The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
An enhanced fall detection system for elderly person monitoring using consumer home networks
Abstract
Various fall-detection solutions have been previously proposed to create a reliable surveillance system for elderly people with high requirements on accuracy, sensitivity and specificity. In this paper, an enhanced fall detection system is proposed for elderly person monitoring that is based on smart sensors worn on the body and operating through consumer home networks. With treble thresholds, accidental falls can be detected in the home healthcare environment. By utilizing information gathered from an accelerometer, cardiotachometer and smart sensors, the impacts of falls can be logged and distinguished from normal daily activities. The proposed system has been deployed in a prototype system as detailed in this paper. From a test group of 30 healthy participants, it was found that the proposed fall detection system can achieve a high detection accuracy of 97.5%, while the sensitivity and specificity are 96.8% and 98.1% respectively. Therefore, this system can reliably be developed and deployed into a consumer product for use as an elderly person monitoring device with high accuracy and a low false positive rate.
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Cites
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Amir, O., Rand, D. G., & Gal, Y. K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031461 · Cited by 364
Cited by
Developing residential wireless sensor networks for ECG healthcare monitoring
Dey, N., Ashour, A. S., Shi, F., Fong, S. J., & Sherratt, R. S. (2017) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2017.015063 · Cited by 283
Self-citationMobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges
El-Rashidy, N., El-Sappagh, S., Islam, S., M. El-Bakry, H., & Abdelrazek, S. (2021) · Diagnostics · doi:10.3390/diagnostics11040607 · Cited by 258
Application of data fusion techniques and technologies for wearable health monitoring
King, R. C., Villeneuve, E., White, R. J., Sherratt, R. S., Holderbaum, W., & Harwin, W. S. (2017) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2016.12.011 · Cited by 182
“Wang et al. [74] described a three-fold threshold system that combine a trunk worn accelerometer and cardiotachometer to detect falls.”
Zobi, M., Bolzani, L., Tabii, Y., & Oulad Haj Thami, R. (2025) · Sensors · doi:10.3390/s25216783 · Cited by 6
Metadata
- Authors
- Wang, J., Zhang, Z., Li, B., Lee, S., & Sherratt, R. S.
- Venue
- IEEE Transactions on Consumer Electronics
- Published
- 2014-02
- Volume
- 60
- Issue
- 1
- Pages
- 23-29
- ISSN
- 0098-3063 (ISSN-L)
- OpenAlex
- W2102699948
- Cited by
- 277
- References
- 1
- FWCI
- 18.10
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, J., Zhang, Z., Li, B., Lee, S., & Sherratt, R. S. (2014). An enhanced fall detection system for elderly person monitoring using consumer home networks. IEEE Transactions on Consumer Electronics. https://doi.org/10.1109/tce.2014.6780921
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