Fall detection monitoring systems: a comprehensive review
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
http://link.springer.com/article/10.1007/s12652-017-0592-3/fulltext.html
Reference96 articles.
1. Alwan M, Rajendran PJ, Kell S, Mack D, Dalal S, Wolfe M, Felder R (2006) A smart and passive floor-vibration based fall detector for elderly. In: Information and communication technologies, 2006. ICTTA’06. 2nd, IEEE, vol 1, pp 1003–1007
2. Anania G, Tognetti A, Carbonaro N, Tesconi M, Cutolo F, Zupone G, De Rossi D (2008) Development of a novel algorithm for human fall detection using wearable sensors. In: Sensors, 2008 IEEE, IEEE, pp 1336–1339
3. Andò B, Baglio S, Lombardo CO, Marletta V (2015) An event polarized paradigm for adl detection in aal context. IEEE Trans Instrum Meas 64(7):1814–1825
4. Andò B, Baglio S, Lombardo CO, Marletta V (2016) A multisensor data-fusion approach for adl and fall classification. IEEE Trans Instrum Meas 65(9):1960–1967
5. Aslan M, Sengur A, Xiao Y, Wang H, Ince MC, Ma X (2015) Shape feature encoding via fisher vector for efficient fall detection in depth-videos. Appl Soft Comput 37:1023–1028
Cited by 97 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. AI-powered trustable and explainable fall detection system using transfer learning;Image and Vision Computing;2024-09
2. Cross-dataset evaluation of wearable fall detection systems using data from real falls and long-term monitoring of daily life;Measurement;2024-08
3. Enhancing Detection of Falls and Bed-Falls Using a Depth Sensor and Convolutional Neural Network;IEEE Sensors Journal;2024-07-15
4. Implementing a Robust Method for Detecting Human Actions in Health Monitoring by Employing Sensors on Mobile Internet of Things Devices and Utilizing a One-Dimensional Convolutional Neural Network;Journal of Technology in Behavioral Science;2024-06-14
5. Fall Detection by Ambient Sensors on Years-Long Simulation Data;2024 International Conference on Activity and Behavior Computing (ABC);2024-05-29
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3