Behavior Recognition for Elderly People in Large-Scale Deployment

Endelin, Romain; Renouard, Stéphane; Tiberghien, Thibaut; Aloulou, Hamdi; Mokhtari, Mounir

doi:10.1007/978-3-642-39470-6_8

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…A large scale and immersive use of context aware systems may require to limit the variety and complexity of sensing technologies used, in order to make their deployment simple and straightforward [5]. This makes the failures inherent to sensing technologies even more challenging for context awareness, as the imprecision of sensors is even more critical and the reasoning is more uncertain due to the lack of data.…”

Section: Introductionmentioning

confidence: 97%

Uncertainty handling in semantic reasoning for accurate context understanding

Aloulou

Mokhtari

Tiberghien

et al. 2015

Knowledge-Based Systems

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Section: Introductionmentioning

confidence: 97%

Uncertainty handling in semantic reasoning for accurate context understanding

Aloulou

Mokhtari

Tiberghien

et al. 2015

Knowledge-Based Systems

Self Cite

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“…The successful operation of such systems heavily relies on the precise recognition of elderly behavior. Analyzing the daily life activities of the elderly and subsequently evaluating their ability to live independently can yield vital evidence for medical treatment, healthcare, and policy formulation [21,22]. Yet, the application of extant image-based behavior recognition methods for assessing the independent living ability of the elderly is impeded by several limitations [23].…”

Section: Introductionmentioning

confidence: 99%

A Novel Image Recognition-Based Assessment System for Elderly Independent Living Ability and Its Applications

Zhou¹

2023

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In an aging population, the gradual decline in cognitive, comprehensive, and mobility abilities poses a significant challenge for the independent living of the elderly. Accurate assessment of such abilities becomes crucial, not only for facilitating care-giving but also for policy-making related to elder care. To address this need, this study presents a novel image recognition-based assessment system designed to accurately evaluate the independent living ability of the elderly. The system construction and subsequent real-world applications constitute the initial focus of this study. Significant efforts have been made to detect key points of the skeletal structure in elderly individuals. The skeleton extraction process has been methodically divided into five distinct steps: detection of key points, matching and connecting joint points, generating coordinates of joint points and their connection maps, measuring correlations between key point pairs, and calculating optimal matching results using a bipartite graph approach. In the latter part of the study, an advanced model integrating an attention mechanism with a Graph Convolutional Neural Network (GCNN) has been developed and implemented for elder behavior recognition. The effectiveness and validity of this approach have been assessed through rigorous experimental validation. This study's findings can potentially revolutionize the quality of life assessment for the elderly and provide valuable insights for relevant policy-making. Further research in this direction is deemed necessary for enhancing the assessment system and expanding its applications.

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Assistive Technologies for Older Adults in Urban Areas: A Literature Review

Kötteritzsch

Weyers

2015

Cogn Comput

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Behavior Recognition for Elderly People in Large-Scale Deployment

Cited by 6 publications

References 9 publications

Uncertainty handling in semantic reasoning for accurate context understanding

Uncertainty handling in semantic reasoning for accurate context understanding

A Novel Image Recognition-Based Assessment System for Elderly Independent Living Ability and Its Applications

Assistive Technologies for Older Adults in Urban Areas: A Literature Review

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