Abstract
The ability to discriminate between falls and activities of daily living (ADL) has been investigated by using tri-axial accelerometer sensors, mounted on the trunk and using simulated falls performed by young healthy subjects under supervised conditions and ADL performed by elderly subjects. In this paper we propose a power-aware real-time fall detection integrated circuit (IC) that can distinguish Falls from ADL by processing the accelerations measured during 240 falls and 240 ADL.In the proposed fixed point custom DSP architecture, a threshold algorithm was implemented to analyze the effectiveness of Programmable Truncated Multiplication regarding power reduction while maintaining a high output accuracy. The presented system runs a real time implementation of the algorithm on a low power architecture that allows up to 23% power savings through its digital blocks when compared to a standard implementation, without any accuracy loss.
| Original language | English (Ireland) |
|---|---|
| Title of host publication | Real-time Low-energy Fall Detection Algorithm with a Programmable Truncated MAC |
| Number of pages | 4 |
| Publication status | Published - 1 Oct 2010 |
Authors (Note for portal: view the doc link for the full list of authors)
- Authors
- Solaz, MD,Bourke, A,Conway, R,Nelson, J,OLaighin, G,