Sensor Monitoring to Measure and Support Daily Functioning for Independently Living Older People: A Systematic Review and Road Map for Further Development

Pol, Margriet; Poerbodipoero, Soemitro; Robben, Saskia; Daams, Joost G.; Hartingsveldt, Margo van; Vos, Rien de; Rooij, Sophia E. de; Kröse, B.J.A.; Buurman, Bianca M.

doi:10.1111/jgs.12563

Cited by 31 publications

(22 citation statements)

References 29 publications

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“…These trends include the uniform use of electronic health records in hospitals,4 major advances in physiological sensor development,5 the rapid adoption of mobile technologies,6 and the ability to perform analytics in the background to provide decision support at the point of care 7…”

mentioning

confidence: 99%

Finding patients before they crash: the next major opportunity to improve patient safety

Bates

Zimlichman

2014

BMJ Qual Saf

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mentioning

confidence: 99%

Finding patients before they crash: the next major opportunity to improve patient safety

Bates

Zimlichman

2014

BMJ Qual Saf

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“…The later system allows an assistant to send a prompt remotely when the individual makes any mistake during task performance [20]. Despite these various developments, in a systematic review of the use of smart home technology for detecting and managing ADL, Pol et al (2013) argue that the evidence for validating and customising the application of sensing systems for communitydwelling (at home) older adults in their own homes is still scarce [21].…”

Section: Related Workmentioning

confidence: 99%

A Sensor Platform for Non-invasive Remote Monitoring of Older Adults in Real Time

Bennasar

McCormick

Price

et al. 2019

Innovation in Medicine and Healthcare Systems, and Multimedia

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The population of older adults is increasing across the globe; this growth is predicted to continue into the future. Most older adults prefer to live in their own home, but many live alone without immediate support. Living longer is often coupled with health and social problems and difficulty managing daily activities. Therefore, some level of care is required, but this is costly. Technological solutions may help to mitigate these problems by recognising subtle changes early and intervening before problems become unmanageable. Understanding a person's usual behaviour when carrying out Activities of Daily Living (ADL) makes it possible to detect and respond to anomalies. However, current commercial and research monitoring systems do not an analysis of ADL and are unable to detect subtle changes. To address this gap, we propose the STRETCH (Socio-Technical Resilience for Enhancing Targeted Community Healthcare) sensor platform that is comprised of non-invasive sensors and machine learning techniques to recognise changes and allow early interventions. The paper discusses design principles, modalities, system architecture, and sensor network architecture.

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“…These surveys show that other sensing modalities such as wearables or cameras can be useful as well, but in our study we only focus on simple ambient sensors. For the use of sensor data in clinical practice most solutions are not mature enough yet [9]. Most health monitoring systems aim at detecting anomalies in the behavioral pattern by applying predefined (or learned) thresholds on features derived from sensor data (e.g.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal ambient sensor monitoring for functional health assessments

Robben

Pol

Kröse

2014

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication

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Ambient monitoring systems offer great possibilities for health trend analysis in addition to anomaly detection. Health trend analysis helps care professionals to evaluate someones functional health and direct or evaluate the choice of interventions. This paper presents one case study of a person that was followed with an ambient monitoring system for almost three years and another of a person that was followed for over a year. A simple algorithm is applied to make a location based data representation. This data is visualized for care professionals, and used for inspecting the regularity of the pattern with means of principal component analysis (PCA). This paper provides a set of tools for analyzing longitudinal behavioral data for health assessments. We advocate a standardized data collection procedure, particularly the health metrics that could be used to validate health focused sensor data analyses.

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Sensor Monitoring to Measure and Support Daily Functioning for Independently Living Older People: A Systematic Review and Road Map for Further Development

Abstract: Studies on the effectiveness of sensor monitoring to support people in daily functioning remain scarce. A road map for further development is proposed.

Cited by 31 publications

References 29 publications

Finding patients before they crash: the next major opportunity to improve patient safety

Finding patients before they crash: the next major opportunity to improve patient safety

A Sensor Platform for Non-invasive Remote Monitoring of Older Adults in Real Time

Longitudinal ambient sensor monitoring for functional health assessments

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