Publication Type : Conference Paper
Thematic Areas : Learning-Technologies, Medical Sciences, Biotech
Publisher : Proceedings of the Third International Conference on Computing and Network Communications (CoCoNet’19) (accepted), Trivandrum, Kerala, India .
Source : Proceedings of the Third International Conference on Computing and Network Communications (CoCoNet’19), Trivandrum, Kerala, India, Dec 18-21, 2019.
Url : https://scholar.google.com/scholar?oi=bibs&cluster=13739677239843420800&btnI=1&hl=en
Keywords : Sum vector analysisclassificationMuscle kinematicsLow-cost method
Campus : Amritapuri
School : School of Biotechnology
Center : Amrita Mind Brain Center, Biotechnology, Computational Neuroscience and Neurophysiology
Department : Computational Neuroscience Laboratory, biotechnology
Year : 2019
Abstract : Recent advances in low-cost wearable sensors with methodologies, have opened up a promising future for gait analysis. By providing patient analysis with gait disorders from clinics to common people the analysis requires some form of précised user input. The purpose of this study was to develop a computationally low-cost methodology that could evaluate the performance of different sensor configurations and to study the effect of locomotion mode for swing and stance using kinematic data from hip, knee and ankle extracted using mobile phone accelerometers. The method involved features translated as sum vectors and then using a simple neural network where gait data was normalized and classified the swing or stance. Sum-vector neural network-based method allowed a significantly higher test accuracy compared to the other machine learning algorithms. As an extended gait analysis model focusing predictive applications and implementations that need faster computations, the method could classify the gait kinetic and kinematics of human lower limb more optimally.
Cite this Research Publication : S. S. Babu, Chaitanya Nutakki, and Dr. Shyam Diwakar, “Classification of Human Gait: Swing and Stance Phases using Sum-Vector Analysis”, in Proceedings of the Third International Conference on Computing and Network Communications (CoCoNet’19), Trivandrum, Kerala, India, Dec 18-21, 2019.