CFP last date
20 December 2024
Reseach Article

Statistical based Neural Network in Human Activity Recognition

by Mohammad Pivezhandi, Baback Mazloom-Nezhad Maybodi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 124 - Number 12
Year of Publication: 2015
Authors: Mohammad Pivezhandi, Baback Mazloom-Nezhad Maybodi
10.5120/ijca2015905678

Mohammad Pivezhandi, Baback Mazloom-Nezhad Maybodi . Statistical based Neural Network in Human Activity Recognition. International Journal of Computer Applications. 124, 12 ( August 2015), 1-5. DOI=10.5120/ijca2015905678

@article{ 10.5120/ijca2015905678,
author = { Mohammad Pivezhandi, Baback Mazloom-Nezhad Maybodi },
title = { Statistical based Neural Network in Human Activity Recognition },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 124 },
number = { 12 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume124/number12/22153-2015905678/ },
doi = { 10.5120/ijca2015905678 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:14:25.044742+05:30
%A Mohammad Pivezhandi
%A Baback Mazloom-Nezhad Maybodi
%T Statistical based Neural Network in Human Activity Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 124
%N 12
%P 1-5
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research proposed an efficient method in classification of Human Activity Recognition tasks. The evaluated tuned models show higher than 99 percent mean accuracy and gain more training and testing accuracy in comparison to previous studies. Dimensionally reduction have been introduced based on P-value evaluation in feature space. Finally a hybrid model that compressed statistically in feature space alongside with Neural Network architecture have been proposed. The final model could be used as best architecture of hardware implementation in gesture recognition applications.

References
  1. Saisakul a, Anthony S Atkins, and Hongnian Yu. Activity classification using a single wrist-worn accelerometer. In Software, Knowledge Information, Industrial Management and Applications (SKIMA), 2011 5th International Conference on, pages 1–6. IEEE, 2011.
  2. Esteban Alfaro, Matias G´amez, and Noelia Garcia. Adabag: An r package for classification with boosting and bagging. Journal of Statistical Software, 54(2):1–35, 2013.
  3. Leo Breiman. Out-of-bag estimation. Technical report, Citeseer, 1996.
  4. Bradley Efron and Robert J Tibshirani. An introduction to the bootstrap. CRC press, 1994.
  5. Miikka Ermes, Juha Parkka, Jani Mantyjarvi, and Ilkka Korhonen. Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions. Information Technology in Biomedicine, IEEE Transactions on, 12(1):20–26, 2008.
  6. HAR. Human activity recognition. http://groupware.les.inf.puc-rio.br/har.
  7. Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The elements of statistical learnin, 2009.
  8. Benjamin Hofner, Andreas Mayr, Nikolay Robinzonov, and Matthias Schmid. Model-based boosting in r: a hands-on tutorial using the r package mboost. Computational Statistics, 29(1-2):3–35, 2014.
  9. Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. An introduction to statistical learning. Springer, 2013.
  10. Andy Liaw and Matthew Wiener. Classification and regression by randomforest. R news, 2(3):18–22, 2002.
  11. Jun Nishimura and Tadahiro Kuroda. Multiaxial haar-like feature and compact cascaded classifier for versatile recognition. Sensors Journal, IEEE, 10(11):1786–1795, 2010.
  12. Greg Ridgeway. Generalized boosted models: A guide to the gbm package. Update, 1(1):2007, 2007.
  13. Liu Rong and Liu Ming. Recognizing human activities based on multi-sensors fusion. In Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on, pages 1–4. IEEE, 2010.
  14. Eduardo Velloso, Andreas Bulling, Hans Gellersen, Wallace Ugulino, and Hugo Fuks. Qualitative activity recognition of weight lifting exercises. In Proceedings of the 4th Augmented Human International Conference, pages 116–123. ACM, 2013.
  15. Yuting Zhang, Stacey Markovic, Inbal Sapir, Robert C Wagenaar, and Thomas DC Little. Continuous functional activity monitoring based on wearable tri-axial accelerometer and gyroscope. In Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2011 5th International Conference on, pages 370–373. IEEE, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Dimensionality reduction Human Activity Recognition Neural network P-value extension Statistical Analysis