The 11th International Conference on Mobile Systems and Pervasive Computing (MobiSPC-2014) A Study on Human Activity Recognition Using Accelerometer Data from Smartphones

By Akram Bayat, Marc Pomplun, Duc-Anh Tran. 2014

480 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9baa45693e37d6f14a9a0efae7c5f552808b36cb

How researchers see this paper

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

1. Erhan Bulbul
2. Aydın Çetin
3. Ibrahim Alper Dogru
4. Samer Mohammed
5. Latifa Oukhellou
6. Faicel Chamroukhi
7. Ferhat Attal
8. Yacine Amirat

Citations in the corpus

• Human Action Recognition From Various Data Modalities: A Review (2020, unknown): “used to perform human activity analysis [268].”
• Human Activity Recognition Using Smartphones (2018, background): “studied on human activity recognition with accelerator signals[1].”
• Physical Human Activity Recognition Using Wearable Sensors (2015, methodology): “…and at wrist level [24] and at the level of hip IMU sensors including accelerometers and gyroscopes, placed at the trunk and the shank levels lying, sitting, standing, and walking, as well as distinguishing the body elevation such as flat, elevator down, elevator up, stairs down and stairs up.”