null, rfNumber=[79], rfOrder=80, authorNames=ZHOU Z H, WENG L, TAT T, journalName=ACS Nano, refType=null, unstructuredReference=ZHOU Z H, WENG L,TAT T,et al.Smart insole for robust wearable biomechanical energy harvesting in harsh environments[J].ACS Nano,2020,14(10):14126-14133., articleTitle=Smart insole for robust wearable biomechanical energy harvesting in harsh environments, refAbstract=null), Reference(id=1321967907949621331, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, doi=null, pmid=null, pmcid=null, year=2025, volume=16, issue=null, pageStart=4426, pageEnd=null, url=null, language=null, rfNumber=[80], rfOrder=81, authorNames=SHIN H S, KIM J, FADELL N, journalName=Nature Communications, refType=null, unstructuredReference=SHIN H S, KIM J, FADELL N,et al.Soft,skin-interfaced wireless electrogoniometry systems for continuous monitoring of finger and wrist joints[J].Nature Communications,2025,16:4426., articleTitle=Soft,skin-interfaced wireless electrogoniometry systems for continuous monitoring of finger and wrist joints, refAbstract=null)], funds=[Fund(id=1321967896314621952, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, awardId=2020YFF0304605, language=CN, fundingSource=国家重点研发计划“科技冬奥”重点专项(2020YFF0304605), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1321967891709277136, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, xref=1., ext=[AuthorCompanyExt(id=1321967891717665745, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, companyId=1321967891709277136, language=EN, country=null, province=null, city=null, 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ArticleFig(id=1321967895815500795, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, language=EN, label=Fig.2, caption=Key technology of flexible wearable devices in basic vital signs[37,44-48], figureFileSmall=0N75ILtoullaD6pJo/Efow==, figureFileBig=p38+oN4Awq2TzaHnbjXahA==, tableContent=null), ArticleFig(id=1321967895895192572, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, language=CN, label=图2, caption=柔性可穿戴设备在基础生理指标中的关键技术[37,44-48], figureFileSmall=0N75ILtoullaD6pJo/Efow==, figureFileBig=p38+oN4Awq2TzaHnbjXahA==, tableContent=null), ArticleFig(id=1321967895995855869, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, language=EN, label=Fig.3, caption=Application of flexible wearable devices in 24 h physical behavior

(a)application in physical activity[66,68-69,78-79];(b)application in sleep[75];(c)application in sedentary behavior[67,73,80]

, figureFileSmall=yPKrzM8o5B8tRztzX8lbfg==, figureFileBig=wOAmxEb/bQXXlNB1/SXjjQ==, tableContent=null), ArticleFig(id=1321967896071353342, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, language=CN, label=图3, caption=柔性可穿戴设备在24 h身体行为中的应用

(a)在体力活动中的应用[66,68-69,78-79];(b)在睡眠监测中的应用[75];(c)在久坐行为中的应用[67,73,80]

, figureFileSmall=yPKrzM8o5B8tRztzX8lbfg==, figureFileBig=wOAmxEb/bQXXlNB1/SXjjQ==, tableContent=null), ArticleFig(id=1321967896142656511, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, language=EN, label=Table 1, caption=

Performance comparison of flexible wearable energy systems

, figureFileSmall=null, figureFileBig=null, tableContent=
Energy-harvesting technologyEnergy sourceOutput performanceCycle/stabilityApplication scenarioRef.
OPV-ZIB integrated systemIndoor/outdoor lightη >16%, P >10.2 mW/cm², p>5.82 mWh/cm²OPV: >92% retention after 500 h;ZIB: >86% capacity retention after 200 cycles;system maintains >80% efficiency after 500 bending cycles

Wearable sensors, smart

watches

[61]
BFC-AgCl-Zn microgrid

Finger sweat

(lactate)

VOC(BFC): 1.4 V;battery pack output:≈2.0 V;

continuous power supply

Self-charging without motion;supports long-term continuous operation

Multi-metabolite monitoring,health

assessment

[64]
PEET textileGarment friction (mechanical energy)p: 4.46 W/(m²·Hz);η: 19%Performance exceeds conventional TENG by over two orders of magnitude;scalable integrationSportswear, high-power wearable energy systems[60]
PolaTex fabricAmbient electromagnetic field (50/60 Hz)Maximum energy recovery: 10.2 mW/person;sufficient to power a heart rate monitorUtilizes human body as “antenna”;enables distributed, continuous power

Low-power office

devices,wireless sensors

[63]

TENG smart

insole

Gait mechanical energyWireless self-powered, stable outputPerformance depends on sustained motion;material durability is critical

Gait analysis, foot

biomechanics monitoring

[65]
), ArticleFig(id=1321967896222348288, tenantId=1146029695717560320, journalId=1220038251117760515, articleId=1321967890316768199, language=CN, label=表1, caption=

不同柔性可穿戴材料供能系统的性能比较

, figureFileSmall=null, figureFileBig=null, tableContent=
Energy-harvesting technologyEnergy sourceOutput performanceCycle/stabilityApplication scenarioRef.
OPV-ZIB integrated systemIndoor/outdoor lightη >16%, P >10.2 mW/cm², p>5.82 mWh/cm²OPV: >92% retention after 500 h;ZIB: >86% capacity retention after 200 cycles;system maintains >80% efficiency after 500 bending cycles

Wearable sensors, smart

watches

[61]
BFC-AgCl-Zn microgrid

Finger sweat

(lactate)

VOC(BFC): 1.4 V;battery pack output:≈2.0 V;

continuous power supply

Self-charging without motion;supports long-term continuous operation

Multi-metabolite monitoring,health

assessment

[64]
PEET textileGarment friction (mechanical energy)p: 4.46 W/(m²·Hz);η: 19%Performance exceeds conventional TENG by over two orders of magnitude;scalable integrationSportswear, high-power wearable energy systems[60]
PolaTex fabricAmbient electromagnetic field (50/60 Hz)Maximum energy recovery: 10.2 mW/person;sufficient to power a heart rate monitorUtilizes human body as “antenna”;enables distributed, continuous power

Low-power office

devices,wireless sensors

[63]

TENG smart

insole

Gait mechanical energyWireless self-powered, stable outputPerformance depends on sustained motion;material durability is critical

Gait analysis, foot

biomechanics monitoring

[65]
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面向24 h身体行为监测应用的柔性可穿戴智能材料应用研究进展
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郭佳 1 , 唐嘉凯 1 , 侯少卿 1 , 张栋 2 , 曹春梅 1
材料工程 | 面向柔性可穿戴器件的智能材料专栏 2026,54(6): 13-24
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材料工程 |面向柔性可穿戴器件的智能材料专栏 2026 , 54 (6) : 13 -24
面向24 h身体行为监测应用的柔性可穿戴智能材料应用研究进展
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郭佳1, 唐嘉凯1, 侯少卿1, 张栋2, 曹春梅1
作者信息
  • 1.清华大学 体育部,北京 100084
  • 2.首都体育学院 体育人工智能研究院,北京 100091
通讯作者:
曹春梅(1977—),女,副教授,博士,研究方向:运动生物力学、运动训练与机能监控,联系地址:北京市海淀区清华大学北体育馆(100084),E-mail:
Application and research progress in flexible wearable intelligent materials for 24 h physical behavior monitoring
Jia GUO1, Jiakai TANG1, Shaoqing HOU1, Dong ZHANG2, Chunmei CAO1
Affiliations
  • 1.Division of Sports Science and Physical Education,Tsinghua University,Beijing 100084,China
  • 2.Institute of Artificial Intelligence in Sports,Capital University of Physical Education and Sports,Beijing 100091,China
出版时间: 2026-06-20 doi: 10.11868/j.issn.1001-4381.2025.000686
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现代生活方式带来了久坐、睡眠障碍等公众健康问题,柔性可穿戴智能材料凭借其较好的生物相容性与信号采集连续性,成为24 h身体行为(体力活动、久坐行为、睡眠)精准监测的核心技术支柱。本文旨在剖析该领域从基础理论到工程应用的研究现状,探讨了柔性电子界面在体力活动监测中的应用,阐述了传感器的材料创新实现从宏观生物力学感知到微观代谢产物追踪的演变;进一步分析了柔性电子材料在识别久坐行为中的作用,重点介绍了如何利用高灵敏度材料捕捉人体的姿势变化及评估生理负荷;在睡眠健康领域,则聚焦于无感化材料对睡眠呼吸与节律的监测。此外,还梳理了支撑设备长效续航的自供能及高效储能技术,如摩擦电、光伏及生物燃料电池等前沿方案。同时指出当前该领域仍面临标准化验证缺失、设备续航不足、行为与生理深层关系模糊等挑战。未来需通过材料创新、多模态传感融合、人工智能算法优化及大规模临床验证,以期构建全生命周期的智能化健康管理生态。

可穿戴设备  /  体力活动  /  久坐  /  睡眠  /  健康

Modern lifestyles are associated with significant public health concerns, including sedentary behavior and sleep disorders. Flexible wearable intelligent materials, characterized by excellent biocompatibility and continuous signal acquisition capabilities, are becoming a pivotal technology for the precise 24 h monitoring of physical behaviors (e.g., activity, sedentariness, and sleep). This review aims to dissect the current research landscape in this field, from theoretical foundations to engineering applications. It first explores the use of flexible electronic interfaces in physical activity monitoring, highlighting how material innovations have enabled the expansion from macroscopic biomechanical sensing to microscopic metabolite tracking. The role of these materials in identifying sedentary behaviors is then analyzed, focusing on high-sensitivity designs for capturing postural transitions and assessing physiological load. For sleep health, the discussion centers on unobtrusive material systems for long-term monitoring of respiratory and sleep rhythms. Furthermore, to support the extended operation of such wearable devices, this review synthesizes advanced self-powering and energy storage solutions, such as triboelectric nanogenerators, photovoltaics, and biofuel cells. Persistent challenges are identified, including the lack of standardized validation, limited battery life, and insufficient understanding of the complex correlations between behavior and physiology. Future progress is expected to depend on the convergence of material innovation, multimodal sensor fusion, optimized artificial intelligence algorithms, and large-scale clinical trials, ultimately contributing to a comprehensive smart health management ecosystem.

wearable device  /  physical activity  /  sedentary behavior  /  sleep  /  health
郭佳, 唐嘉凯, 侯少卿, 张栋, 曹春梅. 面向24 h身体行为监测应用的柔性可穿戴智能材料应用研究进展. 材料工程, 2026 , 54 (6) : 13 -24 . DOI: 10.11868/j.issn.1001-4381.2025.000686
Jia GUO, Jiakai TANG, Shaoqing HOU, Dong ZHANG, Chunmei CAO. Application and research progress in flexible wearable intelligent materials for 24 h physical behavior monitoring[J]. Journal of Materials Engineering, 2026 , 54 (6) : 13 -24 . DOI: 10.11868/j.issn.1001-4381.2025.000686
随着科技的不断迭代,人们的生活方式发生了深刻变革,随即引发体力活动不足、高久坐暴露水平、睡眠障碍等一系列公共健康问题[1-2]。“体力活动-久坐行为-睡眠模式”的24 h身体行为与人体健康密切相关(图1),任何年龄段人群都应每周进行适宜的体力活动,因为久坐行为会对心血管、神经、消化等系统带来负面影响[3-7],还会影响睡眠质量进一步加重对身体的负担[8-9]。为应对这一全球健康挑战,以提升人类健康水平为目的的可穿戴技术应运而生。该技术有极大的潜力通过对人体生化环境进行无创连续的监测,为精准医疗的发展奠定了重要基础[1,10]。尤其在24 h身体行为监测方面,可穿戴设备能够连续地捕获身体行为数据(包含体力活动、久坐习惯、睡眠模式),有效规避传统监测手段所带来的问卷回忆偏移、主观偏差等问题。
早期身体活动监测主要依赖惯性测量单元或基于微机电系统的加速度计。这类设备通常体积较大、刚性强,且需由专业人员固定于特定身体部位(如髋部或腰部),在一定程度上降低了受试者依从性,限制了其广泛应用。此外,该类技术多依赖实验室环境,难以真实反映个体在自然状态下的全天行为特征。尤其在睡眠监测中,即便被视为金标准的多导睡眠仪,也常因设备复杂、佩戴不适而干扰受试者睡眠,降低数据的生态效度。因此,具备便携性与无感特征的可穿戴设备对于实现长期、精准的生理监测具有关键意义[1,11]。
近年来,柔性电子与人工智能科学技术的突破性进展推动了新一代可穿戴设备的发展。以柔性基板、可拉伸导体、仿生传感界面为代表的柔性可穿戴设备逐渐走入大众视野。这类材料不仅能与机体紧密地贴合,还能使人体在几乎无感的状态下实现对生理与行为信号的连续、稳定、精确采集[12-13]。可见,柔性材料的引入不仅显著提高了设备的佩戴舒适性和用户满意度,更为实现真正意义上的长时间、高精度的24 h身体行为监测奠定了坚实的物理基础[11]。
基于此,本综述聚焦于柔性可穿戴智能设备在24 h身体行为监测中的赋能作用,系统梳理该类设备对基础生命体征的监测和能源供给的关键类型、传感机制,以及在体力活动、久坐行为与睡眠三大健康行为领域中应用进展,旨在为后来的健康导向型的可穿戴系统的设计与临床应用提供借鉴和理论支撑,为提升公众健康水平、构建健康中国作出贡献。
24 h身体活动监测正在从“实验室刚性”走向“自然柔性”,确保长期佩戴的绝对舒适性与安全性,实现大量数据的标准化与临床解读是该领域发展的重要目标。
当前应用于体力活动与久坐识别中的柔性可穿戴设备主要有可集成传感器[14]、鞋垫[15]、织物电子上衣[16]、耳内传感器[17]、皮肤贴片[18]等形态;主要应用部位包括:颈部[19]、面部(前额)[20]、前臂与手腕[21-22]、足部[23]、耳道[17]、腋下[16]、腰背部[23]、口鼻[24]等关键动力学节点。在睡眠监测领域,主要形式为集成传感器,如绑带、敷贴、口罩、服饰[25-30]等形态,这些设备主要应用在口鼻[31]、前额与下颌[28]、前臂与腕部[30]等部位当中。这些多形态、多部位部署方式的实现,依赖于柔性材料在低模量匹配、形变适应性和长期贴附稳定性方面的工程优势。
根据检测功能和转换机制的不同,目前的设备主要分为三类:首先是生理电信号监测,用于心律失常、肌肉疲劳等方面的分析,主要的设备形态包括:电子皮肤[32-33]、智能贴片[19,34]、纺织衣物[16,35]等,核心监测原理是通过柔性电极直接接触皮肤,采集生物电信号;还有生物力学与运动监测,主要涉及柔性应变传感器[31]、智能纺织品[35-36]、集成惯性单元[37],其核心监测原理主要是通过物理量的传感转换,将人体运动产生的机械形变(如拉伸、扭转、弯曲)实时转化为电信号,从而分析人体的关节运动角度、步态、姿势等等;以及生理生化指标监测,涉及智能纺织品[16,36,38]、微流控贴片[18]、气流传感器[24,29]等材料,通过对汗液、相关激素和呼吸等生理指标的收集,进行人体代谢机能状态的分析等。
从材料应用进展来看,柔性可穿戴设备的材料正从单一柔性向多功能复合柔性发展,目的在于保证佩戴时的机械顺应性,实现信号稳定传导与生物相容性等需求。在柔性基底层方面,聚酰亚胺(PI)、聚对苯二甲酸乙二醇酯(PET)、SEBS以及Ecoflex、PDMS等弹性体材料被广泛应用[19-30,39]。其中,PI与PET具有良好的热稳定性和工艺兼容性,适用于集成柔性晶体管、电极阵列和微流控结构[20,30];而SEBS、Ecoflex与PDMS由于其低弹性模量和良好的可拉伸性,更常用于电子皮肤、贴片式传感器和智能纺织品中,从而使材料与身体更加贴合[19,29,40]。在传感材料方面,MXene(如Ti3C2T x )因具有高导电性和对湿度、生化分子的敏感特性,被用于呼吸、睡眠和代谢相关指标监测[20,31];碳纳米管、石墨烯及其复合材料广泛应用于应变、压力与电化学传感[25,29];柔性压电材料(如PZT)能够通过结构设计实现生物力学信号向电信号的高效转换[19,41]。此外,基于In2O3等氧化物半导体的柔性晶体管,以及酶或适配体功能化电极,能够有效实现激素和代谢物的选择性检测[30,42]。在皮肤与设备贴合方面,双网络水凝胶(如PVA/PAAm、明胶/PAAm)既有低模量,又具备高韧性,能够有效提升皮肤贴附稳定性并降低长期佩戴的不适风险[31,43]。同时,集成微流控通道或离子导入胶的界面层,可实现汗液、呼吸气流或离子信号的连续采集与传输[19-20,39]。在封装和黏附方面,PDMS、Ecoflex、SEBS以及医用级PU膜被广泛用于器件防护与绝缘[19,25,28];同时,仿生黏附材料(如模仿蜘蛛丝或皮肤微结构的黏附层)能够在保证稳固贴附的同时减少皮肤刺激和运动伪差[28,40]。
在深入探讨特定身体行为之前,首先讨论柔性可穿戴技术在实现对心率(heart rate,HR)、血氧饱和度(blood oxygen saturation,SpO2)、心电(electrocardiogram,ECG)、肌电(electromyography,EMG)、脑电(electroencephalogram,EEG)等基础生命生理信号的连续、无感化监测方面的贡献(图2[37,44-48])。这些信号是评估机体功能状态的核心指标,代表了神经系统、心血管系统、呼吸系统、运动系统等的工作状态,是解析体力活动、久坐与睡眠期间生理反应的重要前提。本节将从柔性电极材料与生物电信号监测、柔性光学材料与SpO2/脉搏监测以及能源续航技术3个方面展开叙述。
HR是评估个体在日常生活中生理状态、心血管适应性的核心生理指标。静息状态下的HR可以反映机体基础代谢状态[49],睡眠心率可以评估夜间心脏负荷与恢复能力[50],而实时运动监测则能评估运动负荷并预警心律失常[51]。目前,运动状态下的HR监测主要通过ECG和光电容积脉搏波(photoplethysmography,PPG)两种技术实现。ECG是反映心脏节律性变化的电生理信号,能够提供HR、心脏节律和心脏结构变化等关键信息[52]。传统Ag/AgCl凝胶电极易引起皮肤过敏,且因模量失配在运动中易产生位移,导致汗液环境下导电性衰减与信号失真[53]。为突破界面适配瓶颈,须深入研究具备高电学稳定性与本征自黏附性的新型柔性干电极。在分子设计层面,Lin等[53]在聚(3,4-乙撑二氧噻吩)-聚苯乙烯磺酸(PEDOT:PSS)体系中引入麦芽糖醇实现二次掺杂,通过增塑效应获得了低杨氏模量(7 MPa)与高电导率(102 S/cm)的绿色干电极,该电极可实现与皮肤的紧密贴合,显著降低皮肤-电极界面抗阻(100 Hz时48.2 kΩ·cm²),并在EMG、ECG及EEG信号采集中表现出较低噪声与良好的长期稳定性。针对多汗环境下的稳定性难题,Yang等[44]制备了丝素蛋白/聚吡咯(SF/PPy)互锁生物复合电极,利用丝素蛋白在潮湿环境下的模量调节特性增强皮肤黏附力。为了克服传统刚性临床设备在长程监测中的机械失配问题,柔性电子技术通过材料创新与结构设计的协同,实现了高保真的脉搏波及心电信号提取。在制造工艺与电极设计方面,Park等[45]利用全丝网印刷技术制备的聚酰亚胺/聚乙二醇(PI/PEG)物理共混物,通过相分离诱导的多孔结构提升了皮肤透气性,配合Ag/AgCl导电网络与蛇形图案设计,使器件在30%的拉伸应变下仍能保持稳定的界面阻抗,为高精度心率变异性(heart rate variability,HRV)分析奠定了基础。在器件物理结构与集成上,Kim等[37]开发了基于反射模式的微型集成系统,通过将厚度仅为4.1 μm的无机砷化镓光电探测器与红色LED集成在柔性基底上,实现了极小的弯曲半径(2.4 mm),使其能够贴附于指甲或前臂等复杂部位捕捉微弱的脉搏特征波形。
除HR和SpO2等生命体征外,EMG和EEG等生物电信号的实时监测可从肌肉与中枢神经系统层面为身体状态变化提供重要补充信息。EMG是由神经冲动引发肌纤维去极化所产生的电信号,已广泛应用于运动康复、训练评估和运动表现分析等领域[54]。然而,传统表面肌电易受运动伪影干扰,尤其是剧烈活动引起的电极位移和阻抗变化。针对这一问题,Park等[45]研发了具备良好拉伸性的导电材料,在丝网印刷工艺方面将聚酰亚胺与聚乙二醇混合,使其具备了剪切稀化特性,这种非牛顿流体特性极大提升了聚酰亚胺的印刷性能,在力学几何方面,采用了蛇形几何设计使其能够顺应皮肤形变并维持稳定接触,从而保障肌电信号质量。Zhang等[46]报道了一种电导率可达545 S/cm,在30%压力应变下电阻变化仅为5.5%的可穿戴本征导电聚合物干电极,在运动状态下仍可获得优于传统电极的信号质量,上述性能的提升在材料层面主要源于两点:第一,低模量的导电网络可在形变中保持电路的连续性;第二,界面黏附与离子-电子协同传导机制有效抑制了接触阻抗的波动。这两点共同作用,从原理上降低了运动伪影的生成。此外,Zhang等[36]受皮肤中“软弹性蛋白-硬胶原”复合结构的启发,开发出一种新型导电纱线。其设计核心是将刚性导线制成正弦波形,并与高弹性纤维机械互锁,这使其同时具备了高导电、高拉伸和高强度的特性。这种结构不仅在大应变范围内保持低刚度以确保舒适佩戴,还能在临近失效时触发自保护性刚化,从而兼顾了稳定性与耐久性。此类可直接将导电材料编织成织物,为设计适用于真实运动场景的生物电监测电极开辟了新的道路。相较于EMG,EEG能够直接反映中枢神经系统活动,在睡眠分期和认知负荷评估中具有独特优势。然而,其信号幅值低,易受运动伪影、电磁干扰及皮肤阻抗的影响,对头皮-电极界面的稳定性、力学顺应性与高密度集成提出了更高要求。因此,柔性干式EEG电极在动态行为场景下实现稳定、高信噪比采集仍具挑战,使其在24 h连续监测中更适合作为睡眠或低活动状态下的补充信号。
SpO2是血液中氧合血红蛋白占总可结合血红蛋白的比值,反映了血液含氧量与携氧能力的比例关系。静息状态下SpO2能够反映人体呼吸系统、心血管系统的健康情况。在身体活动过程中监测SpO2可以实时评估氧代谢需求和疲劳程度[55],睡眠时监测SpO2可以帮助监测呼吸暂停等睡眠障碍问题[56]。柔性SpO₂监测的研究重点,已从宏观形态适配深入至微观材料特性的精准调控。在挑战物理厚度极限方面,Felici等[54]通过仅3 μm厚的聚合物发光二极管(organic light-emitting diode,OLED)与有机光电探测器(organic photodiode,OPD)的集成,实现了无感化的血氧与脉搏监测。针对光电传感的灵敏度和高功耗问题,Lee团队[57]提出了一个“混合反射式”的设计方案,其采用无机发光二极光作为光源,以及环绕式有机光电二极管作为光信号探测器,使用层压工艺把二者集成,通过调控OPD的吸收特性与界面工程,有效抑制了侧向光耦合,从而在降低驱动功耗的同时,增强了对微弱SpO2信号的捕捉能力。Kang等[58]通过调控异质结的界面能垒,基于铟镓锌氧化物与二酮吡咯并吡咯聚合物的光电晶体管实现了极高的探测灵敏度,其比探测率达到了1.00×10¹³ Jones,在<5 V的低电压下即可实现全天的心血管健康预警。此外,Polat等[47]为了提升监测的灵敏度,并降低功耗,异质结与低维材料被广泛应用:利用石墨烯敏化半导体量子点的宽谱吸收特性,器件可在环境光下工作,为无电池的监测提供了可能。
在提升检测精度与环境稳定性方面,Lee等[35]基于直径仅250 μm的一维柔性光纤平台,成功研发出红绿光两种量子点发光纤维设备,将该设备与柔性光电探测器结合,构建可穿戴血氧监测贴片,这种贴片高光谱纯度显著提升了血氧计算精度,还可以与织物集成。Jinno等[59]针对有机材料的环境稳定性瓶颈,通过引入聚乙烯亚胺乙氧基化修饰层并设计倒置器件结构,成功调节了电极功函数,提升了载流子注入效率。这使得微米级厚度的“光电皮肤”无需封装也能保持长效稳定。此外,为了支撑“全天候”监测需求,Lai等[33]提出了一种基于微纤维封装网状液态金属的电子皮肤,该研究首次实现了将环境电磁污染与生物力学能协同转化为电能。该透气材料体系不仅能自供电,还能高保真捕捉眼睑、喉部等处的微弱生理信号,为构建高度集成的自驱动生物电子系统提供了新思路。综上所述,柔性血氧监测从基础的物理适配向高性能、长效稳定的智能生物电子系统演变。这种材料与功能的深度融合,为实现全天候、精准化的临床级移动医疗奠定了坚实基础。
在当前追求连续、无感人体监测的背景下,柔性可穿戴设备面临一项根本挑战:如何在多场景切换中保持长期稳定运行,同时避免频繁充电或更换电池。为解决这一矛盾,近年研究正着力发展自供能与无电池一体化技术,旨在实现传感、供能与通信三者的高效协同。Wang等[15]研发的一种全集成、自供能的智能鞋垫系统,系统集成了柔性钙钛矿太阳能电池,将光能转化为电能,为内部的22个压力传感器和蓝牙传输模块供电,消除了对大体积外部电源的依赖。东华大学团队[60]开发的等离子体增强能量纺织物(plasma-enhanced energy textile,PEET),通过模拟自然界“闪电回击”机制,利用两种高分子材料(PA11和P(VDF-TrFE))纳米纤维层之间电子亲和力的差异,驱动电荷发生极化分离,实现了高达19%的能量转换效率,功率输出远超传统静电技术。基于光能转化的技术展现出了全天候持续供能潜力,Saifi等[61]研发的90 μm超薄柔性能量采集-存储系统(flexible energy harvesting and storage system,FEHSS),将高效有机光伏(organic photovoltaics,OPV)与超薄锌离子电池(zinc-ion battery,ZIB)集成,其功率密度超10 mW/cm²,能量密度超5.82 mWh/cm²,FEHSS系统为无感化长时间的健康监测提供了理想的动力供给。针对自主式传感器在稳定采样和高耗能方面的挑战,Min等[22]研发了钙钛矿柔性太阳能电池驱动的自主式柔性汗液传感系统,其采用柔性准二维钙钛矿太阳能电池模块,即便是室内微弱的灯光也能够提供充足电力。此外,He等[62]基于体热供电的柔性热电织物,为可穿戴系统提供了一条无需外部干预的持续供能路径,其依据3D编织结构,采用内层刚性外层柔性的编织结构,通过在织物内部维持稳定温差,在确保高透气性和舒适贴合的同时,可实现体热能量采集与多物理信号的稳定输出。除环境能量采集外,部分研究尝试直接利用人体或周围电磁环境实现供能。如Li等[63]研发的PolaTex技术创新性地利用人体作为介电体,从50/60 Hz环境电磁场(如笔记本电脑辐射)中回收能量,最高可输出10.2 mW/人,成功驱动心率监测设备。还有贴片或织物可通过手机读写器实现能量采集和数据传输,Lin等[16]研发的基于液态金属纤维的数字化刺绣技术将高性能液态金属纤维集成到衣物中,其可利用刺绣形成的电磁感应线圈,实现近场供能。Ding等[64]研发的指尖微电网系统利用指尖高密度汗腺(约400个/cm²)分泌的汗液,通过乳酸基生物燃料电池(biofuel cell, BFC)实时发电,并为可拉伸AgCl-Zn电池充电,无需任何身体活动。系统集成了多路传感器与蓝牙模块,可实现对葡萄糖、乳酸等关键代谢物的自供电、连续、无线监测。
需要指出的是,在高通道密度或高采样率的生理信号采集场景(如EMG、ECG及柔性超声阵列)中,部分多模态平台仍需依赖柔性电路与可充电锂电池,以保障信号稳定性与系统可靠性[40-41]。总体来看,柔性可穿戴能源技术正朝多路径协同方向发展,以满足不同场景生理监测的能耗需求,支撑对活动、久坐及睡眠中应激与恢复过程的长期解析。表1展示了不同柔性可穿戴材料供能系统的性能比较[60-61,63-65]。
柔性可穿戴技术的不断进步,推动了身体行为监测从严格的实验室评估,向自然状态下的身体行为检测迈进,对人类生命健康促进起到了重大贡献。本节将系统梳理该技术在上述三大行为领域的最新应用进展,揭示其如何重塑健康评估与疾病管理范式。
传统体力活动监测多依赖于问卷或加速度计获取步数或能量消耗等结局指标。柔性可穿戴技术的介入能够实现对生物力学、人体代谢与能量供给的系统性闭环监测,为精准运动处方与健康风险评估提供了较为精确的数据维度。
在生物力学感知层面,柔性传感器通过仿生设计与材料创新,可以实现对运动姿态的高精度捕捉。为实现更加精确的运动负荷评估,柔性传感器不仅需要实现运动计数,更需要捕捉精细的负荷。以足底压力监测为例,Li团队[66]通过仿生设计,利用离子动力学机制构建传感器。当微结构受压时,接触面积比例增长与离子自适应调节协同作用,使其在0~1 MPa的超宽范围内实现了高线性响应(R²=0.997),从而将胫骨负荷评估误差降至1.8%。Wang等[15]针对传统穿戴式鞋垫传感器存在的非线性响应、稳定性差和能源受限等调整,采用高线性度传感机制,将柔性太阳能电池嵌入鞋垫,实现了对多种运动状态的识别。为了消除剧烈运动中传感器与皮肤“模量失配”引起的信号失真,本征低阻抗且高形变的液态金属、展现出显著优势。Lin等[16]利用数字刺绣工艺制备的液态金属纤维电子织物,在经历高频机械拉伸后仍能保持导电网络完整性,支撑长效的无线生理监测。进一步,Guo等[40]通过分布聚硼硅氧烷来模拟蜘蛛网黏液的特性,增强了电子皮肤的黏性,确保在复杂运动下不脱落,并且利用半液态金属的流动导电特性缓解界面应变集中,将材料的高延展性转化为器件层面的低阻抗与低噪声特性,其获取的电生理信号质量优于传统Ag/AgCl电极,手势识别准确率达93.9%。此外,考虑到长期监测的大众化需求,Fastier-Wooller团队[67]通过银基油墨与热黏附织物开发的“熨烫式”传感器,利用成熟的印刷工艺解决了导电层在动态弯折下的耐洗涤性,在自然行走条件下实现了96%的步态识别准确率。Park团队[34]采用柔性贴片式表皮触觉设备,集成远程机器学习框架,可以处理复杂的全身运动数据,适用于远程康复训练、模拟比赛、游戏社交等场景。针对日常佩戴的机械损伤问题,Lee等[32]最新研究开发的超快自修复电子皮肤能在10 s内恢复80%的功能,并且能够准确识别疲劳的产生。这种从微观能带调控、界面力学优化到工程化稳定性提升的多尺度材料革新,正驱动柔性生物电子向高性能、全天候的运动负荷监测系统演变。
在代谢监测方面,柔性电化学传感器的结构与材料迭代使运动中汗液乳酸的实时检测成为可能。从材料工程角度看,电极材料的生物相容性、催化活性以及基底的柔顺性,直接决定了传感器在动态出汗条件下的稳定性。Zhu等[42]构建了一种无电池、可无线通信的柔性乳酸贴片,采用酶电极、导电碳墨对电极与PET基底组成电化学体系,并通过射频能量采集供能。其中,碳基导电材料与柔性高分子基底的协同设计,使电化学反应界面在皮肤形变和汗液浸润条件下仍能保持稳定输出。结合微流控取样结构,其在0~10 MPa范围内可实现高线性度响应(R²=0.998)。多日跑步实验进一步验证,初始汗液乳酸水平与肌肉疲劳累积相关(r=0.79),证实了该平台在个体化训练负荷评估中的应用潜力。然而在静息或低强度活动下,汗液分泌会减少,为此,Wu等[68]提出了一种仿猪笼草的分层微流控贴片,上层微通道与下层肋状结构引导液体分散,从而降低界面阻力,使汗液在极低流速下仍能被吸引进入通道,将静息态下的无感汗液收集效率提升2倍,还有Saha团队[18]研发的一种基于渗透-毛细协同机制的汗液收集贴片,通过高渗透压水凝胶与多孔纤维素纸基的材料组合,可实现自供能的持续取样。在低汗率条件下,该系统仍可实现长达12 h的稳定采样。
在大规模人群队列的流行病学研究中,柔性可穿戴设备为体力活动监测提供了重要的平台。基于英国生物样本库的加速度计数据集的前瞻性队列研究证实,即便是日常生活中短暂的高强度间歇性的体力活动,如爬楼梯、快步追公交,也能降低全因死亡率和多种疾病风险。例如,对于无规律运动习惯的个体,每日仅需3~5 min的高强度间歇性活动,即可使全因死亡率风险降低38%~40%,心血管疾病死亡率风险降低48%~49%[69]。这种间歇性的高强度体力活动还与癌症总体发病率以及多种与运动相关癌症发病率(如肺癌、乳腺癌等)的下降显著相关[70]。然而,现有的流行病学证据多依赖于单一维度的加速度计数据,难以揭示体力活动对人体深层生理机能的动态影响。为了实现从宏观行为向微观生理机制解析的跨越,有学者正致力于开发能够同步追踪血流动力学与代谢生物标志物的集成系统。例如, Sempionatto等[19]研发的一种集成超声换能器与电化学传感器的表皮贴片,利用电化学机制监测组织间液中的葡萄糖,汗液中的乳酸、咖啡因和酒精,还能利用超声波检测深层组织的血压和心脏节律波形,揭示了身体在应对日常活动时的代偿性生理响应。从材料工程视角看,将大规模流行病学证据转化为真实世界的干预手段,亟须具备机械稳定性、无感化的柔性材料体系,并且可以揭示深层生理机制,才能为精准公共卫生干预提供高保真的底层数据支撑。
久坐行为通常被定义为清醒状态下能量消耗不超过1.5代谢当量(metabolic equivalents,METs)的坐姿或躺姿活动。然而,仅以能量消耗作为判定标准,难以准确刻画不同久坐模式所蕴含的健康风险差异。随着柔性可穿戴技术的发展,该领域的研究正逐步从以久坐时长为核心的粗放计量,向精细的姿势识别与深层的生理指标深化。
针对久坐行为的设备的多形态、多部位部署方式的实现,依赖于柔性材料在低模量匹配、形变适应性和长期贴附稳定性方面的工程优势。其中智能鞋垫能够精确表征足底压力分布变化,从而量化久坐-活动状态。Wang等[15]报道了一种新型集成的足底压力实时监测系统,团队采用非线性协同策略克服了传统传感器的局限性,并在鞋垫内部署了22个压力传感器,可以生成较高空间分辨率的阻力压力热力图,还支持向量机模型,能够精准识别坐立、站立等各种久坐及低强度活动姿态。Bu团队[71]在普通打印纸上浸涂导电的Ti3C2T x MXene纳米片,并且在表面涂抹疏水的蜡烛灰,其在干燥过程中由于导电涂层与纸基底之间的弹性模量和热膨胀系数不一致,于是在涂层内部形成了灵敏的微裂纹结构,该系统传感器可以检测面部肌肉的细微变化,可以用于辅助医疗诊断或人机交互。Cai等[72]发现摩擦电纳米发电机(TENG)同时承担了能量采集与信号转导功能,使器件在无需外部供能的条件下实现高信噪比与快速响应,能够稳定捕捉眨眼、咀嚼等低幅动作,为办公久坐场景下的疲劳与认知负荷评估提供了新的客观指标。
针对久坐行为的研究重心已由简单的时长统计转向静息代谢状态的综合分析。其中汗液是一项有效的分析指标汗液中的皮质醇、腿黑色、电解质与昼夜戒律、睡眠结构、自主神经活动密切相关,在久坐条件下与睡眠条件下进行连续汗液检测可以评估睡眠质量、压力负荷和基础代谢稳定[2]。Wang团队[30]研发了一种集成化适效应管的传感系统智能手表,具体是开发了一种新型的皮质醇特异性适体,并且将其与米薄膜氧化铟(In2O3)场效应晶体管结合,实现了对汗液中微量皮质醇的实时定量分析。Saha团队[18]提出了一种渗透-毛细采样机制,构建了一个由多层柔性材料组成的被动式流体管理系统,其采样层通过皮肤接触的水凝胶,利用渗透压原理在无须主动排汗的情况下,即可收集久坐、办公或睡眠等状态下的代谢标志物。Wu等[68]受猪笼草分层微结构的启发,研发了一种汗液收集贴片,其在通道内集成了宽度仅为20 μm的肋条结构,能够充分发挥毛细作用力,尽管是极低的0.5 μL汗液分泌量,也可以将其汇聚到中心检测区,大大提高了汗液收集效率。Nyein团队[73]同样报道了一种能够在人体静息状态下持续监测热调节汗液的柔性微流控贴片,其利用微流控结构结合亲水填料,极大缩短了收集汗液用时,贴片集成了多种传感器,可以检测汗液率、pH值、氯离子以及左旋多巴浓度,为静息状态下的自主神经系统和代谢监测提供了平台。Lin团队[74]开发了一种针对天然排汗的血糖监测系统,该系统采用水凝胶贴片从手部快速吸取汗液,并用普鲁士蓝掺杂的PEDOT纳米复合材料电极进行电化学传感,打破了传统血糖传感器需要通过运动刺激排汗的限制,适用于在常规办公和久坐活动中进行血糖管理的场景。除皮肤生化分析外,静息生理状态还可通过呼吸特征加以补充,Escobedo团队[24]研发了一种集成在口罩内部的无线智能传感平台,可以集成光化学指示膜的智能口罩利用高分辨率的CO2监测,揭示了久坐状态下的通气负荷与呼吸节律变化。综上,久坐行为监测正利用适体场效应管、渗透-毛细微流控及智能口罩等柔性技术,实现对皮质醇、血糖及肺通气情况等指标的实时追踪,推动研究重心从时长计量向静息代谢状态的深度解析跨越。
柔性可穿戴设备正构建无感化、长时程的睡眠监测新范式,为实现客观的整夜监测提供了条件。Lee团队[75]研发的一种名为WiSP的超薄柔性心脏监测设备,平均厚度仅为1 mm,质量仅有1.2 g,由聚氨酯弹性封装、柔性电路与医用生物黏附层构成,可在皮肤曲面上实现高度贴合并保持防水性能,其无感化特征解决了传统电极干扰睡眠的问题,能够稳定检测夜间HR及HRV。Zhang等[26]开发了一种基于生物可降解材料的无线智能呼吸监测系统,通过可降解壳聚糖-碳纳米管(carbon nanotube, CNT)薄膜做成的TENG或通过纳米柱阵列增强灵敏度的柔性TENG,将材料界面能量转换能力直接转化为可用电信号,该系统能够实现对呼吸的实时监测,可以监控睡眠呼吸暂停等事件的发生。类似的,Song等[76]开发了一种基于图案化铝塑膜和内置悬臂弹簧片的柔性、低成本TENG,其可以实现自供能,并且可以监测人体在睡眠时期的身体状态。Kim等[29]研发的一种集成于口罩的像素画传感阵列,该材料具有高透气性和拉伸性,得益于其高空间分辨率,该口罩可以实时识别口/鼻呼吸切换、鼻塞等呼吸行为,具有探测睡眠呼吸暂停的潜力。Ni等[31]的研究构建了一个具备高灵敏度、高拉伸性的有机水凝胶湿度传感器,采用聚乙烯醇和聚丙烯酰胺构成的双网络水凝胶结构,并引入MXene与氯化锂协同提升感知性能,配合水-甘油体系提升抗干燥与抗冻性能,此贴片可以佩戴于口鼻附近,实时解析呼吸频率、幅度,还能够对夜间呼吸节律实现连续捕捉。Sun团队[25]利用石墨烯的高导电性与细菌纤维素的优异力学性能,构建了3D多孔石墨烯/细菌纤维素生物气凝胶。该材料具备20 Pa~30 kPa的宽工作范围,且拥有高灵敏度与循环稳定性,还可以实现对呼吸波形及频率的实时捕获,该设备可以为睡眠呼吸暂停的居家监测提供可能。
在系统集成与数据分析层面,睡眠监测正由单一参数记录向多维解析演进。传统多导睡眠仪成本高,设备沉重,针对此问题Kwon团队[28]构建了一个集成传感器硬件与智能算法的完整穿戴平台,其中硬件架构方面采用柔软、全集成的可穿戴平台,并且设备以面部贴片形式佩戴,能够同步检测EEG和EMG,算法方面集基于卷积神经网络(convolutional neural network, CNN)-门控循环单元(gated recurrent unit,GRU)架构,可以识别睡眠分期与阻塞性睡眠呼吸暂停事件。Zhang等 [26]研究中也引入小样本学习的CNN能在训练数据受限条件下有效学习呼吸信号特征,实现对正常呼吸、阻塞性呼吸与呼吸暂停的区分。此外,谷歌团队[77]基于可穿戴长期纵向数据的大语言模型已展现出生成个性化睡眠洞察和预测主观睡眠质量的潜力。Kwon团队[28]的蓝牙贴片式系统通过本地预处理后回传多通道信号,在保证数据质量的同时满足夜间长时续航与佩戴舒适性需求。
尽管柔性可穿戴技术已实现多模态传感与智能分析,但其长期睡眠监测的临床应用仍面临个体差异、佩戴稳定性等挑战。未来需在材料、系统与算法三方面协同创新:提升界面生物相容性与耐久性,实现多信号低功耗同步采集,并融合纵向大数据与可解释人工智能,从而推动睡眠监测从“状态识别”向“健康预测”跨越,最终融入全程健康管理(图3[66-69,73,75,78-80])。
柔性可穿戴技术正处于从“功能验证”向“临床准入”跨越的关键窗口期。尽管该领域在24 h无感监测方面已取得长足进展,但要真正重塑公共健康管理模式,仍需在材料底层的自主化、系统逻辑的生理化以及验证体系的标准化上实现根本性突破。
首先,材料系统的演进应超越单一的传感功能,向“感知-能源-自愈”高度集成的自主生态演进。未来的设计不应仅局限于提升传感器灵敏度,而应致力于构建具备本征自修复能力的超薄材料体系,从物理层面化解长期服役中的界面失效难题。同时,应深耕离子动力学调控与仿生流体架构,解决静息态下痕量汗液采样的时效性瓶颈;并结合多源能量采集技术,通过捕获环境电磁能与生物机械能,为设备提供无感的持久能源底座,这也是实现全天候、可持续监测的重要的物理路径。
在信号解析层面,研究逻辑需要回归材料本身的物理化学响应机理。人工智能不应仅是处理复杂数据的“黑盒”,而更应通过揭示材料在力、热、电、生化等多维刺激下的交叉敏感机制,实现物理层面的信号分离,从而建立基于材料本征响应的生理特征模型。这种机理驱动的特征提取方法,能够有效滤除运动等背景噪声,更精准地揭示自主神经系统在不同行为状态下的协同调节规律,为健康干预提供具备物理解释力的底层依据。
此外,建立柔性传感界面与生物标志物之间的动态响应关联模型,是实现临床认可的关键前提。当前亟须开展跨尺度动态基线研究,理清汗液等非侵入式体液与血液金标准在分子层面的传质规律与响应映射关系,剔除因材料界面个体差异带来的信号干扰。同时,必须规范不同生理部位的采样流程,并建立可量化的数字健康评价标准。只有在完成上述基础工作后,柔性传感器输出的数据才能真正具备临床诊断所需的“证据价值”。
综上所述,柔性可穿戴智能设备凭借其亲肤适配与持续监测的优势,实现了对人体行为与生理信号的全天候捕捉。随着材料工程、微纳制造与可解释人工智能的深度融合,这类设备正从实验室走向成熟,将进化为更可靠、符合临床金标准的智能生物电子系统,为构建覆盖全生命周期的个体化健康管理体系奠定技术基础。
  • 国家重点研发计划“科技冬奥”重点专项(2020YFF0304605)
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2026年第54卷第6期
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doi: 10.11868/j.issn.1001-4381.2025.000686
  • 接收时间:2025-11-26
  • 首发时间:2026-10-27
  • 出版时间:2026-06-20
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  • 收稿日期:2025-11-26
  • 录用日期:2026-01-28
基金
国家重点研发计划“科技冬奥”重点专项(2020YFF0304605)
作者信息
    1.清华大学 体育部,北京 100084
    2.首都体育学院 体育人工智能研究院,北京 100091

通讯作者:

曹春梅(1977—),女,副教授,博士,研究方向:运动生物力学、运动训练与机能监控,联系地址:北京市海淀区清华大学北体育馆(100084),E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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