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Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

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Real-time low-energy fall detection algorithm with a programmable truncated MAC.

Manuel de la Guia Solaz¹, Alan Bourke, Richard Conway

¹Electronics and Computer Engineering Department, University of Limerick, Ireland. manuel.delaguia@ul.ie

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 25, 2010

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This study introduces a power-efficient integrated circuit for real-time fall detection, accurately distinguishing falls from daily activities using accelerometer data. The system achieves significant power savings without compromising accuracy.

Area of Science:

Biomedical Engineering
Signal Processing
Wearable Technology

Background:

Distinguishing falls from activities of daily living (ADL) is crucial for elder care and patient monitoring.
Tri-axial accelerometers are commonly used for fall detection, but power consumption remains a challenge for continuous monitoring.
Existing systems often require high power, limiting their practical application in wearable devices.

Purpose of the Study:

To propose a novel power-aware real-time fall detection integrated circuit (IC).
To develop a system capable of accurately distinguishing between falls and ADL using accelerometer data.
To evaluate the power-saving potential of a custom Digital Signal Processor (DSP) architecture with Programmable Truncated Multiplication.

Main Methods:

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A custom fixed-point DSP architecture was designed for real-time processing of acceleration data.

A threshold algorithm incorporating Programmable Truncated Multiplication was implemented to analyze fall events.

The system processed data from 240 simulated falls and 240 ADL, recorded using trunk-mounted tri-axial accelerometers.

Main Results:

The proposed IC accurately distinguished between falls and ADL.
The implemented algorithm achieved up to 23% power savings in digital blocks compared to standard implementations.
No loss in accuracy was observed despite the power reduction techniques used.

Conclusions:

The developed power-aware IC offers an effective solution for real-time fall detection.
Programmable Truncated Multiplication is a viable technique for reducing power consumption in DSP architectures for fall detection.
This technology has the potential to enhance the reliability and practicality of wearable fall monitoring systems.