SmartFDS: Design and Implementation of Falling Detection System on Smartphones

Xiao Li, Yufeng Wang, Qicai Zhou, Qun Jin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Falling accidents cause severe damage to human health, especially to the elderly. Nowadays, smartphones are ubiquitous and widely used around the world, in which rich sensors are embedded. Thus, a smartphone based falling detection system, SmartFDS is proposed in this paper, which can recognize the associated individual's falling behavior and send out an emergent message containing the location for immediate help. Generally, SmartFDS includes offline training phase and online activity recognition phase. Specifically, in training phase, utilizing the embedded accelerometer sensor, falling data for various situations are collected to extract the desired features that can appropriately characterize the falling behavior. Considering that the raw data are intrinsically prone to noise and error, those data are preprocessed by weighted smoothing. Then, 6 time-domain features are elaborated to determine the discriminative features for characterizing falling, and two features, maximum and vertical velocity are selected. Then, 4 different classification algorithms are investigated, and SVM is selected. The prototype of SmartFDS is implemented on Android phones, and can detect falling in real time accurately.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016
EditorsXingang Liu, Tie Qiu, Yayong Li, Bin Guo, Zhaolong Ning, Kaixuan Lu, Mianxiong Dong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages402-405
Number of pages4
ISBN (Electronic)9781509058808
DOIs
Publication statusPublished - 2017 May 1
Event9th IEEE International Conference on Internet of Things, 12th IEEE International Conference on Green Computing and Communications, 9th IEEE International Conference on Cyber, Physical, and Social Computing and 2016 IEEE International Conference on Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016 - Chengdu, China
Duration: 2016 Dec 162016 Dec 19

Publication series

NameProceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016

Other

Other9th IEEE International Conference on Internet of Things, 12th IEEE International Conference on Green Computing and Communications, 9th IEEE International Conference on Cyber, Physical, and Social Computing and 2016 IEEE International Conference on Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016
CountryChina
CityChengdu
Period16/12/1616/12/19

Keywords

  • Classification
  • Falling detection
  • Feature selection
  • Smartphone

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Communication

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