A frequency-domain analysis of head-motion prediction
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
What Shall We Teach Our Pants?
ISWC '00 Proceedings of the 4th IEEE International Symposium on Wearable Computers
MIThril 2003: Applications and Architecture
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
A paradigm shift: alternative interaction techniques for use with mobile & wearable devices
CASCON '03 Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research
Analyzing features for activity recognition
Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies
Generic Personal Assistance Architecture for Mobile Environments
SMAP '06 Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization
Feature selection and activity recognition from wearable sensors
UCS'06 Proceedings of the Third international conference on Ubiquitous Computing Systems
A wearable multi-sensor system for mobile acquisition of emotion-related physiological data
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Activity classification using realistic data from wearable sensors
IEEE Transactions on Information Technology in Biomedicine
Measuring Cognitive Workload in Non-military Scenarios Criteria for Sensor Technologies
FAC '09 Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009
Activity recognition using biomechanical model based pose estimation
EuroSSC'10 Proceedings of the 5th European conference on Smart sensing and context
Towards global aerobic activity monitoring
Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments
Sensor requirements for activity recognition on smart watches
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
| Hi-index | 0.00 |
Physical activity is one important aspect in user behavior analysis. Abnormal movement behavior might be an indicator for an inappropriate lifestyle, insufficient social inclusion, or generally disadvantageous life conditions which might call for medical treatment. Assistive technologies can make use of information on the physical activity of e.g. residents of a nursing home or elderly patients living alone at home. In this paper, we present a mobile technology for identifying movement behavior in everyday life. A three-dimensional acceleration sensor is used to determine physical activity by domain specific feature extraction. By use of data mining techniques and a feature set extracted from everyday usage data, we achieve a high quality and robust classification of physical activity. This can be used for further user behavior analysis. Especially non-linear features like step-detection, horizontal and vertical acceleration as well as spectral analysis proved to be very powerful. A proof-of concept prototype is described which shows the applicability of the developed technologies in everyday life.