Joint Gait Kinematic and Kinetic Analysis using Inertial Measurement Units and Plantar Pressure Sensor System

Joint Gait Kinematic and Kinetic Analysis using Inertial Measurement Units and Plantar Pressure Sensor System

Gait analysis is widely used in various fields of research, often associated in the field that concerns public health. The kinematic and kinetic analysis of a person's gait are the usual elements involved for the advancement of the topics involving this area but a relationship between the two a...

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Bibliographic Details
Published in:2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM ) pp. 1 - 6
Main Authors: Dela Cruz, Michaela Anne A., Legaspi, Katrina Mae C., Marcelino, Raymund Miguel D., Rosete, Jan Ryan, Sangalang, Danielle Anne R., Suarez, Consuelo G., Roxas, Edison A., Serrano, Kanny Krizzy D., dela Cruz, Angelo R.
Format: Conference Proceeding
Language:English
Published: IEEE 01-11-2019
Subjects:
angle
correlation
F-Scan System
Foot
gait
IMU
Kinematics
kinetic
Kinetic theory
Knee
Legged locomotion
Mathematical model
MATLAB
peak pressure
plantar pressure
regression
Sensors
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Summary:Gait analysis is widely used in various fields of research, often associated in the field that concerns public health. The kinematic and kinetic analysis of a person's gait are the usual elements involved for the advancement of the topics involving this area but a relationship between the two are not often established or focused upon. The purpose of this study is to discover the correlation between the kinetic and kinematic elements of a person's gait with the use of wearable sensors such as IMUs and insole plantar pressure sensors. The sensors, alongside their corresponding software, were utilized to observe a person's gait based on gait cycles. The acquired data were viewed using MATLAB and is analyzed in terms of its plantar pressure and kinematic composition. Consequently, the results displayed the angular displacement and pressure distribution per leg and foot. Using Regression Learner app from MATLAB, a model is trained to test the validity of said model with a test subject. The Pearson's correlation coefficient of the actual and predicted waveforms ranged from 0.80 to 0.95. The system can also be used to aid in gait analysis and assessment by medical practitioners and by future researchers.
DOI:10.1109/HNICEM48295.2019.9072701