The fall detection method based on the wireless acceleration sensor

被引:0
|
作者
Liang, Zhengyou [1 ]
Xu, Yalong [1 ]
Li, Zheng [2 ]
机构
[1] Guangxi Univ, Coll Comp & Elect Informat, Nanning 530004, Peoples R China
[2] Xidian Univ, Sch Phys & Optoelectron Engn, Xian 710126, Peoples R China
关键词
fall detection; wireless sensor; three axis acceleration; pattern recognition;
D O I
10.4028/www.scientific.net/AMM.475-476.136
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
To judge whether the alone elderly fall or not is an important need in the elderly health supervision. This paper puts forward a method based on three axis acceleration data and pattern recognition has been presented to judge the situation of falling for old men. The method was based on an acceleration transducer named MMA7260Q. Due to the characteristic that the three-axis signal divers in a huge area during the progress of old men falling, it combined the peak value of acceleration and acceleration energy curve to proceed three axis acceleration data for detecting the falling, it could avoid outputting errors due to the changing of angle of old men. According to the result of the experiment, the accuracy rate of the method of detection proposed in the report could run up to 93 percent.
引用
收藏
页码:136 / +
页数:2
相关论文
共 50 条
  • [41] Kernel Principal Subspace based Outlier Detection Method in Wireless Sensor Networks
    Ghorbel, Oussama
    Abid, Mohamed
    Snoussi, Hichem
    2014 28TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (WAINA), 2014, : 737 - 742
  • [42] Coverage hole detection method of wireless sensor network based on clustering algorithm
    Wang, Feifei
    Hu, Haifeng
    MEASUREMENT, 2021, 179
  • [43] Wireless Multimedia Sensor Network Based Subway Tunnel Crack Detection Method
    Shen, Bo
    Zhang, Wen-Yu
    Qi, Da-Peng
    Wu, Xiao-Yang
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2015,
  • [44] Security Detection Method for Clustering Wireless Sensor Networks Based on Markov Chain
    Dong, Na
    Chen, Ze
    Liu, Weina
    Hou, Botao
    Engineering Intelligent Systems, 2022, 30 (01): : 55 - 65
  • [45] A Participation Degree-Based Fault Detection Method for Wireless Sensor Networks
    Zhang, Wei
    Zhang, Gongxuan
    Chen, Xiaohui
    Zhou, Xiumin
    Liu, Yueqi
    Zhou, Junlong
    SENSORS, 2019, 19 (07)
  • [46] An Isolation Principle Based Distributed Anomaly Detection Method in Wireless Sensor Networks
    Zhi-Guo Ding
    Da-Jun Du
    Min-Rui Fei
    International Journal of Automation and Computing, 2015, 12 (04) : 402 - 412
  • [47] Mobile Sensor-Based Fall Detection Framework
    Islam, Md Saiful
    Shahriar, Hossain
    Sneha, Sweta
    Zhang, Chi
    Ahamed, Sheikh
    2020 IEEE 44TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2020), 2020, : 693 - 698
  • [48] Sensor-based fall detection systems: a review
    Sheikh Nooruddin
    Md. Milon Islam
    Falguni Ahmed Sharna
    Husam Alhetari
    Muhammad Nomani Kabir
    Journal of Ambient Intelligence and Humanized Computing, 2022, 13 : 2735 - 2751
  • [49] Accelerometer-based Sensor Network for Fall Detection
    Le, Thinh M.
    Pan, R.
    2009 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS 2009), 2009, : 240 - 243
  • [50] A survey of fall detection model based on wearable sensor
    Li, Congcong
    Teng, Guifa
    Zhang, Yuting
    2019 12TH INTERNATIONAL CONFERENCE ON HUMAN SYSTEM INTERACTION (HSI), 2019, : 181 - 186