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Nature Medicine:智能手表可以帮助连续、纵向评估并预测多种生理学变化!

2021-05-25 MedSci原创 MedSci原创

包括智能手表在内可穿戴设备或许可以帮助连续、纵向评估并预测多种生理学变化!

智能手表(Smartwatch)是安装有嵌入式系统、用于增强基于报时等功能的腕部手表,其功能相似于一台个人数码助理。早期智能手表既可以执行计算、翻译或者操作掌上电子游戏等基础功能,中期智能手表则实现了可穿戴式电脑的功能。

随着科学技术的发展,大多数智能手表可以运行流动软件应用程序,一些可以运行移动操作系统,少数有着完整的移动电话功能。而越来越多的研究将其与医疗保健进行结合。例如专门为训练、潜水以及户外运动而量身打造,又如训练计划、跑步圈数、速度显示、兼容心率监控等。

最近,来自美国杜克大学和斯坦福大学医学院的生物医学工程师和基因组学研究人员表示,智能手表和其他可穿戴设备可能可被用来感知疾病、脱水甚至红细胞数量的变化。

研究人员说,在机器学习的帮助下,关于心率、体温和日常活动的可穿戴设备数据可能被用来预测通常在临床验血期间观察到的健康测量。该研究发表在《自然医学》Nature Medicine杂志上。

在医生办公室就诊时,医务工作者通常会测量病人的生命体征,包括他们的身高、体重、体温和血压。尽管这些信息被归档在一个人的长期健康记录中,但它通常不被用来创建一个诊断。相反,医生会要求进行临床实验,测试病人的尿液或血液,以收集具体的生物信息,帮助指导健康决策。

但是这些测试并非没有缺点。例如进行血检验时患者必须亲临现场,这对病人来说并不总是容易安排的,而且像抽血这样的程序可能是侵入性的、不舒服的。

杜克大学的Jessilyn Dunn说:"心率和体温存在着昼夜变化,但就诊时单一测量可能并不能捕捉到这种自然变化,"他是这项研究的共同负责人和共同通讯作者。"但是像智能手表或Fitbits这样的设备有能力跟踪这些测量和长时间的自然变化,并识别何时出现了与该自然基线的变化。"

从使用可穿戴设备收集的生命体征预测临床实验室测量的方法。

这项研究于2015年在斯坦福大学开始,由综合个人全息图谱(iPOP)队列组成,包括54名患者。在三年时间里,iPOP参与者佩戴着英特尔Basis智能手表,测量他们的心率、运动、皮肤温度和汗腺的激活。参与者还参加了定期的门诊,研究人员使用传统的测量方法来跟踪心率、体温、红细胞和白细胞计数、血糖水平和铁水平等。

实验表明,智能手表的数据和临床血液测试之间存在多种联系。例如,如果参与者的手表显示他们的汗腺激活度较低,正如皮肤电传感器所测量的那样,这表明病人一直处于脱水状态。

个性化模型改善了从生命体征测量中对临床实验室测试的预测。

研究小组还发现,在完整的血液化验过程中进行的测量,如血细胞比容、血红蛋白、红细胞和白细胞计数,与可穿戴设备数据有密切关系。较高的持续体温加上有限的运动往往预示着疾病,这与临床测试中较高的白细胞计数相吻合。活动减少的记录和较高的心率也可能预示着贫血,当病人血液中没有足够的铁时就会发生贫血。

综上,这些结果证明了未来,包括智能手表在内可穿戴设备或许可以帮助连续、纵向评估并预测多种生理学变化!

 

参考文献:

Wearable sensors enable personalized predictions of clinical laboratory measurements. Nat Med (2021). https://doi.org/10.1038/s41591-021-01339-0

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    2022-03-11 kalseyzl
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    2021-08-13 jeanqiuqiu
  4. [GetPortalCommentsPageByObjectIdResponse(id=1953092, encodeId=78af195309238, content=<a href='/topic/show?id=b5e3600995e' target=_blank style='color:#2F92EE;'>#智能手表#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=87, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=60099, encryptionId=b5e3600995e, topicName=智能手表)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=3547346, createdName=dongjia2010, createdTime=Thu Feb 03 18:57:55 CST 2022, time=2022-02-03, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1773951, encodeId=68d81e7395182, content=<a href='/topic/show?id=5f014e1852' target=_blank style='color:#2F92EE;'>#CIN#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=56, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=4718, encryptionId=5f014e1852, topicName=CIN)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=a9a038523631, createdName=kalseyzl, createdTime=Fri Mar 11 00:57:55 CST 2022, time=2022-03-11, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1859148, encodeId=8545185914863, content=<a href='/topic/show?id=e0a9593596' target=_blank style='color:#2F92EE;'>#DIC#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=5935, encryptionId=e0a9593596, topicName=DIC)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=6f7770, createdName=jeanqiuqiu, createdTime=Fri Aug 13 10:57:55 CST 2021, time=2021-08-13, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1752821, encodeId=aa501e5282105, content=<a href='/topic/show?id=09736951388' target=_blank style='color:#2F92EE;'>#生理学#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=71, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=69513, encryptionId=09736951388, topicName=生理学)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1b3136571640, createdName=chenzhuanggui, createdTime=Mon Nov 08 06:57:55 CST 2021, time=2021-11-08, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1885174, encodeId=54ac18851e4f2, content=<a href='/topic/show?id=3b2112532d8' target=_blank style='color:#2F92EE;'>#Nat#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=56, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=12532, encryptionId=3b2112532d8, topicName=Nat)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=2e6f107, createdName=liye789132251, createdTime=Sat Nov 13 22:57:55 CST 2021, time=2021-11-13, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1577804, encodeId=a40815e7804f9, content=<a href='/topic/show?id=cda91148004' target=_blank style='color:#2F92EE;'>#Medicine#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=84, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=11480, encryptionId=cda91148004, topicName=Medicine)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=54cd16396700, createdName=ms1692212821629096, createdTime=Thu May 27 13:57:55 CST 2021, time=2021-05-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1611070, encodeId=621616110e00c, content=<a href='/topic/show?id=eb6b1145939' target=_blank style='color:#2F92EE;'>#Med#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=48, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=11459, encryptionId=eb6b1145939, topicName=Med)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=552a19396740, createdName=ms3994565386320060, createdTime=Thu May 27 13:57:55 CST 2021, time=2021-05-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=968489, encodeId=60d99684892b, content=智能手表无敌, beContent=null, objectType=article, channel=null, level=null, likeNumber=83, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20210817/23cddf8b4fd64eb993e1ce0dc039919a/a5d2416ef1744efb8a761e2b41df007f.jpg, createdBy=f9635507778, createdName=小火龙111, createdTime=Tue May 25 23:09:06 CST 2021, time=2021-05-25, status=1, ipAttribution=)]
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    2021-11-13 liye789132251
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    2021-05-25 小火龙111

    智能手表无敌

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拓展阅读

Nature Medicine:智能手表帮助提前7年发现帕金森病

这项研究显示,可穿戴设备(智能手表)可以在帕金森病出现标志性症状前7年识别出帕金森病,并可以做出临床诊断。

World Allergy Organ J:新型智能手表对过敏性鼻炎患者的用药依从性和症状控制的作用调查:试点研究

评估了一种新型智能手表在改善AR患者的用药依从性和症状控制方面的作用。同时,还调查了自我报告的用药可靠性。

JAHA:智能手表有助于经导管主动脉瓣置换术患者的远程健康管理

智能手表可以促进TAVR出院患者的远程医疗保健,并实现新的远程随访策略。在30天的随访中发生的大多数心脏临床事件是由智能手表检测到的。

NAT BME:从智能手表数据中预测COVID-19

早期发现传染病对于通过加强自我隔离和早期治疗来减轻疾病的传播非常重要。目前,大多数诊断方法包括从鼻腔液、唾液或血液中取样,然后用核酸检测活动性感染,或用血清学方法检测感染。基于核酸的诊断可能需要在暴露

谷歌Verily智能手表获美国FDA批准,可用于心电图节律检测

上周五,美国FDA批准了一款名为Verily Study Watch智能手表上的心电图功能(ECG),使其成为又一款可做医疗用途的智能手表。而推出该款手表的Verily和谷歌同属一个母公司,即Alphabet。因此,这款手表在坊间也广泛被成为“谷歌手表”。

欧姆龙(Omron)发布新款血压计 更像智能手表

血压测量通常需要在医生的帮助下进行,但欧姆龙却希望你可以随时随地都可以自行测量血压。这家日本厂商在本届CES展上带来了两款血压计,和同类型设备相比,它们使用起来要更加方便。 这两款血压计名叫Project Zero,使用者无需医生指导就能用它们来测量血压。两款设备分别是臂带式和腕带式,后者看上去更像是一部普通的智能手表,而非笨重的医疗设备。 通常来讲,在手腕上测量血压比较麻烦,你的

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