Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Review Article A Human Gait Classification Method Based on Radar Doppler Spectrograms | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 389716 12 pages doi 2010 389716 Review Article A Human Gait Classification Method Based on Radar Doppler Spectrograms Fok Hing Chi Tivive 1 Abdesselam Bouzerdoum 1 and Moeness G. Amin EURASIP Member 2 1 School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong NSW 2522 Australia 2 Center for Advanced Communications Villanova University Villanova PA 19085 USA Correspondence should be addressed to Fok Hing Chi Tivive tivive@ Received 1 February 2010 Accepted 24 June 2010 Academic Editor L. F. Chaparro Copyright 2010 Fok Hing Chi Tivive et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. An image classification technique which has recently been introduced for visual pattern recognition is successfully applied for human gait classification based on radar Doppler signatures depicted in the time-frequency domain. The proposed method has three processing stages. The first two stages are designed to extract Doppler features that can effectively characterize human motion based on the nature of arm swings and the third stage performs classification. Three types of arm motion are considered free-arm swings one-arm confined swings and no-arm swings. The last two arm motions can be indicative of a human carrying objects or a person in stressed situations. The paper discusses the different steps of the proposed method for extracting distinctive Doppler features and demonstrates their contributions to the final and desirable classification rates. 1. Introduction In the past few years human gait analysis has received significant interest due to its numerous applications such as border surveillance video understanding biometric identification and .
