Smart Seismic Sensing for Indoor Fall Detection, Location, and Notification

被引:79
作者
Clemente, Jose [1 ]
Li, Fangyu [1 ]
Valero, Maria [1 ]
Song, WenZhan [1 ]
机构
[1] Univ Georgia, Ctr Cyber Phys Syst, Athens, GA 30602 USA
关键词
Fall detection; seismic sensing; person identification; real-time; in-network system; LOCALIZATION;
D O I
10.1109/JBHI.2019.2907498
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a novel real-time smart system performing fall detection, location, and notification based on floor vibration data produced by fall downs. Only using floor vibration as the recognition source, the system incorporates a person identification through vibration produced by footsteps to inform who is the fallen person. Our approach operates in a real-time style, which means the system recognizes a fall immediately and can identify a person with only one or two footsteps. A collaborative in-network location method is used in which sensors collaborate with each other to recognize the person walking, and more importantly, detect if the person falls down at any moment. We also introduce a voting system among sensor nodes to improve person identification accuracy. Our system is robust to identify fall downs from other possible similar events, such as jumps, door close, and objects fall down. Such a smart system can also be connected to smart commercial devices for emergency notifications. Our approach represents an advance in smart technology for elder people who live alone. Evaluation of the system shows that it is able to detect fall downs with an acceptance rate of 95.14 & 0025; (distinguishing from other possible events), and it identifies people with one or two steps in a 97.22 & 0025; (higher accuracy than other methods that use more footsteps). The fall down location error is smaller than 0.27 m, which is acceptable compared with the height of a person.
引用
收藏
页码:524 / 532
页数:9
相关论文
共 27 条
  • [1] Alwan M., 2006, INF COMMUN TECHNOL, P1003, DOI DOI 10.1109/ICTTA.2006.1684511
  • [2] UREDT: Unsupervised Learning Based Real-Time Footfall Event Detection Technique in Seismic Signal
    Anchal, Sahil
    Mukhopadhyay, Bodhibrata
    Kar, Subrat
    [J]. IEEE SENSORS LETTERS, 2018, 2 (01)
  • [3] Anghelescu P, 2015, INT C ELECT COMPUT, pAE1
  • [4] Isolated Bidirectional Grid-Tied Three-Phase AC-DC Power Conversion Using Series-Resonant Converter Modules and a Three-Phase Unfolder
    Chen, W. Warren
    Zane, Regan
    Corradini, Luca
    [J]. IEEE TRANSACTIONS ON POWER ELECTRONICS, 2017, 32 (12) : 9001 - 9012
  • [5] Clemente J, 2018, IEEE GLOB CONF SIG, P693, DOI 10.1109/GlobalSIP.2018.8646641
  • [6] A Radar-Based Smart Sensor for Unobtrusive Elderly Monitoring in Ambient Assisted Living Applications
    Diraco, Giovanni
    Leone, Alessandro
    Siciliano, Pietro
    [J]. BIOSENSORS-BASEL, 2017, 7 (04):
  • [7] Durand S, 2001, INT CONF ACOUST SPEE, P3685, DOI 10.1109/ICASSP.2001.940642
  • [8] Ekimov A., J ACOUST SOC AM, V118, P2021
  • [9] Grafana Labs, 2018, GRAF
  • [10] Kepski M, 2012, LECT NOTES COMPUT SC, V7383, P407, DOI 10.1007/978-3-642-31534-3_60