@inproceedings{lokare_samadi_zhong_gonzalez_mohammadzadeh_lobaton_2017, title={Energy-efficient activity recognition via multiple time-scale analysis}, url={http://dx.doi.org/10.1109/ssci.2017.8285176}, DOI={10.1109/ssci.2017.8285176}, abstractNote={In this work, we propose a novel power-efficient strategy for supervised human activity recognition using a multiple time-scale approach, which takes into account various window sizes. We assess the proposed methodology on our new multimodal dataset for activities of daily life (ADL), which combines the use of physiological and inertial sensors from multiple wearable devices. We aim to develop techniques that can run efficiently in wearable devices for real-time activity recognition. Our analysis shows that the proposed approach Sequential Maximum-Likelihood (SML) achieves high F1 score across all activities while providing lower power consumption than the standard Maximum-Likelihood (ML) approach.}, booktitle={2017 IEEE Symposium Series on Computational Intelligence (SSCI)}, publisher={IEEE}, author={Lokare, N. and Samadi, S. and Zhong, Boxuan and Gonzalez, L. and Mohammadzadeh, F. and Lobaton, E.}, year={2017}, pages={1466–1472} }
 @inproceedings{lokare_gonzalez_lobaton_2016, title={Comparing wearable devices with wet and textile electrodes for activity recognition}, url={http://dx.doi.org/10.1109/embc.2016.7591492}, DOI={10.1109/embc.2016.7591492}, abstractNote={This paper explores the idea of identifying activities from muscle activation which is captured by wearable ECG recording devices that use wet and textile electrodes. Most of the devices available today filter out the high frequency components to retain only the signal related to an ECG. We explain how the high frequency components that correspond to muscle activation can be extracted from the recorded signal and can be used to identify activities. We notice that is possible to obtain good performance for both the wet and dry electrodes. However, we observed that signals from the dry textile electrodes introduce less artifacts associated with muscle activation.}, booktitle={2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, publisher={IEEE}, author={Lokare, Namita and Gonzalez, Laura and Lobaton, Edgar}, year={2016}, month={Aug}, pages={3539–3542} }