Research shows how sensor-based health monitoring could help tackle age-related health problems

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Specific changes in our movement patterns can be indicators of several health problems: For instance, decrease in strength often correlates with risk of falls, mild cognitive impairment, depression, sleep problems, respiratory problems, cardiac arrhythmias and increasing myocardial weakness or worsening of a COVID-19 infection. In older individuals, systematic detection of such changes could help identify chronic diseases such as dementia, Parkinson's disease, or heart disease at an early stage. These age-related health problems are often discovered late, and their progression is usually difficult to assess objectively.

An interdisciplinary research team led by Tobias Nef of the ARTORG Center for Biomedical Engineering Research, and Professor Emeritus of Cardiology Hugo Saner of the University of Bern and Bern University Hospital, now shows how large-scale, sensor-based health monitoring could tackle these problems. The researchers combined a variety of everyday activity and behavior patterns measured by sensors in the homes of elderly study participants helping them to create a summary picture.

We used non-contact sensors at home to create an extensive collection of digital measures that capture broad parts of daily life, behavior and physiology, in order to identify health risks of older people at an early stage."

Dr. Narayan Schütz, study first author and postdoctoral researcher

This may benefit early detection as well as foster development of personalized treatments and research into new therapeutic approaches and drugs. The study was published in npj Digital Medicine.

Reliable system accepted by seniors

The researchers initially collected 1,268 health parameters using non-interaction sensors particularly tailored to the senior demographic. The deployed system consists of simple, contactless motion sensors in each room, a bed sensor under the mattress, and door sensors on the front door and on the refrigerator. Connected to a base station, the system analyzes the registered motion signals and can inform relatives or an alarm center in the event of problems or emergencies – such as when a person does not return to bed at night. The researchers then evaluated the data collected in this way using machine learning approaches.

"We were able to show that such a systems approach – in contrast to the common use of a few health metrics – allows to detect age-relevant health problems such as cognitive impairment, fall risk or frailty surprisingly well," says Tobias Nef, Professor of Gerontechnology and Rehabilitation at the ARTORG Center and co-last author of the study. Compared to wearable devices, this sensor-based home monitoring approach was perceived well among seniors: As the interdisciplinary research group led by Tobias Nef and Hugo Saner was able to prove in a scientific collaboration of computer science, behavioral research and medicine spanning more than ten years, older test subjects in Switzerland found the daily operation of mobile devices rather cumbersome, and some were unable to handle them at all due to dexterity or cognitive problems. In particular, older adults above 80 years of age clearly preferred a zero-interaction system such as the one used in the study.

Great potential

The evaluation and combination of the large amount of everyday health data also offers the potential to identify possible new aging-relevant digital biomarkers: "For example, we found indications that fall risk could significantly depend on certain sleep parameters," explains Tobias Nef.

Prof. Hugo Saner, who was responsible for clinical data collection and is co-last author of the study, assesses the clinical relevance of the results: "Such a system marks a milestone in early detection of worsening health for seniors living alone into old age. We assume that it can make a significant contribution to enabling older people to live at home for as long as possible by delaying hospital admissions and transfers to nursing institutions or, in the best case, even avoiding them." According to the researchers, better early detection, and personalized treatment of typical diseases of old age would not only help older people achieve better health, but also reduce healthcare costs.

Source:

University of Bern

Journal reference:

Schütz, N., et al. (2022) A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust. npj Digital Medicine. doi.org/10.1038/s41746-022-00657-y.

全文翻譯（僅供參考）

我們的運(yùn)動(dòng)模式的具體變化可能是幾個(gè)健康問題的指標(biāo)：例如，力量下降通常與跌倒、輕度認(rèn)知障礙、抑郁、睡眠問題、呼吸問題、心律失常以及心肌無力或 COVID 惡化的風(fēng)險(xiǎn)相關(guān)-19 感染。在老年人中，系統(tǒng)檢測這些變化可以幫助早期識(shí)別慢性疾病，如癡呆、帕金森病或心臟病。這些與年齡相關(guān)的健康問題往往被發(fā)現(xiàn)較晚，而且它們的進(jìn)展通常難以客觀評(píng)估。

由 ARTORG 生物醫(yī)學(xué)工程研究中心的 Tobias Nef 和伯爾尼大學(xué)和伯爾尼大學(xué)醫(yī)院心臟病學(xué)名譽(yù)教授 Hugo Saner 領(lǐng)導(dǎo)的跨學(xué)科研究團(tuán)隊(duì)現(xiàn)在展示了基于傳感器的大規(guī)模健康監(jiān)測如何解決這些問題. 研究人員結(jié)合了老年人研究參與者家中傳感器測量的各種日?；顒?dòng)和行為模式，幫助他們創(chuàng)建一個(gè)概要圖。

我們?cè)诩抑惺褂梅墙佑|式傳感器創(chuàng)建了廣泛的數(shù)字測量集合，捕捉日常生活、行為和生理的廣泛部分，以便及早識(shí)別老年人的健康風(fēng)險(xiǎn)。”

Narayan Schütz 博士，研究第一作者和博士后研究員

這可能有利于早期發(fā)現(xiàn)以及促進(jìn)個(gè)性化治療的發(fā)展以及對(duì)新治療方法和藥物的研究。該研究發(fā)表在npj Digital Medicine上。

老年人接受的可靠系統(tǒng)

研究人員最初使用專為老年人量身定制的非交互傳感器收集了 1,268 個(gè)健康參數(shù)。部署的系統(tǒng)由每個(gè)房間中簡單的非接觸式運(yùn)動(dòng)傳感器、床墊下方的床傳感器以及前門和冰箱上的門傳感器組成。該系統(tǒng)連接到基站，分析注冊(cè)的運(yùn)動(dòng)信號(hào)，并在出現(xiàn)問題或緊急情況時(shí)通知親屬或警報(bào)中心——例如當(dāng)一個(gè)人晚上沒有回到床上時(shí)。然后，研究人員使用機(jī)器學(xué)習(xí)方法評(píng)估了以這種方式收集的數(shù)據(jù)。

“我們能夠證明，這種系統(tǒng)方法——與通常使用一些健康指標(biāo)相比——可以很好地檢測與年齡相關(guān)的健康問題，如認(rèn)知障礙、跌倒風(fēng)險(xiǎn)或虛弱，”教授 Tobias Nef 說ARTORG 中心的老年技術(shù)和康復(fù)博士，也是該研究的共同最后作者。與可穿戴設(shè)備相比，這種基于傳感器的家庭監(jiān)控方法在老年人中得到了很好的評(píng)價(jià)：由 Tobias Nef 和 Hugo Saner 領(lǐng)導(dǎo)的跨學(xué)科研究小組能夠在跨越十多個(gè)計(jì)算機(jī)科學(xué)、行為研究和醫(yī)學(xué)的科學(xué)合作中證明多年以來，瑞士年長的測試對(duì)象發(fā)現(xiàn)移動(dòng)設(shè)備的日常操作相當(dāng)繁瑣，有些人由于靈巧或認(rèn)知問題根本無法處理。

此外，數(shù)據(jù)保護(hù)和隱私被優(yōu)先考慮：“為了確保技術(shù)層面的隱私和數(shù)據(jù)保護(hù)，采用了最高的瑞士和歐洲醫(yī)療數(shù)據(jù)安全標(biāo)準(zhǔn)”，Narayan Schütz 指出。為了保護(hù)隱私，部署的傳感器也不會(huì)記錄聲音或視頻，而且它們的安裝完全是自愿的——這兩個(gè)方面都得到了研究參與者的贊賞。

潛力巨大

大量日常健康數(shù)據(jù)的評(píng)估和組合還提供了識(shí)別可能與衰老相關(guān)的新數(shù)字生物標(biāo)志物的潛力：“例如，我們發(fā)現(xiàn)跌倒風(fēng)險(xiǎn)可能在很大程度上取決于某些睡眠參數(shù)的跡象，”Tobias Nef 解釋說。

負(fù)責(zé)臨床數(shù)據(jù)收集的 Hugo Saner 教授是該研究的共同最后作者，他評(píng)估了結(jié)果的臨床相關(guān)性：“這樣的系統(tǒng)標(biāo)志著早期發(fā)現(xiàn)獨(dú)居老年人健康狀況惡化的里程碑。. 我們認(rèn)為它可以通過推遲入院和轉(zhuǎn)移到護(hù)理機(jī)構(gòu)，或者在最好的情況下，甚至避免它們，為使老年人盡可能長時(shí)間地住在家里做出重大貢獻(xiàn)?！?nbsp;研究人員表示，對(duì)老年典型疾病進(jìn)行更好的早期發(fā)現(xiàn)和個(gè)性化治療，不僅可以幫助老年人獲得更好的健康，還可以降低醫(yī)療成本。

THE EN

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