"Killer App" of wearable computing: wireless force sensing body protectors for martial arts
Proceedings of the 17th annual ACM symposium on User interface software and technology
Covariate Shift Adaptation by Importance Weighted Cross Validation
The Journal of Machine Learning Research
Rapid Prototyping of Activity Recognition Applications
IEEE Pervasive Computing
Wearable Activity Tracking in Car Manufacturing
IEEE Pervasive Computing
Dealing with sensor displacement in motion-based onbody activity recognition systems
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
ISWC '09 Proceedings of the 2009 International Symposium on Wearable Computers
Unsupervised Adaptation to On-body Sensor Displacement in Acceleration-Based Activity Recognition
ISWC '11 Proceedings of the 2011 15th Annual International Symposium on Wearable Computers
Using a live-in laboratory for ubiquitous computing research
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Personal and Ubiquitous Computing
Activity recognition based on a multi-sensor meta-classifier
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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This work introduces an open benchmark dataset to investigate inertial sensor displacement effects in activity recognition. While sensor position displacements such as rotations and translations have been recognised as a key limitation for the deployment of wearable systems, a realistic dataset is lacking. We introduce a concept of gradual sensor displacement conditions, including ideal, self-placement of a user, and mutual displacement deployments. These conditions were analysed in the dataset considering 33 fitness activities, recorded using 9 inertial sensor units from 17 participants. Our statistical analysis of acceleration features quantified relative effects of the displacement conditions. We expect that the dataset can be used to benchmark and compare recognition algorithms in the future.