@inproceedings{3bdd3aacb9364b17be7f1bfde188cdc8,
title = "Poster: Unobtrusive user verification using piezoelectric energy harvesting",
abstract = "With the capability to harvest energy from low frequency motions or vibrations, piezoelectric energy harvesting has become a promising solution to achieve self-powered wearable system. Apart from generating energy to power the wearable devices, the output electricity signal of the PEH can also be used as an information source as it reects the activity or motion paerns of the user. In this paper, we have designed and built an insole-based user authentication system by leveraging the AC voltage generated by the PEH during human walking. Meanwhile, the generated power is also collected and stored, which could be later used as the power source of the mobile system. By using a dataset of 20 subjects, we have demonstrated that our system can achieve 89.76\% of human recognition accuracy when using only one gait cycle signal, and the accuracy can be further increased to 95.86\% when two gait cycles are utilized.",
keywords = "Energy-eciency, Gait verication, Sparse representation, Wearable device",
author = "Dong Ma and Guohao Lan and Weitao Xu and Mahbub Hassan and Wen Hu",
year = "2017",
month = nov,
doi = "10.1145/3144457.3144510",
language = "English",
isbn = "9781450353687",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "541--542",
booktitle = "Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems",
address = "United States",
note = "14th EAI International Conference on Mobile and Ubiquitous Systems (MobiQuitous 2017) : Computing, Networking and Services ; Conference date: 07-11-2017 Through 10-11-2017",
}