Feature Selection and Activity Recognition System Using a Single Triaxial Accelerometer

By Piyush Kumar Gupta, T. Dallas. IEEE Transactions on Biomedical Engineering, 2014

328 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/b8ced7ff722faf5ac5fb2c28709be62d931f5337

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Sreenivasan Ramasamy Ramamurthy
2. Nirmalya Roy

In Computer Vision and Pattern Recognition

1. Hanyu Wang
2. Kun Xia
3. Sreenivasan Ramasamy Ramamurthy
4. Nirmalya Roy
5. Jianguang Huang
6. Sakorn Mekruksavanich
7. Anuchit Jitpattanakul

Citations in the corpus

• Recent trends in machine learning for human activity recognition—A survey (2018, methodology): “The authors Gupta and Dallas (2014) have used detrended fluctuation analysis coefficients as features in learning their classifier and Sekine et al. (2002) have used the fractal dimensions of wavelet coefficients to differentiate three different walking styles, age groups, and patients suffering fro”
• LSTM-CNN Architecture for Human Activity Recognition (2020, background): “The paper [21] presented a wearable wireless accelerometer-based activity recognition system and its application in medical detection.”