Next Article in Journal
Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space
Next Article in Special Issue
A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection
Previous Article in Journal
A Study about Kalman Filters Applied to Embedded Sensors
Previous Article in Special Issue
Frequency-Locked Detector Threshold Setting Criteria Based on Mean-Time-To-Lose-Lock (MTLL) for GPS Receivers
Open AccessArticle

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

by 1,* and 2
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.
Sensors 2017, 17(12), 2815; https://doi.org/10.3390/s17122815
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)
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
Show Figures

Figure 1

MDPI and ACS Style

Liu, T.; Liang, Z.-Q. Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links. Sensors 2017, 17, 2815.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
  • Externally hosted supplementary file 1
    Doi: no
    Link: http://no
    Description: A preliminary related study.
Back to TopTop