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View all- Luo JBai RHe SShin K(2022)Pervasive Pose Estimation for Fall DetectionACM Transactions on Computing for Healthcare10.1145/34780273:3(1-23)Online publication date: 7-Apr-2022
Analysis of a Public Repository for the Study of Automatic Fall Detection Algorithms
Article No.: 7, Pages 1 - 10
Abstract
The use of publicly available repositories containing movement traces of real or experimental subjects is a key aspect to define an evaluation framework that allows a systematic assessment of wearable fall detection systems. This papers presents a detailed analysis of a public dataset of traces which employed five sensing points to characterize the user's mobility during the execution of ADLs (Activities of Daily Living) and emulated falls. The analysis is aimed at analysing two main factors: the importance of the election of the position of the sensor and the possible impact of the user's personal features on the statistical characterization of the movements. Results reveal the importance of the nature of the ADL for the effectiveness of the discrimination of the falls.
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Index Terms
- Analysis of a Public Repository for the Study of Automatic Fall Detection Algorithms
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Published In
September 2018
148 pages
ISBN:9781450364874
DOI:10.1145/3266157
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In-Cooperation
- Fraunhofer IGD: Fraunhofer Institute for Computer Graphics Research IGD
- Rostock: University of Rostock
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 20 September 2018
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- Research-article
- Research
- Refereed limited
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- This work was supported by Universidad de Málaga, Campus de Excelencia Internacional Andalucia Tech
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iWOAR '18
iWOAR '18: 5th international Workshop on Sensor-based Activity Recognition and Interaction
September 20 - 21, 2018
Berlin, Germany
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iWOAR '18 Paper Acceptance Rate 15 of 28 submissions, 54%;
Overall Acceptance Rate 46 of 73 submissions, 63%
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Cited By
View all- Luo JBai RHe SShin K(2022)Pervasive Pose Estimation for Fall DetectionACM Transactions on Computing for Healthcare10.1145/34780273:3(1-23)Online publication date: 7-Apr-2022
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