Development of Clustering Algorithms for Older Faller in Malaysia

Wong, Kam Kang; Chuah, Yea Dat; Tan, Maw Pin; Ng, Siew‐Cheok; Goh, Choon-Hian

doi:10.1109/iecbes48179.2021.9398829

Cited by 2 publications

(2 citation statements)

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“…To better examine the possible associations between the constructs of the UTAUT2 and the 4 functional physical capacities tested, an unsupervised analysis was performed. Wong et al [ 43 ] used unsupervised analysis to determine fall risk groups based on fall-related functional physical capacities tests. In their unsupervised analysis, the K-means method was used to determine the fall groups and the optimal number of groups was established by the elbow method [ 44 ].…”

Section: Methodsmentioning

confidence: 99%

Section: Clusters Of Fall-related Functional Physical Capacitiesmentioning

confidence: 99%

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Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study

Hellec¹,

Hayotte²,

Chorin³

et al. 2023

J Med Internet Res

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Background As people age, their physical capacities (eg, walking and balance) decline and the risk of falling rises. Yet, classic fall detection devices are poorly accepted by older adults. Because they often wear eyeglasses as they go about their daily activities, daily monitoring to detect and prevent falls with smart eyeglasses might be more easily accepted. Objective On the basis of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study evaluated (1) the acceptability of smart eyeglasses for the detection and prevention of falls by older adults and (2) the associations with selected fall-related functional physical capacities. Methods A total of 142 volunteer older adults (mean age 74.9 years, SD 6.5 years) completed the UTAUT2 questionnaire adapted for smart eyeglasses and then performed several physical tests: a unipodal balance test with eyes open and closed, a 10-m walk test, and a 6-minute walk test. An unsupervised analysis classified the participants into physical performance groups. Multivariate ANOVAs were performed to identify differences in acceptability constructs according to the performance group. Results The UTAUT2 questionnaire adapted for eyeglasses presented good psychometric properties. Performance expectancy (β=.21, P=.005), social influence (β=.18, P=.007), facilitating conditions (β=.17, P=.04), and habit (β=.40, P<.001) were significant contributors to the behavioral intention to use smart eyeglasses (R²=0.73). The unsupervised analysis based on fall-related functional physical capacities created 3 groups of physical performance: low, intermediate, and high. Effort expectancy in the low performance group (mean 3.99, SD 1.46) was lower than that in the other 2 groups (ie, intermediate: mean 4.68, SD 1.23; high: mean 5.09, SD 1.41). Facilitating conditions in the high performance group (mean 5.39, SD 1.39) were higher than those in the other 2 groups (ie, low: mean 4.31, SD 1.68; intermediate: mean 4.66, SD 1.51). Conclusions To our knowledge, this study is the first to examine the acceptability of smart eyeglasses in the context of fall detection and prevention in older adults and to associate acceptability with fall-related functional physical capacities. The older adults with higher physical performances, and possibly lower risks of falling, reported greater acceptability of smart eyeglasses for fall prevention and detection than their counterparts exhibiting low physical performances.

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Section: Methodsmentioning

confidence: 99%

Section: Clusters Of Fall-related Functional Physical Capacitiesmentioning

confidence: 99%

Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study

Hellec¹,

Hayotte²,

Chorin³

et al. 2023

J Med Internet Res

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Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study (Preprint)

Hellec¹,

Hayotte²,

Chorin³

et al. 2022

Preprint

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BACKGROUND As people age, their physical capacities (e.g., walking, balance) decline and the risk of falling rises. Yet the classic fall detection devices are poorly accepted by older adults. Since they often wear eyeglasses as they go about their daily activities, daily monitoring to detect and prevent falls with smart eyeglasses might be more easily accepted. OBJECTIVE Based on the Unified Theory of Acceptance and Use of Technology-2 (UTAUT2), this study evaluated (1) the acceptability of smart eyeglasses for the detection and prevention of falls by older adults and (2) the associations with selected fall-related functional physical capacities. METHODS One hundred and forty-two volunteer elderly adults (mean age 74.9 years, SD 6.5 years) completed the UTAUT2 questionnaire adapted for smart eyeglasses and then performed several physical tests: unipodal balance test with eyes open and closed, 10-meter walk test, and 6-minute walk test. An unsupervised analysis classified the participants into physical performance groups. MANOVAs were run to identify differences in acceptability constructs according to the performance group. RESULTS The UTAUT2 questionnaire adapted for eyeglasses presented good psychometric properties. Performance expectancy, social influence, facilitating conditions, and habits were significant contributors to the behavioral intention to use smart eyeglasses (R²=.73). The unsupervised analysis based on fall-related functional physical capacities created three groups of physical performance: low, intermediate, and high. Effort expectancy was lower in the low performance group compared to the other two groups. Facilitating conditions was higher in the high-performance group than in the other two groups. CONCLUSIONS The elderly adults with higher physical performances, and possibly lower risks of falling, reported greater acceptability of smart eyeglasses for fall prevention and detection than their counterparts exhibiting low physical performances.

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Development of Clustering Algorithms for Older Faller in Malaysia

Cited by 2 publications

References 16 publications

Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study

Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study

Applying the UTAUT2 Model to Smart Eyeglasses to Detect and Prevent Falls Among Older Adults and Examination of Associations With Fall-Related Functional Physical Capacities: Survey Study (Preprint)

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