Assessing the Frailty of Older People using Bluetooth Beacons Data

Tsipouras, Markos G.; Γιαννακέας, Νικόλαος; Tegou, Thomas I.; Kalamaras, Ilias; Votis, Konstantinos; Tzovaras, Dimitrios

doi:10.1109/wimob.2018.8589154

Cited by 13 publications

(21 citation statements)

References 20 publications

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“…The localization system was first presented in [3], which is hereby extended with the addition of the frailty assessment study. Preliminary results of this study, with a small dataset, were presented in [4]. The measurements of activity are collected by monitoring the position of the older person in the house, at room level.…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Indoor Activity Monitoring System for Detecting Frailty in Older Adults

Tegou

Kalamaras

Tsipouras

et al. 2019

Sensors

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Indoor localization systems have already wide applications mainly for providing localized information and directions. The majority of them focus on commercial applications providing information such us advertisements, guidance and asset tracking. Medical oriented localization systems are uncommon. Given the fact that an individual’s indoor movements can be indicative of his/her clinical status, in this paper we present a low-cost indoor localization system with room-level accuracy used to assess the frailty of older people. We focused on designing a system with easy installation and low cost to be used by non technical staff. The system was installed in older people houses in order to collect data about their indoor localization habits. The collected data were examined in combination with their frailty status, showing a correlation between them. The indoor localization system is based on the processing of Received Signal Strength Indicator (RSSI) measurements by a tracking device, from Bluetooth Beacons, using a fingerprint-based procedure. The system has been tested in realistic settings achieving accuracy above 93% in room estimation. The proposed system was used in 271 houses collecting data for 1–7-day sessions. The evaluation of the collected data using ten-fold cross-validation showed an accuracy of 83% in the classification of a monitored person regarding his/her frailty status (Frail, Pre-frail, Non-frail).

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Section: Introductionmentioning

confidence: 99%

A Low-Cost Indoor Activity Monitoring System for Detecting Frailty in Older Adults

Tegou

Kalamaras

Tsipouras

et al. 2019

Sensors

Self Cite

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“…These phenomena have been measured transparently in many studies (16%, 9%, and 22%, respectively), and so have been mobility patterns (4%), stair climbing (3%), heart rate (1%), and arm movements (1%). All the studies relying on activity patterns (15 studies), mobility patterns (three studies), stair climbing (two studies), heart rate (one study), and arm movements (one study) involved transparent activities and did not involve any non-transparent activities [ 64 , 106 , 107 , 108 , 109 , 110 , 111 ]. Together, they represent 29% of all the studies.…”

Section: Discussionmentioning

confidence: 99%

“…In over half of the studies relying on transparent activities (23 out of 37—please note that [ 71 , 73 ] are include in both activity and gait patterns), the participants were monitored while carrying out their daily activities at home over several days: 14 out of 15 studies on activity patterns [ 71 , 73 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 ]; all six studies on gait patterns [ 71 , 72 , 73 , 74 , 75 , 76 ]; all three studies on mobility patterns [ 106 , 107 , 108 ]; and two studies on STS transitions [ 55 , 56 ]. However, the remaining 14 studies monitored the participants during simulated activities in the lab.…”

Section: Discussionmentioning

confidence: 99%

“…Studies on activity patterns measured parameters such as sedentary behavior, time spent active, and step counts [ 71 , 73 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 ]. Studies on mobility measured parameters such as the number of transitions between different rooms, the time spent in each room, and some other features derived from them [ 106 , 107 , 108 ]. Studies on stair climbing measured average power and peak power [ 64 , 109 ].…”

Section: Discussionmentioning

confidence: 99%

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Unobtrusive Sensors for the Assessment of Older Adult’s Frailty: A Scoping Review

Cobo

Villalba-Mora

Pérez‐Rodríguez

et al. 2021

Sensors

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Ubiquity (devices becoming part of the context) and transparency (devices not interfering with daily activities) are very significant in healthcare monitoring applications for elders. The present study undertakes a scoping review to map the literature on sensor-based unobtrusive monitoring of older adults’ frailty. We aim to determine what types of devices comply with unobtrusiveness requirements, which frailty markers have been unobtrusively assessed, which unsupervised devices have been tested, the relationships between sensor outcomes and frailty markers, and which devices can assess multiple markers. SCOPUS, PUBMED, and Web of Science were used to identify papers published 2010–2020. We selected 67 documents involving non-hospitalized older adults (65+ y.o.) and assessing frailty level or some specific frailty-marker with some sensor. Among the nine types of body worn sensors, only inertial measurement units (IMUs) on the waist and wrist-worn sensors comply with ubiquity. The former can transparently assess all variables but weight loss. Wrist-worn devices have not been tested in unsupervised conditions. Unsupervised presence detectors can predict frailty, slowness, performance, and physical activity. Waist IMUs and presence detectors are the most promising candidates for unobtrusive and unsupervised monitoring of frailty. Further research is necessary to give specific predictions of frailty level with unsupervised waist IMUs.

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“…Then, for validity purposes the authors correlated these measurements with the frailty scales as a ground truth (e.g., the Fried frailty phenotype scale). In this regard, while in some studies where ICT were used along with algorithms they were able to discriminate (detect) between different frailty levels (e.g., three levels, i.e., frail, non-frail, pre-frail) [27][28][29][30][31][32], other studies either failed to detect frailty [33] or did not provide any quantitative data about the accuracy of the algorithms used or the correlation coefficients [34][35].…”

Section: Technology Readiness Level Of the Ict Used To Manage Frailty In Older Adultsmentioning

confidence: 99%

Information and Communication Technologies for Managing Frailty: A Systematic Literature Review

Cruz¹,

Monsalve²,

Ladurner³

et al. 2021

Aging and disease

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Frailty is a prevalent condition among Canadians; over one million are diagnosed as medically frail, and in the next ten years this number will double. Information and telecommunication technologies can provide a low-cost method for managing frailty more proactively. This study aims to examine the range and extent of information and telecommunication technologies for managing frailty in older adults, their technology readiness level, the evidence, and the associated outcomes. A systematic literature review was conducted. Four databases were searched for studies: Medline, EMBASE, CINAHL, and Web of Science. In total, we included 19 studies (out of 9,930) for the data abstraction. Overall, our findings indicate that (1) the proposed frailty phenotype is the most common ground truth to be used for assessing frailty; (2) the most common uses of information and telecommunication technologies for managing frailty are detection, and monitoring and detection, while interventional studies on frailty are very rare; (3) the five main types of information and telecommunication technologies for managing frailty in older adults are information and telecommunication technology-based platforms, smartphones, telemonitoring (home monitoring), wearable sensors and devices (commercial off-the-shelf), and multimedia formats for online access; (4) the technology readiness level of information and telecommunication technologies for managing frailty in older adults is the "Technology Demonstration" level, i.e., not yet ready to be operated in an actual operating environment; and (5) the level of evidence is still low for information and telecommunication technology studies that manage frailty in older adults. In conclusion, information and telecommunication technologies for managing frailty in the older adult population are not yet ready to be full-fledged technologies for this purpose.

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Assessing the Frailty of Older People using Bluetooth Beacons Data

Cited by 13 publications

References 20 publications

A Low-Cost Indoor Activity Monitoring System for Detecting Frailty in Older Adults

A Low-Cost Indoor Activity Monitoring System for Detecting Frailty in Older Adults

Unobtrusive Sensors for the Assessment of Older Adult’s Frailty: A Scoping Review

Information and Communication Technologies for Managing Frailty: A Systematic Literature Review

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