A Reliable Fall Detection System Based on Wearable Sensor and Signal Magnitude Area for Elderly Residents

Chen, Guan-Chun; Huang, Chih-Ning; Chiang, Chifa; Hsieh, Chia-Juei; Chan, Chia-Tai

doi:10.1007/978-3-642-13778-5_39

Cited by 38 publications

(25 citation statements)

References 4 publications

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“…orientations of sensor, we set x-axis as the fr axis as the vertical side, z-axis as the s acceleration vector is the vector caused by when the body hits the ground, as shown in F This proposed fall characteristics collect be triggered through fall events. In this pap detection algorithm proposed by our labora detect fall events [7]. There are three thresho being used in the fall detection algorithm.…”

Section: Methodsmentioning

confidence: 99%

Notice of Retraction: Development of Fall Characteristics Collection System for Fall Prevention Strategies

Hsieh¹,

Chiang²,

Huang³

et al. 2011

2011 5th International Conference on Bioinformatics and Biomedical Engineering

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Falls often cause serious injury and health threats for elderly people. It is also the major obstacle to independent living for frail and elderly people. Many researchers try to establish an efficient fall prevention strategies for elderly people by collecting a lot of fall characteristics. However, it is difficult to obtain these characteristics simply from the questionnaires of elderly people. Since they may forget or misremember their falling scenario. In this work, we propose a fall characteristics collection system for designing fall prevention strategies. A waist-mounted tri-axial accelerometer is used to capture the movement data of the human body when elderly people fall. Then, the proposed algorithm uses the variations of angle between acceleration vector and three axes to determine the fall characteristics which include falling directions and impact parts. Experimental results demonstrate effectiveness of the proposed scheme. The system is not only cost effective but also portable that fulfills the requirements of fall characteristics data collection.

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Section: Methodsmentioning

confidence: 99%

Notice of Retraction: Development of Fall Characteristics Collection System for Fall Prevention Strategies

Hsieh¹,

Chiang²,

Huang³

et al. 2011

2011 5th International Conference on Bioinformatics and Biomedical Engineering

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“…One-third of home-dwelling people aged 65 or older and two-thirds of those in a residential care fall one or more times each year [2,3]. Injuries sustained from falls include bruises, lacerations, joint dislocations, bone fractures and head trauma.…”

Section: Introductionmentioning

confidence: 99%

“…Most experiments in automatic fall detection involve either only simulated falls and ADLs performed by young subjects [3,[22][23][24]or combined with ADLs performed by elderlies [14,17,18,20,21]. Although high accuracy has been achieved in several studies, the algorithms were validated on a limited number of fall scenarios and subjects.…”

Section: Introductionmentioning

confidence: 99%

“…Several approaches to automatic fall detection include vision [10][11][12], sound [13], gyroscope [14], mobile phone [15], accelerometer(s) [3,[16][17][18][19][20][21] [3,18,20,22,23], and the velocity of the body movements [28,29]. In many studies [14,16,[22][23][24], the angle between the tilt body and the gravitational axis was used to detect the direction of falls.…”

Section: Introductionmentioning

confidence: 99%

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Toward real-time accurate fall/fall recovery detection system by incorporating activity information

Pannurat

Theekakul

Thiemjarus

et al. 2012

Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics

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This study presents a detailed summary of automatic fall detection system based on wearable sensor(s) and a real-time fall detection system prototype developed based on Java Expert System Shell (JESS), featuring the fall, fall recovery, fall direction and activity status before/after fall.Through the rule sets in the knowledge base, we illustrate how the activity information can be used to indicate the fall recovery and fall direction, as well as enhancing the accuracy of fall detection. The system has been validated against 13 types of falls and 12 ADLs acquired from 12 subjects.

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“…One way is to integrate automated sensors, e.g. camera-based fall detection [3], microphone arrays [5] or wearable sensors [1], another way is working on the operating procedures when a fall is detected. This paper focuses on the fall handling procedure during which patients will be provided with appropriate help through a call center in the province of Limburg, Belgium.…”

Section: Introductionmentioning

confidence: 99%

Interdisciplinary Design of a Pervasive Fall Handling System

Bergh¹,

Luyten²,

Aendekerk³

et al. 2014

Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare

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Falls among elderly are an important concern as they impact the capability to live independently. Falls do not only have a negative impact on one's physical well-being, an increased risk of falling also has an important impact on one's psychological well-being. A context-aware fall handling system can mitigate many of the problems of falls by facilitating timely and appropriate handling of falls.In this paper, we present the results of an early exploration of using context as part of fall detection and resolution services in Flanders, Belgium. We put specific emphasis on the role of diverse disciplines during the process and reflect on their influence on the outcomes. We believe that these reflections could be more generally applicable for interdisciplinary research projects.

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A Reliable Fall Detection System Based on Wearable Sensor and Signal Magnitude Area for Elderly Residents

Cited by 38 publications

References 4 publications

Notice of Retraction: Development of Fall Characteristics Collection System for Fall Prevention Strategies

Notice of Retraction: Development of Fall Characteristics Collection System for Fall Prevention Strategies

Toward real-time accurate fall/fall recovery detection system by incorporating activity information

Interdisciplinary Design of a Pervasive Fall Handling System

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