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Vol. 5, No. 1, February 2020

Performance Comparisson Human Activity Recognition Using Simple Linear Method

https://doi.org/10.22219/kinetik.v5i1.1025
Wahyu Andhyka Kusuma
Universitas Muhammadiyah Malang
Zamah Sari
Universitas Muhammadiyah Malang
Agus Eko Minarno
Universitas Muhammadiyah Malang
Hardianto Wibowo
Universitas Muhammadiyah Malang
Denar Regata Akbi
Universitas Muhammadiyah Malang
Naser Jawas
University of Warwick

Corresponding Author(s) : Wahyu Andhyka Kusuma

kusuma.wahyu.a@gmail.com

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 5, No. 1, February 2020

Abstract

Human activity recognition (HAR) with daily activities have become leading problems in human physical analysis. HAR with wide application in several areas of human physical analysis were increased along with several machine learning methods. This topic such as fall detection, medical rehabilitation or other smart appliance in physical analysis application has increase degree of life. Smart wearable devices with inertial sensor accelerometer and gyroscope were popular sensor for physical analysis. The previous research used this sensor with a various position in the human body part. Activities can classify in three class, static activity (SA), transition activity (TA), and dynamic activity (DA). Activity from complexity in activities can be separated in low and high complexity based on daily activity. Daily activity pattern has the same shape and patterns with gathering sensor. Dataset used in this paper have acquired from 30 volunteers.  Seven basic machine learning algorithm Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosted and K-Nearest Neighbor. Confusion activities were solved with a simple linear method. The purposed method Logistic Regression achieves 98% accuracy same as SVM with linear kernel, with same result hyperparameter tuning for both methods have the same accuracy. LR and SVC its better used in SA and DA without TA in each recognizing.

Keywords

Human Activity Recognition Physical Analysis Linear Method
Kusuma, W. A., Sari, Z., Minarno, A. E., Wibowo, H., Akbi, D. R., & Jawas, N. (2020). Performance Comparisson Human Activity Recognition Using Simple Linear Method. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 5(1), 1-10. https://doi.org/10.22219/kinetik.v5i1.1025
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