Paper Info
Title
Gait analyzer based on a cell phone with a single three-axis accelerometer
Abstract
We propose a fuss-free gait analyzer based on a single three-axis accelerometer mounted on a cell phone for health care and presence services. It is not necessary for users not to wear sensors on any part of their bodies; all they need to do is to carry the cell phone. Our algorithm has two main functions; one is to extract feature vectors by analyzing sensor data in detail using wavelet packet decomposition. The other is to flexibly cluster personal gaits by combining a self-organizing algorithm with Bayesian theory. Not only does the three-axis accelerometer realize low cost personal devices, but we can track aging or situation changes through on-line learning. A prototype that implements the algorithm is constructed. Experiments on the prototype show that the algorithm can identify gaits such as walking, running, going up/down stairs, and walking fast with an accuracy of about 80%.
Year
DOI
Venue
2006
10.1145/1152215.1152244
Mobile HCI
Keywords
Field
DocType
single three-axis,single three-axis accelerometer,prototype show,cluster personal gait,fuss-free gait analyzer,self-organizing algorithm,cell phone,feature vector,three-axis accelerometer,personal device,bayesian theory,health care,sensor,self organizing map,wavelet packet decomposition,gait analysis,self organization,accelerometer
Computer vision,Feature vector,Gait,Accelerometer,Computer science,Self-organizing map,Phone,Gait analysis,Artificial intelligence,Wavelet packet decomposition,Spectrum analyzer
Conference
ISBN
Citations 
PageRank 
1-59593-390-5
50
4.19
References 
Authors
7
2
Name
Order
Citations
PageRank
Toshiki Iso1626.49
Kenichi Yamazaki215112.39