poster

Fall and emergency detection with mobile phones

Authors:

Hamed Ketabdar,

Tim PolzehlAuthors Info & Claims

Assets '09: Proceedings of the 11th international ACM SIGACCESS conference on Computers and accessibility

Pages 241 - 242

https://doi.org/10.1145/1639642.1639695

Published: 25 October 2009 Publication History

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Abstract

In this demo, we present an application for mobile phones which can monitor physical activities of users and detect unexpected emergency situations such as a sudden fall or accident. Upon detection of such an event, the mobile phone can inform a designated center (by automatically calling or sending message) about the incident and its location. This can facilitate and speed up recovery and help process especially if the user is alone or the accident has happened in a deserted place. Such an application can be particularly useful for elderly people or people with physical and movement disabilities. The application operates based on analysis of user movements using data provided by accelerometers integrated in mobile phones.

References

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Kern, N., Schiele, B., Schmidt, A. Multi-sensor Activity Context Detection for Wearable Computing, Lecture Notes in Computer Science, Volume 2875/2003, Springer Berlin/Heidelberg, 2003.

Google Scholar

[2]

Mathie, M. J., Coster, A. C. F., Lovell, N. H., and Celler, B. G., Detection of daily physical activities using a triaxial accelerometer, Medical and Biological Engineering and Computing, Vol. 41, No. 3, Springer Berlin / Heidelberg, 2003.

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McLachlan, G.J. and Basford, K.E. "Mixture Models: Inference and Applications to Clustering", Marcel Dekker (1988).

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Cited By

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Wang YLi MKim YLee BDanilovich MLazar AConroy DKacorri HChoe E(2024)Redefining Activity Tracking Through Older Adults' Reflections on Meaningful ActivitiesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642170(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642170
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
https://dl.acm.org/doi/10.1145/3478027
Vargemidis DGerling KSpiel KAbeele VGeurts L(2020)Wearable Physical Activity Tracking Systems for Older Adults—A Systematic ReviewACM Transactions on Computing for Healthcare10.1145/34025231:4(1-37)Online publication date: 30-Sep-2020
https://dl.acm.org/doi/10.1145/3402523
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Index Terms

Fall and emergency detection with mobile phones
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems

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Information & Contributors

Information

Published In

Assets '09: Proceedings of the 11th international ACM SIGACCESS conference on Computers and accessibility

October 2009

290 pages

ISBN:9781605585581

DOI:10.1145/1639642

General Chair:
Shari Trewin
IBM T. J. Watson Research Center, USA
,
Program Chair:
Kathleen F. McCoy
University of Delaware, USA

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 October 2009

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Poster

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ASSETS09

Sponsor:

SIGACCESS

ASSETS09: The 11th International ACM SIGACCESS Conference on Computers and Accessibility

October 25 - 28, 2009

Pennsylvania, Pittsburgh, USA

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Overall Acceptance Rate 436 of 1,556 submissions, 28%

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Cited By

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Wang YLi MKim YLee BDanilovich MLazar AConroy DKacorri HChoe E(2024)Redefining Activity Tracking Through Older Adults' Reflections on Meaningful ActivitiesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642170(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642170
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
https://dl.acm.org/doi/10.1145/3478027
Vargemidis DGerling KSpiel KAbeele VGeurts L(2020)Wearable Physical Activity Tracking Systems for Older Adults—A Systematic ReviewACM Transactions on Computing for Healthcare10.1145/34025231:4(1-37)Online publication date: 30-Sep-2020
https://dl.acm.org/doi/10.1145/3402523
Xie BLi JZhao X(2019)Research on Damage Detection of a 3D Steel Frame Model Using SmartphonesSensors10.3390/s1903074519:3(745)Online publication date: 12-Feb-2019
https://doi.org/10.3390/s19030745
Wang NRi KLiu HZhao X(2018)Notice of Removal: Structural Displacement Monitoring Using Smartphone Camera and Digital Image CorrelationIEEE Sensors Journal10.1109/JSEN.2018.282813918:11(4664-4672)Online publication date: 1-Jun-2018
https://doi.org/10.1109/JSEN.2018.2828139
Han RZhao XYu YGuan QHu WLi M(2016)A Cyber-Physical System for Girder Hoisting Monitoring Based on SmartphonesSensors10.3390/s1607104816:7(1048)Online publication date: 7-Jul-2016
https://doi.org/10.3390/s16071048
Merrouche IMakhlouf ASaadia NRamdane-Cherif A(2016)Overview and systems of assistance to older people2016 4th International Conference on Control Engineering & Information Technology (CEIT)10.1109/CEIT.2016.7929050(1-6)Online publication date: Dec-2016
https://doi.org/10.1109/CEIT.2016.7929050
Zhao XHan RDing YYu YGuan QHu WLi MOu J(2015)Portable and convenient cable force measurement using smartphoneJournal of Civil Structural Health Monitoring10.1007/s13349-015-0132-95:4(481-491)Online publication date: 9-Aug-2015
https://doi.org/10.1007/s13349-015-0132-9
Koshmak GLinden MLoutfi A(2014)Dynamic Bayesian Networks for Context-Aware Fall Risk AssessmentSensors10.3390/s14050933014:5(9330-9348)Online publication date: 23-May-2014
https://doi.org/10.3390/s140509330
Dhillon JWunsche BLutteroth C(2013)Accessible telehealth — Leveraging consumer-level technologies and social networking functionalities for senior care2013 6th International Conference on Human System Interactions (HSI)10.1109/HSI.2013.6577864(451-458)Online publication date: Jun-2013
https://doi.org/10.1109/HSI.2013.6577864
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