Journal ArticleDOI
Accelerometer-based human fall detection using Sparrow Search Algorithm and Back Propagation neural network
Tianhu Wang,Baoqiang Wang,Yunzhe Shen,Yang Zhao,Wenjie Li,Keming Yao,Xiaojie Liu,Yi Guang Luo +7 more
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TLDR
In this article , an optimized BP neural network fall prediction model based on the Sparrow Search Algorithm (SSA) is established to reduce the injury caused by the fall and solve the problems of low efficiency and low accuracy of traditional fall prediction methods.About:
This article is published in Measurement.The article was published on 2022-10-01. It has received 2 citations till now. The article focuses on the topics: Accelerometer & Acceleration.read more
Citations
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Journal ArticleDOI
An improved neural network model for battery smarter state-of-charge estimation of energy-transportation system
Proceedings ArticleDOI
A Hybrid Deep Learning Model for Human Activity Recognition and Fall Detection for the Elderly
TL;DR: Li et al. as mentioned in this paper proposed a deep learning model that takes advantage of the affordability and latest technological advancements of mobile sensors to identify certain physical activities and promptly send an alert in the event of a fall.
References
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Journal ArticleDOI
Challenges, issues and trends in fall detection systems
TL;DR: An extensive literature review of fall detection systems is presented, including comparisons among various kinds of studies, to serve as a reference for both clinicians and biomedical engineers planning or conducting field investigations.
Proceedings ArticleDOI
A Smart and Passive Floor-Vibration Based Fall Detector for Elderly
Majd Alwan,Prabhu Jude Rajendran,S. Kell,David C. Mack,Siddharth Dalal,M. Wolfe,Robin A. Felder +6 more
TL;DR: The working principle and the design of a floor vibration-based fall detector that is completely passive and unobtrusive to the resident is described and the results showed 100% fall detection rate with minimum potential for false alarms.
Journal ArticleDOI
Human fall detection on embedded platform using depth maps and wireless accelerometer
Bogdan Kwolek,Michal Kepski +1 more
TL;DR: This paper presents how to design and implement a low-cost system for reliable fall detection with very low false alarm ratio, a 365/7/24 embedded system permitting unobtrusive fall detection as well as preserving privacy of the user.
Journal ArticleDOI
Traumatic Brain Injuries Evaluated in U.S. Emergency Departments, 1992‐1994
TL;DR: This study underscores the ongoing need for effective surveillance of all types of TBI and evaluation of prevention strategies targeting high-risk individuals and serves as a basis for comparison of incidence rates over time and a tool with which to measure the efficacy of future interventions.
Journal ArticleDOI
SmartFall: A Smartwatch-Based Fall Detection System Using Deep Learning.
TL;DR: A Deep Learning model for fall detection generally outperforms more traditional models across the three datasets and exhibits a better ability to generalize to new users when predicting falls, an important quality of any model that is to be successful in the real world.