Analysis of human footsteps utilizing multi-axial seismic fusion

Abstract

This paper introduces a method of enhancing an unattended ground sensor (UGS) system's classification capability of humans via seismic signatures while subsequently discriminating these events from a range of other sources of seismic activity. Previous studies have been performed to consistently discriminate between human and animal signatures using cadence analysis. The studies performed herein will expand upon this methodology by improving both the success rate of such methods as well as the effective range of classification. This is accomplished by fusing multiple seismic axes in real-time to separate impulsive events from environmental noise. Additionally, features can be extracted from the fused axes to gather more advanced information about the source of a seismic event. Compared to more basic cadence determination algorithms, the proposed method substantially improves the detection range and correct classification of humans and significantly decreases false classifications due to animals and ambient conditions.

A New Identification Method of Underground Excavation Based on Velocity Estimation Using Double Point Synchronous Measurements

“…A large number of experiments have shown that seismic waves are primarily composed of Rayleigh waves. Therefore, Rayleigh waves are widely used in seismic signal analysis [18]- [20].…”

Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

“…In the domain of human sensing, seismic waves have been used to detect presence of humans [88,89], tracking and bearing estimation [90]. Mainly the seismic studies that consider animals have focused on differentiating between two categories (bipedal (human) and quadruped (animals) [78,91]). Few works on pure wildlife studies have focused on problems such as detection or classification of animals.…”

Intelligent Carpet System, Based on Photonic Guided-Path Tomography, for Gait and Balance Monitoring in Home Environments

“…Generally, this task can be achieved by systems of varying complexity, portability and cost, depending on the context in which they are deployed. A number of methods for footstep sensing have been proposed and developed since the 1980s, involving piezoelectric [1], [2], resistive [3], force [4], [5], capacitive [6], seismic [7] and acoustic sensing principles [8]. The utilized sensing technology has included load cells [9], [10], switches [11], electromechanical films [12], optical fibers [13], flatbed scanners [14], resistive loads [15] and accelerometers [16], as well as combinations thereof [17].…”