Next Article in Journal
A Micromachined Pressure Sensor with Integrated Resonator Operating at Atmospheric Pressure
Next Article in Special Issue
Combined Hand Gesture — Speech Model for Human Action Recognition
Previous Article in Journal / Special Issue
Automatic and Objective Assessment of Alternating Tapping Performance in Parkinson’s Disease
Article Menu

Export Article

Open AccessArticle
Sensors 2013, 13(12), 16985-17005; https://doi.org/10.3390/s131216985

Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home

Department of Computer Science & Information Engineering, National Dong-Hwa University, No. 1, Sec. 2, Da-Hsueh Rd., Shoufeng, Hualien 974, Taiwan
*
Author to whom correspondence should be addressed.
Received: 19 September 2013 / Revised: 22 November 2013 / Accepted: 26 November 2013 / Published: 10 December 2013
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
View Full-Text   |   Download PDF [2270 KB, uploaded 21 June 2014]   |  

Abstract

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second. View Full-Text
Keywords: Kinect; toddler; childcare; fall risk; early-warning Kinect; toddler; childcare; fall risk; early-warning
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Yang, M.-T.; Chuang, M.-W. Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home. Sensors 2013, 13, 16985-17005.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top