Classifying Alzheimer’s wandering and apathetic behaviours using indoor and outdoor localization data

Dementia, especially Alzheimer’s disease, is increasing due to population ageing and is projected to nearly triple by 2050. Understanding and identifying common behaviours such as apathy, depression, and wandering can enable caregivers and medical professionals to enhance the quality of care for patients and implement appropriate interventions to mitigate cognitive decline. This paper analyses localization data collected from patients with mild cognitive impairment and Alzheimer’s disease residing in a healthcare facility. In particular, metrics and behavioural indices are computed to classify the behaviour of individuals. The proposed method was initially applied to the localization data of seven residents, each exhibiting distinct behaviours. Subsequently, validation was conducted using data from 46 patients monitored over three months. Classification results were compared with the observations made by healthcare operators and physicians. The study demonstrated a high level of accuracy in classifying patients into different behavioural domains, such as wandering and depressed–apathetic, with 42 out of 46 cases correctly classified.

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Publication Details

Journal
Journal of Ambient Intelligence and Smart Environments
Published
2025-02-18
DOI
https://doi.org/10.1177/18761364241306100
Citations
2
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
2.94
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article

Classifying Alzheimer’s wandering and apathetic behaviours using indoor and outdoor localization data

Sara Comai, Andrea Masciadri, Fabio Salice
2 citations
Journal of Ambient Intelligence and Smart Environments
Dementia and Cognitive Impairment Research
2.94
article

Classifying Alzheimer’s wandering and apathetic behaviours using indoor and outdoor localization data

Sara Comai, Andrea Masciadri, Fabio Salice
article en
2 citations

Abstract

Dementia, especially Alzheimer’s disease, is increasing due to population ageing and is projected to nearly triple by 2050. Understanding and identifying common behaviours such as apathy, depression, and wandering can enable caregivers and medical professionals to enhance the quality of care for patients and implement appropriate interventions to mitigate cognitive decline. This paper analyses localization data collected from patients with mild cognitive impairment and Alzheimer’s disease residing in a healthcare facility. In particular, metrics and behavioural indices are computed to classify the behaviour of individuals. The proposed method was initially applied to the localization data of seven residents, each exhibiting distinct behaviours. Subsequently, validation was conducted using data from 46 patients monitored over three months. Classification results were compared with the observations made by healthcare operators and physicians. The study demonstrated a high level of accuracy in classifying patients into different behavioural domains, such as wandering and depressed–apathetic, with 42 out of 46 cases correctly classified.

Journal of Ambient Intelligence and Smart EnvironmentsVol. 17(2)
Politecnico di Milano (IT)
Openalex Percentile: Top 12%
Dementia and Cognitive Impairment Research
2.94
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