A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials-Reference-Cited by-同舟云学术

A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials

Published:2016-04-22 Issue:1 Volume:55 Page:45-55
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med Biol Eng Comput

Author:

Aziz Omar,Musngi Magnus,Park Edward J.,Mori Greg,Robinovitch Stephen N.

Funder

Canadian Institutes of Health Research

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11517-016-1504-y.pdf

Reference33 articles.

1. Albert MV, Kording K, Herrmann M, Jayaraman A (2012) Fall classification by machine learning using mobile phones. PLoS One 7(5):e36556

2. Arnold CM, Faulkner RA (2007) The history of falls and the association of the timed up and go test to falls and near-falls in older adults with hip osteoarthritis. BMC Geriatr 7:17

3. Aziz O, Park EJ, Mori G, Robinovitch SN (2012) Distinguishing near-falls from daily activities with wearable accelerometers and gyroscopes using support vector machines. In: Conference proceedings of IEEE engineering in medicine biology society 2012, pp 5837–5840

4. Aziz O, Park EJ, Mori G, Robinovitch SN (2014) Distinguishing the causes of falls in humans using an array of wearable tri-axial accelerometers. Gait Posture 39(1):506–512

5. Aziz O, Robinovitch SN (2011) An analysis of the accuracy of wearable sensors for classifying the causes of falls in humans. IEEE Trans Neural Syst Rehabil Eng 19(6):670–676

Cited by 148 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Interactions during falls with environmental objects: evidence from real-life falls in long-term care captured on video;BMC Geriatrics;2024-09-02

2. Acquisition of Data on Kinematic Responses to Unpredictable Gait Perturbations: Collection and Quality Assurance of Data for Use in Machine Learning Algorithms for (Near-)Fall Detection;Sensors;2024-08-20

3. Cross-dataset evaluation of wearable fall detection systems using data from real falls and long-term monitoring of daily life;Measurement;2024-08

4. GoldAid: An Integrated Safety System Leveraging IoT and Advanced Algorithms for Rapid Medical Aid in the Golden Hour;IEEE Sensors Journal;2024-08-01

5. The Effect of Sensor Feature Inputs on Joint Angle Prediction across Simple Movements;Sensors;2024-06-05