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A Review on Fall Detection in Smart Home for Elderly and Disabled People

Tsepo Constantinus Kolobe, Chungling Tu, Pius Adewale Owolawi

2022Journal of Advanced Computational Intelligence and Intelligent Informatics17 citationsDOIOpen Access PDF

Abstract

Falling is a major challenge faced by elderly and disabled people who live alone. They therefore need reliable surveillance so they can be assisted in the event of a fall. An effective fall detection system is needed to provide good care to such people as it will allow for communication with caregivers. Such a system will not only reduce the medical costs related to falls but also lower the death rate among elderly and disabled people due to falls. This review paper presents a survey of different fall detection techniques and algorithms used for fall detection. Various fall detection approaches including wearable, vision, ambience, and multimodal systems are analyzed and compared and recommendations are presented.

Topics & Concepts

Falling (accident)Computer scienceWearable computerElderly peopleEvent (particle physics)Fall preventionDisabled peopleComputer securityMedical emergencyPhysical medicine and rehabilitationMedicineGerontologyPoison controlEmbedded systemHuman factors and ergonomicsPsychiatryQuantum mechanicsCerebral palsyPhysicsContext-Aware Activity Recognition SystemsIoT and Edge/Fog ComputingIoT-based Smart Home Systems
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