The DOI matches its Crossref record.
The design of a practical and reliable fall detector for community and institutional telecare
Abstract
Falls are one of the greatest obstacles to independent living for frail and elderly people. Their early detection is an important step in providing people with the reassurance and confidence necessary to maintain an active lifestyle. We have investigated a worn fall detector linked to a community alarm system. A worn device is the only one which is satisfactory, provided that it generates few false alarms. The fall detector we have developed is the size of a small radio pager. It uses a two-stage detection process which senses shock and the orientation of the wearer. A fall is detected within 20 s and triggers a radio signal to a community alarm system. Tests were devised using a jointed mannequin to simulate five modes of falling to understand the effects of impact at different parts of the body. This allowed us to select the appropriate trigger threshold and wearing positions for the sensor. Prototypes were evaluated with 20 people to observe false alarms. The final design allowed reliable detection in 180 different falling scenarios.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring
Yang, C.-C., & Hsu, Y.-L. (2010) · Sensors · doi:10.3390/s100807772 · Cited by 1,058
Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls
Bagalà, F., Becker, C., Cappello, A., Chiari, L., Aminian, K., Hausdorff, J. M., Zijlstra, W., & Klenk, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037062 · Cited by 464
Fall Detection Devices and Their Use With Older Adults: A Systematic Review
Chaudhuri, S., Thompson, H., & Demiris, G. (2014) · Journal of Geriatric Physical Therapy · doi:10.1519/jpt.0b013e3182abe779 · Cited by 215
Mihailidis, A., Carmichael, B., & Boger, J. (2004) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2004.834386 · Cited by 208
Real-time elderly activity monitoring system based on a tri-axial accelerometer
Kang, D. W., Choi, J. S., Lee, J. W., Chung, S. C., Park, S. J., & Tack, G. R. (2010) · Disability and Rehabilitation: Assistive Technology · doi:10.3109/17483101003718112 · Cited by 43
Metadata
- Authors
- Doughty, K., Lewis, R., & Mcintosh, A.
- Venue
- Journal of Telemedicine and Telecare
- Publisher
- SAGE Publications
- Published
- 2000-02
- Volume
- 6
- Issue
- 1_suppl
- Pages
- 150-154
- ISSN
- 1357-633X (ISSN-L)
- 1758-1109
- OpenAlex
- W1976789043
- Cited by
- 185
- References
- 0
- FWCI
- 1.32
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The design of a practical and reliable fall detector for community and institutional telecare. https://app.cochat.ai/papers/10.1258/1357633001934483
- The paper
- Doughty, K., Lewis, R., & Mcintosh, A. (2000). The design of a practical and reliable fall detector for community and institutional telecare. Journal of Telemedicine and Telecare. https://doi.org/10.1258/1357633001934483
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.