Sensor-based fall detection systems: a review
Author:
Funder
Universiti Malaysia Pahang
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-021-03248-z.pdf
Reference85 articles.
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2. Bagalà F, Becker C, Cappello A et al (2012) Evaluation of accelerometer-based fall detection algorithms on real-world falls. PLoS ONE 7:e37062. https://doi.org/10.1371/journal.pone.0037062
3. Bergen G, Stevens MR, Burns ER (2016) Falls and fall injuries among adults aged ≥65 years—United States, 2014. MMWR Morb Mortal Wkly Rep 65:993–998. https://doi.org/10.15585/mmwr.mm6537a2
4. Bet P, Castro PC, Ponti MA (2019) Fall detection and fall risk assessment in older person using wearable sensors: a systematic review. Int J Med Inform 130:103946. https://doi.org/10.1016/j.ijmedinf.2019.08.006
5. Bin KS, Park J-H, Kwon C et al (2019) An energy-efficient algorithm for classification of fall types using a wearable sensor. IEEE Access 7:31321–31329. https://doi.org/10.1109/ACCESS.2019.2902718
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