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Sensors 2017, 17(12), 2815; https://doi.org/10.3390/s17122815

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

1
Department of Electronics Engineering, Huizhou University, Huizhou 516001, China
2
College of Information Science and Technology, Jinan University, Guangzhou 510632, China
*
Author to whom correspondence should be addressed.
Received: 5 November 2017 / Revised: 2 December 2017 / Accepted: 3 December 2017 / Published: 5 December 2017
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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Abstract

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method. View Full-Text
Keywords: biometric sensing; walker classification; ubiquitous RF links biometric sensing; walker classification; ubiquitous RF links
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Liu, T.; Liang, Z.-Q. Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links. Sensors 2017, 17, 2815.

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