Sensortechnology for monitoring challenging behavior in nursing home residents with dementia

Jan Kleine Deters; Rinesh Baidjnath Misier; Sarah Janus; Huib Burger; Heinrich Wörtche; Sytse U Zuidema

doi:10.1017/s104161022300217x

Sensortechnology for monitoring challenging behavior in nursing home residents with dementia

Jan Kleine Deters, Rinesh Baidjnath Misier, Sarah Janus, Huib Burger, Heinrich Wörtche, Sytse U Zuidema

Sensors and Smart Systems

University of Groningen, University Medical Center, Alzheimer Center Groningen, Department of General Practice and Elderly Care Medicine
University of Groningen, University Medical Center Groningen, Faculty of Medical Sciences, Department of General Practice, Geriatrics

Onderzoeksoutput: Article › Academic › peer review

Samenvatting

Achtergrond
Neuropsychiatrische symptomen (NPS) komen vaak voor bij getroffen personen en kunnen een uitdaging vormen voor (in)formele zorgverleners. Daarom worden ze ook wel uitdagend gedrag (CBs) genoemd. Sensortechnologie die context en gedrag meet, kan helpen om CB's op een objectieve manier effectief te beheren. Sensoren kunnen professionals in de gezondheidszorg, zoals verpleegkundigen, helpen door op afstand gedragsveranderingen die samenhangen met CB's te monitoren en alarmeren. Dit kan/zal de kwaliteit van leven (QoL) verbeteren voor zowel zorgverleners als cliënten die in een verpleeghuis wonen.

In het project “MOnitoring Onbegrepen Gedrag bij Dementie met sensortechnologie” (MOOD-Sense) willen we een dergelijk monitoringsysteem ontwikkelen. Ons onderzoek richt zich op twee vragen 1) Hoe ontwikkel en implementeer je een monitoringsysteem binnen de context van verpleeghuizen met parameters over omgeving, fysiologie en gedrag, identificeer en verwerk je relevante precursoren van uitdagend gedrag met dit monitoringsysteem en 2) krijg je inzicht in welk gedrag uitdagend is volgens verpleegkundigen en hoe dit beschreven wordt. Dit zal worden gerepresenteerd in een ontologie zodat sensorgegevens kunnen worden vertaald naar dezelfde conceptuele informatie.

Originele taal-2	English
Pagina's (van-tot)	45-46
Aantal pagina's	2
Tijdschrift	International Psychogeriatrics
Volume	35
Nummer van het tijdschrift	S1
DOI's	https://doi.org/10.1017/s104161022300217x
Status	Published - dec. 2023

Keywords

sensortechnologie
verzorgingstehuizen
dementie
monitoring
caregivers

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10.1017/s104161022300217xLicentie: CC BY-NC-ND

https://www.sciencedirect.com/science/article/pii/S1041610224059052?via%3DihubLicentie: CC BY-NC-ND

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title = "Sensortechnology for monitoring challenging behavior in nursing home residents with dementia",

abstract = "Background:: Neuropsychiatric symptoms (NPS) are common in affected individuals and can be challenging for (in)formal caregivers. Therefore, they are also referred to as challenging behaviors (CBs). Sensor technology measuring context and behavior can be assistive to effectively manage CBs in an objective fashion. Sensors can help support healthcare professionals, such as nurses, by enabling remote monitoring and alarming on early-stage behavioral changes associated with CBs. This might/ will improve the quality of life (QoL) for both caregivers and clients living in a nursing homes (NH). Methods:: The first research question will be examined with a set of experiments in the field (in NH) with an iterative approach. Insights from previous experiments on usability and added value of sensors will be used to improve successive experiments. During each experiment, multiple participants (clients with dementia and CBs) are monitored with both ambient and wearable sensors. For the second research question a qualitative approach is employed, using focus groups (FG) and consensus methods. These FGs will be held amongst nursing staff who are involved in daily care tasks for people with dementia. Subsequently, consensus methods are used to align behavioral descriptors/labels. Results:: early findings will be presented at the symposium Discussion:: Within this project we expect to find precursors of challenging behavior in a personalized fashion based on nurse{\textquoteright}s expert knowledge and sensor data. In order to develop a monitoring system that can be embedded within NH{\textquoteright}s, real-time alarming, in-situ behavior recognition and trustworthiness are part of our technological requirements. Just-in-time interventions may then be deployed to prevent behavior escalation or the persistence of undesirable situations.",

keywords = "sensor technology, nursing homes, dementia, monitoren, zorgverleners, sensortechnologie, verzorgingstehuizen, dementie, monitoring, caregivers",

author = "Deters, {Jan Kleine} and Misier, {Rinesh Baidjnath} and Sarah Janus and Huib Burger and Heinrich W{\"o}rtche and Zuidema, {Sytse U}",

year = "2023",

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doi = "10.1017/s104161022300217x",

language = "English",

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AU - Deters, Jan Kleine

AU - Misier, Rinesh Baidjnath

AU - Janus, Sarah

AU - Burger, Huib

AU - Wörtche, Heinrich

AU - Zuidema, Sytse U

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Y1 - 2023/12

N2 - Background:: Neuropsychiatric symptoms (NPS) are common in affected individuals and can be challenging for (in)formal caregivers. Therefore, they are also referred to as challenging behaviors (CBs). Sensor technology measuring context and behavior can be assistive to effectively manage CBs in an objective fashion. Sensors can help support healthcare professionals, such as nurses, by enabling remote monitoring and alarming on early-stage behavioral changes associated with CBs. This might/ will improve the quality of life (QoL) for both caregivers and clients living in a nursing homes (NH). Methods:: The first research question will be examined with a set of experiments in the field (in NH) with an iterative approach. Insights from previous experiments on usability and added value of sensors will be used to improve successive experiments. During each experiment, multiple participants (clients with dementia and CBs) are monitored with both ambient and wearable sensors. For the second research question a qualitative approach is employed, using focus groups (FG) and consensus methods. These FGs will be held amongst nursing staff who are involved in daily care tasks for people with dementia. Subsequently, consensus methods are used to align behavioral descriptors/labels. Results:: early findings will be presented at the symposium Discussion:: Within this project we expect to find precursors of challenging behavior in a personalized fashion based on nurse’s expert knowledge and sensor data. In order to develop a monitoring system that can be embedded within NH’s, real-time alarming, in-situ behavior recognition and trustworthiness are part of our technological requirements. Just-in-time interventions may then be deployed to prevent behavior escalation or the persistence of undesirable situations.

AB - Background:: Neuropsychiatric symptoms (NPS) are common in affected individuals and can be challenging for (in)formal caregivers. Therefore, they are also referred to as challenging behaviors (CBs). Sensor technology measuring context and behavior can be assistive to effectively manage CBs in an objective fashion. Sensors can help support healthcare professionals, such as nurses, by enabling remote monitoring and alarming on early-stage behavioral changes associated with CBs. This might/ will improve the quality of life (QoL) for both caregivers and clients living in a nursing homes (NH). Methods:: The first research question will be examined with a set of experiments in the field (in NH) with an iterative approach. Insights from previous experiments on usability and added value of sensors will be used to improve successive experiments. During each experiment, multiple participants (clients with dementia and CBs) are monitored with both ambient and wearable sensors. For the second research question a qualitative approach is employed, using focus groups (FG) and consensus methods. These FGs will be held amongst nursing staff who are involved in daily care tasks for people with dementia. Subsequently, consensus methods are used to align behavioral descriptors/labels. Results:: early findings will be presented at the symposium Discussion:: Within this project we expect to find precursors of challenging behavior in a personalized fashion based on nurse’s expert knowledge and sensor data. In order to develop a monitoring system that can be embedded within NH’s, real-time alarming, in-situ behavior recognition and trustworthiness are part of our technological requirements. Just-in-time interventions may then be deployed to prevent behavior escalation or the persistence of undesirable situations.

KW - sensor technology

KW - nursing homes

KW - dementia

KW - monitoren

KW - zorgverleners

KW - sensortechnologie

KW - verzorgingstehuizen

KW - dementie

KW - monitoring

KW - caregivers

UR - https://www.mendeley.com/catalogue/7c9d17c9-c3c8-3066-8106-36b28105e7d5/

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JO - International Psychogeriatrics

JF - International Psychogeriatrics

IS - S1

ER -

Sensortechnology for monitoring challenging behavior in nursing home residents with dementia

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Keywords

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