Evidence map›Paper›PMID 33498590›Full record

ArticleSensors (Basel, Switzerland)2021

Night-Time Monitoring System (eNightLog) for Elderly Wandering Behavior.

James Chung-Wai Cheung, Eric Wing-Cheong Tam, Alex Hing-Yin Mak, Tim Tin-Chun Chan, Will Po-Yan Lai, Yong-Ping Zheng

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 33 citations in OpenAlex.

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  6. Contactless monitoring of human behaviors in bed using RSSI signals.Medical & biological engineering & computing · 2023
    Article
  7. Sensors for Human Physical Behaviour Monitoring.Sensors (Basel, Switzerland) · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 2 countries.

James Chung-Wai CheungDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China.ORCID 0000-0001-7446-0569
Eric Wing-Cheong TamJockey Club Smart Ageing Hub, Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Alex Hing-Yin MakJockey Club Smart Ageing Hub, Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Tim Tin-Chun ChanJockey Club Smart Ageing Hub, Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Will Po-Yan LaiJockey Club Smart Ageing Hub, Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Yong-Ping ZhengDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Hong Kong Polytechnic University · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wandering is a common behavioral disorder in the community-dwelling elderly. More than two-thirds of caregivers believe that wandering would cause falls. While physical restraint is a common measure to address wandering, it could trigger challenging behavior in approximately 80% of the elderly with dementia. This study aims to develop a virtual restraint using a night monitoring system (eNightLog) to provide a safe environment for the elderly and mitigate the caregiver burden. The eNightLog system consisted of remote sensors, including a near infra-red 3D time-of-flight sensor and ultrawideband sensors. An alarm system was controlled by customized software and algorithm based on the respiration rate and body posture of the elderly. The performance of the eNightLog system was evaluated in both single and double bed settings by comparing to that of a pressure mat and an infrared fence system, under simulated bed-exiting scenarios. The accuracy and precision for the three systems were 99.0%, 98.8%, 85.9% and 99.2%, 97.8%, 78.6%, respectively. With higher accuracy, precision, and a lower false alarm rate, eNightLog demonstrated its potential as an alternative to physical restraint to remedy the workload of the caregivers and the psychological impact of the elderly.

Indexed as

Monitoring, PhysiologicWandering BehaviorAccidental FallsAgedCaregiversHumansIndependent Livingbed exitingdementiaelderlyfallnight monitoringnursing homeremote sensingultrawideband radarwandering

Identifiers

PMID33498590
PMCPMC7864330
OpenAlexW3121816566

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.