Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects
- DOI
- 10.3390/s22030756
- Published
- 2022-01-19
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s22030756,
title = {Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects},
author = {Jithin S. Sunny and C. Pawan K. Patro and Khushi Karnani and Sandeep C. Pingle and Feng Lin and Misa Anekoji and Lawrence D. Jones and Santosh Kesari and Shashaanka Ashili},
year = {2022},
journal = {Sensors},
doi = {10.3390/s22030756},
url = {https://doi.org/10.3390/s22030756}
}RIS
TY - JOUR TI - Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects AU - Jithin S. Sunny AU - C. Pawan K. Patro AU - Khushi Karnani AU - Sandeep C. Pingle AU - Feng Lin AU - Misa Anekoji AU - Lawrence D. Jones AU - Santosh Kesari AU - Shashaanka Ashili PY - 2022 JO - Sensors DO - 10.3390/s22030756 UR - https://doi.org/10.3390/s22030756 ER -
APA
Sunny, J. S., Patro, C. P. K., Karnani, K., Pingle, S. C., Lin, F., Anekoji, M., Jones, L. D., Kesari, S., & Ashili, S. (2022). Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects. Sensors. https://doi.org/10.3390/s22030756
Source records
- crossref · retrieved 2026-09-24T21:50:33.627Z