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  4. Define Stance and Swing pattern of gait cycle using motion sensor and K-Mean Clustering
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Define Stance and Swing pattern of gait cycle using motion sensor and K-Mean Clustering

Author(s)
Santikan, Piyapon
Tangwongcharoen, Wisan
Kimpan, Warangkhana
Date Issued
January 1, 2022
Type
Conference Paper
DOI
10.1109/ECTI-CON54298.2022.9795482
Abstract
This research studied walking patterns based on the gait cycle focused on the stance and swing period. We are interested in creating the pattern for representing a normal person and person with a walking disorder by distinguishing patterns. This research uses Razor-IMU to collect all walking data and transfer data from sensors via WIFI which helps gain data to be stable and accurate.After collecting the walking data, we transformed data into linear graphs to reference the gait cycle pattern. Because the graph in linear form can show the movement and distinguish between normal and abnormal people the difference. The aim is to obtain representative data of normal and abnormal people for further analysis. Therefore, the data were then grouped using K-mean Clustering. The data obtained from the clusters were able to distinguish between normal and abnormal walking distances.
Citation
19th International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology Ecti Con 2022, 2022
Subjects

Gait cycle

K-Mean Clustering

Stance

Swing

Walking

Metrics
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