Gunshot Recoil Dataset

Citation Author(s):
David
Welsh
University of Maryland, Baltimore County
Md Abdullah Al
Hafiz Khan
Kennesaw State University
Nirmalya
Roy
University of Maryland, Baltimore County
Submitted by:
David Welsh
Last updated:
Mon, 10/18/2021 - 18:47
DOI:
10.21227/2k8c-tm65
Data Format:
*.csv
Links:
UMBC MPSC Resources
License:
Creative Commons Attribution
869 Views
Categories:
Artificial Intelligence
Signal Processing
Machine Learning
Sensors
Wearable Sensing
Keywords:
Signal Processing, Human Activity Recognition (HAR), accelerometer, Gunshot
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Abstract 

The Firearm Recoil Dataset was collected utilizing a wrist worn accelerometer to record the recoil generated from one subject’s use of 15 different firearms of the Handgun, Rifle and Shotgun class. The type of the firearm based on its ability to auto-load or not is also denoted. 

Instructions: 

Datasets are broken up into seperate CSV files for each individual firearm. Details associated with the firearm utilized and data collection specifications is outlined in the Readme File. 

If you use this datasets for your research, please cite the following paper:

Md. Abdullah Al Hafiz Khan, David Welsh, and Nirmalya Roy. Firearm Detection Using Wrist Worn Tri-Axis Accelerometer Signals, in Proceedings of the 4th Workshop on sensing systems and applications using wrist worn smart devices (WristSense’18), co-located with PerCom, March 2018

Comments

Thank you

Submitted by Thai Ha Dang on Fri, 06/03/2022 - 04:40

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Documentation

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File Readme.pdf619.41 KB

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