This dataset was obtained from the IBM Machine Learning Professional Certificate program offered by Coursera. You can see the original dataset in the following link:

https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones

The difference of the current dataset is that this contains 10299 instances which corresponds to merging the training and testing instances of the above dataset published by UCI Machine Learning. The main reason of publishing this data was toa achieve an even higher accuracy as we are working with significatively much more instances than in the original one. I encourage you to see the differences!, however all credits are deserved to UCI.

Attribute information

For each record in the dataset the following is provided:

• Triaxial acceleration from the accelerometer (total acceleration) and the estimated body acceleration.

• Triaxial Angular velocity from the gyroscope.

• A 561-feature vector with time and frequency domain variables.

• Its activity label.

• An identifier of the subject who carried out the experiment.

Relevant papers

Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine. International Workshop of Ambient Assisted Living (IWAAL 2012). Vitoria-Gasteiz, Spain. Dec 2012

Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge L. Reyes-Ortiz. Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic. Journal of Universal Computer Science. Special Issue in Ambient Assisted Living: Home Care. Volume 19, Issue 9. May 2013

Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine. 4th International Workshop of Ambient Assited Living, IWAAL 2012, Vitoria-Gasteiz, Spain, December 3-5, 2012. Proceedings. Lecture Notes in Computer Science 2012, pp 216-223.

Jorge Luis Reyes-Ortiz, Alessandro Ghio, Xavier Parra-Llanas, Davide Anguita, Joan Cabestany, Andreu Català. Human Activity and Motion Disorder Recognition: Towards Smarter Interactive Cognitive Environments. 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges, Belgium 24-26 April 2013.

Citation

Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges, Belgium 24-26 April 2013.