Abstract
This paper introduces the use of autoregressive modelling (AR) to characterize individual human gait signatures from micro-Doppler data. AR models are fitted to micro-Doppler data obtained while 6 subjects walk towards a custom-made ultrasonic transceiver module. The estimated AR coefficients capture individual movement characteristics. Such features can be used to identify different subjects quickly and with low computational cost. In the best configuration, average performance higher than 98% was obtained.
Original language | English |
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Title of host publication | 2012 IEEE Biomedical Circuits and Systems Conference |
Subtitle of host publication | Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications |
Pages | 312-315 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 1 Dec 2012 |
Externally published | Yes |
Event | 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Hsinchu, Taiwan, Province of China Duration: 28 Nov 2012 → 30 Nov 2012 |
Conference
Conference | 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 |
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Country/Territory | Taiwan, Province of China |
City | Hsinchu |
Period | 28/11/12 → 30/11/12 |
Keywords
- autoregressive models
- individual recognition
- Micro-Doppler
- ultrasonic device