Biometrics system for gait analysis using inertial measurement units (IMU)
DOI:
https://doi.org/10.33414/rtyc.49.47-67.2024Keywords:
Gait biometrics, Multidimensional analysis, Inertial measurement units, Assessment of human jointsAbstract
The people movement depends of nervous system action on specific muscle groups that rest on the bone structure. Some pathological processes can cause alterations in the strength and coordination that must exist between the muscular responses, causing alterations in the expected movement. In their initial phase, most of these alterations go unnoticed until the physical damage significantly affects human activity, and in many cases irreparably. Currently, the most widely used method for the analysis of human movement is based on study of sequential photography in limited space, although digital positioning systems are also used to a lesser extent. This project deals with the technology development for biometric capture of human movement using inertial measurement sensors. The idea is to detail the spatial displacement of body specific sections to from the measurement of acceleration and angular movement, with the purpose of assessing the response of the joints involved. The objective is developed a system that allows to specialists medical identify abnormalities in the movement of patient under study. Preliminary results demonstrate the efficiency of implemented inertial sensor. Using 7 sensors strategically located on the patient's body and with an acquisition speed of 100 samples per second on each sensor, it's possible to detail walking movements less than 7.5 millimeters and accuracy in angular velocity up 0.1°/0.01 second. With the development of this instrument, the ability to visualize and analyze movements that are normally imperceptible to the human eye is achieved.
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Copyright (c) 2024 Nelson Dugarte Jerez, Antonio Alvarez Abril, Negman W. Alvarado Riviera, Carlos Marcelo Gómez, Ana Lattuca, Guillermo Martín Sosa Barraco, Edison del Carmen Dugarte Dugarte, German Lombardo
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
