A Review on Fall Detection in Smart Home for Elderly and Disabled People
Tsepo Constantinus Kolobe, Chungling Tu, and Pius Adewale Owolawi
Department of Computer Systems Engineering, Tshwane University of Technology
2 Aubrey Matlakala Street, Soshanguve, Pretoria 0001, South Africa
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.
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