Introduction: Monitoring systems at home are critical in the event of a fall, and can range from standalone fall detection devices to activity recognition devices that aim to identify behaviors in which the user may be at risk of falling, or to detect falls in real-time and alert emergency personnel.Areas covered: This review analyzes the current literature concerning the different devices available for home fall detection.Expert opinion: Included studies highlight how fall detection at home is an important challenge both from a clinical-assistance point of view and from a technical-bioengineering point of view. There are wearable, non-wearable and hybrid systems that aim to detect falls that occur in the patient's home. In the near future, a greater probability of predicting falls is expected thanks to an improvement in technologies together with the prediction ability of machine learning algorithms. Fall prevention must involve the clinician with a person-centered approach, low cost and minimally invasive technologies able to evaluate the movement of patients and machine learning algorithms able to make an accurate prediction of the fall event.

Ambient assisted living systems for falls monitoring at home / Orejel Bustos, Amaranta Soledad; Tramontano, Marco; Morone, Giovanni; Ciancarelli, Irene; Panza, Giuseppe; Minnetti, Andrea; Picelli, Alessandro; Smania, Nicola; Iosa, Marco; Vannozzi, Giuseppe. - In: EXPERT REVIEW OF MEDICAL DEVICES. - ISSN 1743-4440. - 20:10(2023), pp. 821-828. [10.1080/17434440.2023.2245320]

Ambient assisted living systems for falls monitoring at home

Iosa, Marco;
2023

Abstract

Introduction: Monitoring systems at home are critical in the event of a fall, and can range from standalone fall detection devices to activity recognition devices that aim to identify behaviors in which the user may be at risk of falling, or to detect falls in real-time and alert emergency personnel.Areas covered: This review analyzes the current literature concerning the different devices available for home fall detection.Expert opinion: Included studies highlight how fall detection at home is an important challenge both from a clinical-assistance point of view and from a technical-bioengineering point of view. There are wearable, non-wearable and hybrid systems that aim to detect falls that occur in the patient's home. In the near future, a greater probability of predicting falls is expected thanks to an improvement in technologies together with the prediction ability of machine learning algorithms. Fall prevention must involve the clinician with a person-centered approach, low cost and minimally invasive technologies able to evaluate the movement of patients and machine learning algorithms able to make an accurate prediction of the fall event.
2023
Fall prevention; disability; home devices; neurorehabilitation; telemedicine; telerehabilitation; wearable devices
01 Pubblicazione su rivista::01g Articolo di rassegna (Review)
Ambient assisted living systems for falls monitoring at home / Orejel Bustos, Amaranta Soledad; Tramontano, Marco; Morone, Giovanni; Ciancarelli, Irene; Panza, Giuseppe; Minnetti, Andrea; Picelli, Alessandro; Smania, Nicola; Iosa, Marco; Vannozzi, Giuseppe. - In: EXPERT REVIEW OF MEDICAL DEVICES. - ISSN 1743-4440. - 20:10(2023), pp. 821-828. [10.1080/17434440.2023.2245320]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1691251
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