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iWOAR 2018 - 5th International Workshop on Sensor-based Activity Recognition and Interaction

Date2018-09-20 - 2018-09-21

Deadline2018-06-15

VenueBerlin, Germany Germany

Keywords

Websitehttps://iwoar.org/2018

Topics/Call fo Papers

Wearable sensors potentially enable for a better and unobtrusive recognition of human activity and the state of rest, sleep, stress and drive the ongoing trend of the quantified self-movement. As an enabling technology, powerful, while yet inexpensive MEMS-Chips (micro-electro-mechanical system) push the penetration of a broad variety of mobile devices. Thereby, these devices gain high interest, not only in terms of general customer products, but also as integrated systems in an industrial context, either way to enable continuous monitoring of complex life processes and workplace situations.
Another challenge that research is facing concerns the limited human abilities of interaction in context of mobility and in situations, in which high attention is being demanded. New and alternative ways are needed to be found in order to take advantage of all human capabilities to enable safe and unobtrusive interaction.
This conference-like workshop is initiated and organized by the Fraunhofer IGD and the University of Rostock. It offers scientists, interested parties, and users in the area of sensor-based activity recognition and interaction the possibility to an exchange of experiences and a presentation of best-practice examples, as well as technical and scientific results. The workshop focuses on technologies for human activity recognition and interaction via inertial sensors (accelerometers, gyroscopes etc.) and their scientific applications.
Thereby, the following topics and fields of application will be addressed:
Topics:
Human Activity Recognition
Human Performance Measuring
Human Monitoring
Wearable Sensing in Healthcare Informatics Wearable Computing
Interaction Techniques
Intelligent User Interfaces
Input & Output modalities
Context Awareness
Machine Learning
Artificial Intelligence
Deep Learning
Feature Extraction
Data Classification
Data Imputation
Signal Reconstruction and Interpolation
Application Fields:
Ambient Assisted Living
Technologies for Senior Living
Quantified Self
Lifestyle & Behavior Change
Pervasive Healthcare
Occupational Health, Health Care and Wellness
Telemedicine and Biotechnology
Assisted Production
Maintenance and Service
Alternative Control of Everyday Life's Products
Assistive Technologies for Urban Environments

Last modified: 2018-02-15 17:15:40