Enhancing handgun safety with embedded signal processing and dynamic grip recognition

Timothy Chang, Zong Chen, Biao Cheng, Michael Cody, Michael Liska, William Marshall, Michael Recce, Donald Sebastian, Dimitri Shishkin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper describes the first phase results in personalized weapons technology utilizing biometrics, in order to develop a user only system that recognizes unique human characteristics of a specific individual. In particular, the investigation is focused on development of a Dynamic Grip Recognition (DGR) system where a sensor embedded grip and digital signal processing unit have been fabricated to perform user recognition in real time. Specifically, grips with 16 piezoelectric sensors have been developed and fitted to an M9 pistol. In addition, the required trigger switch has also been developed and incorporated into the DGR system. The DGR method performed as well in live fire (93% recognition rate) as it did in the simulator environment (95% recognition rate). Furthermore, all of the electronics, signal capture devices and sensors were demonstrated to be unaffected by the environmental extremes of live fire (over 400 shots), and to perform well.

Original languageEnglish (US)
Title of host publicationIECON 2005
Subtitle of host publication31st Annual Conference of IEEE Industrial Electronics Society
Pages2107-2113
Number of pages7
DOIs
StatePublished - 2005
EventIECON 2005: 31st Annual Conference of IEEE Industrial Electronics Society - Raleigh, NC, United States
Duration: Nov 6 2005Nov 10 2005

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2005

Other

OtherIECON 2005: 31st Annual Conference of IEEE Industrial Electronics Society
Country/TerritoryUnited States
CityRaleigh, NC
Period11/6/0511/10/05

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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