ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
SenSay: A Context-Aware Mobile Phone
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
Gait phase effects in mobile interaction
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Sensor networks as video game input devices
Future Play '07 Proceedings of the 2007 conference on Future Play
Mobile empathy: putting the mobile device in its user's shoes
Proceedings of the 5th Nordic conference on Human-computer interaction: building bridges
ePet: when cellular phone learns to recognize its owner
Proceedings of the 2nd ACM workshop on Assurable and usable security configuration
Gait identification using cumulants of accelerometer data
SENSIG'09/VIS'09/MATERIALS'09 Proceedings of the 2nd WSEAS International Conference on Sensors, and Signals and Visualization, Imaging and Simulation and Materials Science
WSEAS Transactions on Signal Processing
Sensing foot gestures from the pocket
UIST '10 Proceedings of the 23nd annual ACM symposium on User interface software and technology
Towards ubiquitous acquisition and processing of gait parameters
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Personal and Ubiquitous Computing
A real-time living activity recognition system using off-the-shelf sensors on a mobile phone
CONTEXT'11 Proceedings of the 7th international and interdisciplinary conference on Modeling and using context
An online human activity recognizer for mobile phones with accelerometer
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Putting your best foot forward: investigating real-world mappings for foot-based gestures
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia
Towards a semi-automatic personal digital diary: detecting daily activities from smartphone sensors
Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
Capturing Basic Movements for Mobile Gaming Platforms Embedded with Motion Sensors
International Journal of E-Health and Medical Communications
Proceedings of the 2013 international conference on Intelligent user interfaces
A survey on smartphone-based systems for opportunistic user context recognition
ACM Computing Surveys (CSUR)
Walk detection and step counting on unconstrained smartphones
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Ultrasound-based movement sensing, gesture-, and context-recognition
Proceedings of the 2013 International Symposium on Wearable Computers
Accelerometer-based transportation mode detection on smartphones
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
| Hi-index | 0.00 |
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%.