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Updated: May 14, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Wireless slips and falls prediction system.

Devon Krenzel1, Steve Warren, Kejia Li

  • 1Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS, USA.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|February 1, 2013
PubMed
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This study developed a wireless wearable device to detect and predict falls in the elderly. Real-time analysis of sensor data shows promise in identifying instability and preventing future incidents.

Area of Science:

  • Biomedical Engineering
  • Gerontology
  • Wearable Technology

Background:

  • Falls are a significant risk for the elderly, often caused by reduced strength and stability.
  • Predicting and detecting falls can enhance independence and reduce fall-related injuries.

Purpose of the Study:

  • To design and evaluate a wireless, wearable device for fall detection and prediction in older adults.
  • To assess the device's capability in real-time instability detection.

Main Methods:

  • A wireless wearable device was developed to collect accelerometer and gyroscope data.
  • Lyapunov-based analyses were applied to the time series sensor data.
  • Real-time detection and prediction algorithms were implemented.

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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Published on: February 8, 2019

Related Experiment Videos

Last Updated: May 14, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Using Motion Capture Technology in the Instrumented Timed Up and Go Test to Detect the Risk of Falling in Aged Adults
05:26

Using Motion Capture Technology in the Instrumented Timed Up and Go Test to Detect the Risk of Falling in Aged Adults

Published on: October 25, 2024

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
04:13

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Published on: February 8, 2019

Main Results:

  • The device successfully sampled continuous accelerometer and gyroscope data.
  • Lyapunov-based analyses demonstrated real-time detection of wearer instability.
  • The system showed the potential for predicting impending falls.

Conclusions:

  • The developed wearable device can detect and predict falls in the elderly.
  • Real-time instability detection using sensor data is feasible.
  • This technology can contribute to fall prevention and increased independence for seniors.