CNN based approach for activity recognition using a wrist-worn accelerometer

@article{Panwar2017CNNBA,
  title={CNN based approach for activity recognition using a wrist-worn accelerometer},
  author={Madhuri Panwar and S. Ram Dyuthi and K. Chandra Prakash and Dwaipayan Biswas and Amit Acharyya and Koushik Maharatna and Arvind Gautam and Ganesh R. Naik},
  journal={2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  year={2017},
  pages={2438-2441}
}
In recent years, significant advancements have taken place in human activity recognition using various machine learning approaches. However, feature engineering have dominated conventional methods involving the difficult process of optimal feature selection. This problem has been mitigated by using a novel methodology based on deep learning framework which automatically extracts the useful features and reduces the computational cost. As a proof of concept, we have attempted to design a… CONTINUE READING
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