Left and Right Hand Gesture Classification Using Scatter Diagram and Principle Component Analysis

This study investigates and acts as a trial clinical outcome for human motion and hand behaviour analysis in consensus of subject's habit related quality of life. It was developed to analyse and access the quality of human hands motion that can be used in hospitals, clinics and human motion res...

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Bibliographic Details
Main Authors: Chew, Kim Mey, Yong, Ching Yee, Rubita, Sudirman, Nasrul Humaimi, Mahmood
Format: Proceeding
Language:English
Published: 2013
Subjects:
Online Access:http://ir.unimas.my/id/eprint/45894/1/P11.%20Left%20and%20Right%20Hand%20Gesture%20Classification%20Using%20Scatter%20Diagram%20and%20Principle%20Component%20Analysis%20%28IEEE%29.pdf
http://ir.unimas.my/id/eprint/45894/
https://ieeexplore.ieee.org/document/6498182
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Summary:This study investigates and acts as a trial clinical outcome for human motion and hand behaviour analysis in consensus of subject's habit related quality of life. It was developed to analyse and access the quality of human hands motion that can be used in hospitals, clinics and human motion researches. It aims to establish how widespread the quality of life effects of human motion. An experiment was set up in a laboratory environment with conjunction of analysing human hand motion and its habit. Sensors are attached on both wrists. The instruments demonstrate adequate internal consistency of findings: 1. it is hard for subject to draw a perfect circle whether using left or right hand and this is supported by descriptive statistical data and scatter diagram. 2. Subject's left hand unable to draw a perfect circle or square. These two drawings are looks alike and it is supported by PCA analysis. A simple and informative representation for statistical data, scatter diagram and PCA plot were developed to demonstrate the results.