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
来源
SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS II, PTS 1 AND 2 | 2014年 / 475-476卷
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
  • [11] A Study on Real-Time Fall Detection Systems Using Acceleration Sensor and Tilt Sensor
    Kim, Seong-Hyun
    Kim, Dong-Wook
    SENSOR LETTERS, 2012, 10 (5-6) : 1302 - 1307
  • [12] Real Time Obstacle Detection Method Based on Lidar and Wireless Sensor
    Zhang, Junyou
    Han, Jian
    Wang, Shufeng
    Liao, Yaping
    Li, Pengfei
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 5951 - 5955
  • [13] Fall Detection on Ambient Assisted Living using a Wireless Sensor Network
    Pereira, Antonio
    Felisberto, Filipe
    Maduro, Luis
    Felgueiras, Miguel
    ADCAIJ-ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, 2012, 1 (01): : 63 - 72
  • [14] A comparison of public datasets for acceleration-based fall detection
    Igual, Raul
    Medrano, Carlos
    Plaza, Inmaculada
    MEDICAL ENGINEERING & PHYSICS, 2015, 37 (09) : 870 - 878
  • [15] Mining Acceleration Data for Smartphone-based Fall Detection
    Piparunaekaporn, Luepol
    Wichinawakul, Puritud
    Kamolsantiroj, Suwatchai
    2018 10TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SMART TECHNOLOGY (KST 2018) - CYBERNETICS IN THE NEXT DECADES, 2018, : 74 - 79
  • [16] Patch-Transformer Network: A Wearable-Sensor-Based Fall Detection Method
    Wang, Shaobing
    Wu, Jiang
    SENSORS, 2023, 23 (14)
  • [17] IR-UWB Sensor Based Fall Detection Method Using CNN Algorithm
    Han, Taekjin
    Kang, Wonho
    Choi, Gyunghyun
    SENSORS, 2020, 20 (20) : 1 - 23
  • [18] Sensor-based fall detection systems: a review
    Nooruddin, Sheikh
    Islam, Md Milon
    Sharna, Falguni Ahmed
    Alhetari, Husam
    Kabir, Muhammad Nomani
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 13 (5) : 2735 - 2751
  • [19] 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
  • [20] 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