NCSU-ADL [Date release: November, 2017] – This dataset contains motion and physiological measurements from individuals performing specific activities of daily life at their personal pace. Please cite [1] if using this dataset in your research. Subjects 059, 292, 380, 503 and 805 were used in the analysis of [1]. Subjects 059, 274, 292, 380, 390, 454, 503, 805, 875 and 909 were used in the analysis of [2].

Publications

1. N. Lokare, B. Zhong and E. Lobaton, “Activity-Aware Physiological Response Prediction using Wearable Sensors,” Inventions, 2(4), 2017.
2. N. Lokare, S. Samadi, B. Zhong, L. Gonzalez, F. Mohammadzadeh, E. Lobaton, “Energy-Efficient Activity Recognition via Multiple Time-Scale Analysis,” IEEE Symp. Series on Computational Intelligence (SSCI), 2017.