2022
DOI: 10.1016/j.buildenv.2022.109533
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Detecting stressful older adults-environment interactions to improve neighbourhood mobility: A multimodal physiological sensing, machine learning, and risk hotspot analysis-based approach

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Cited by 8 publications
(2 citation statements)
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“…The resilience and cognitive readiness of emergency workers can benefit from increasing research interest in wearable sensors for biological signal monitoring and analysis. The availability of inexpensive and small sensors for real-time monitoring and connectivity technologies has enabled recent applications such as healthcare [ 9 , 10 , 11 ], human–machine interfaces [ 12 ] and monitoring of workers [ 13 ] or elderly people [ 14 ].…”
Section: Introductionmentioning
confidence: 99%
“…The resilience and cognitive readiness of emergency workers can benefit from increasing research interest in wearable sensors for biological signal monitoring and analysis. The availability of inexpensive and small sensors for real-time monitoring and connectivity technologies has enabled recent applications such as healthcare [ 9 , 10 , 11 ], human–machine interfaces [ 12 ] and monitoring of workers [ 13 ] or elderly people [ 14 ].…”
Section: Introductionmentioning
confidence: 99%
“…Recent advances in wearable electronics have led to the development of fully integrated and scalable wireless devices for monitoring extraneous and continuous stress in everyday life. [17][18][19] However, recent studies still rely on rigid, bulky sensor modules affixed to the body with straps and belts tightly, which is not yet completely free from motion artifacts during daily activities. Furthermore, most stress monitoring has been conducted indoors and the effort that directly investigates physiologic stress to hard labor in hot environments is restricted to field studies.…”
mentioning
confidence: 99%