Title :
Affection sensing in gait using intelligent shoe system
Author :
Yanbo Tao ; Huihuan Qian ; Yangsheng Xu
Author_Institution :
Dept. of Mech. & Autom. Eng., Chinese Univ. of Hong Kong, Shatin, China
Abstract :
The human behavior, such as gait, is controlled by the brain and other peripheral neural system, and thus is significantly affected by the internal emotion. It is important to carry out the affective sensation of abnormal internal emotion in a non-invasive and non-privacy-infringed way. This paper presents an experiment method and platform to sense the abnormal affective status through gaits. We used a wearable intelligent shoe system for affective sensing, designed an experiment for the human subject to have the normal gait and the gait with emotional disorder, and finally classified the gaits through machine learning.
Keywords :
behavioural sciences computing; emotion recognition; gait analysis; learning (artificial intelligence); wearable computers; abnormal affective status; abnormal internal emotion affective sensation; affection sensing; emotional disorder; human behavior; human gait; machine learning; peripheral neural system; wearable intelligent shoe system; Artificial intelligence; Electromyography; Foot; Footwear; Legged locomotion; Roads; Sensors; Affection sensing; Gait; Machine learning;
Conference_Titel :
Information Science and Technology (ICIST), 2014 4th IEEE International Conference on
Conference_Location :
Shenzhen
DOI :
10.1109/ICIST.2014.6920589
