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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links.

Tong Liu1, Zhuo-Qian Liang2

  • 1Department of Electronics Engineering, Huizhou University, Huizhou 516001, China. ltee@hzu.edu.cn.

Sensors (Basel, Switzerland)
|December 6, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a novel biometric system using radio frequency (RF) links for classifying individuals based on their walking patterns. The system leverages fluctuated received signal strength (RSS) data for accurate, path-dependent walker recognition.

Keywords:
biometric sensingubiquitous RF linkswalker classification

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Area of Science:

  • Biometrics
  • Radio Frequency Sensing
  • Human Motion Analysis

Background:

  • Ubiquitous radio frequency (RF) links offer potential for non-intrusive sensing.
  • Received signal strength (RSS) fluctuations are indicative of human motion.
  • Existing biometric systems often require dedicated hardware or specific conditions.

Purpose of the Study:

  • To propose a lightweight biometric sensing system for path-dependent walker classification using RF links.
  • To investigate the effectiveness of a three-layer RF sensing network for capturing discriminative human motion features.
  • To compare vector quantization (VQ) and hidden Markov models (HMMs) for walker recognition and verification.

Main Methods:

  • Utilizing fluctuated received signal strength (RSS) sequences from human motion as features.
  • Organizing a three-layer RF sensing network with links at upper limb, thigh, and lower leg heights.
  • Investigating optimal sensing configuration parameters, including link height and number of fused links.
  • Developing and comparing VQ and HMMs for classification tasks.

Main Results:

  • Synergistic sensing using multiple RF links significantly improves distinction among subjects.
  • The proposed system demonstrates effectiveness in both line-of-sight (LOS) and non-line-of-sight (NLOS) indoor scenarios.
  • Comparative analysis of VQ and HMMs provides insights into classification performance for walker recognition.

Conclusions:

  • RF links can be effectively utilized as a novel component in biometric sensing systems.
  • A multi-link RF sensing network enhances the accuracy and robustness of walker classification.
  • The developed system offers a lightweight and versatile approach to biometric identification based on gait.