Robust Human Physical Activity Recognition Using Smartphone Sensors

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Yazdian Dehkordi Mahdi; ABEDI ZAHRA; Khani Nasim

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Journal: NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR Year:2020 | Volume:18 | Issue:2 Page(s): 159-164

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Title

Robust Human Physical Activity Recognition Using Smartphone Sensors

Author(s)

Yazdian Dehkordi Mahdi | ABEDI ZAHRA | Khani Nasim | Issue Writer Certificate

Keywords

SmartphoneQ2

GyroscopeQ2

AccelerometerQ1

Human physical activity recognitionQ1

Sensor qualityQ1

Sensor noiseQ1

Abstract

Human physical activity recognition using Gyroscope and Accelerometer sensors of Smartphones has attracted many researches in recent years. In this paper, the performance of principle component analysis feature extraction method and several classifiers including support vector machine, logestic regression, Adaboost and convolutional neural network are evaluated to propose an efficient system for human activity recognition. The proposed system can improve the classification accuracy in comparison with the state of the art researches in this field. The performance of a physical activity recognition system is expected to be robust on different Smartphone platforms. The quality of Smartphone sensors and their corresponding noises vary considerably between different Smartphone models and sometimes within the same model. Therefore, it is beneficial to study the effect of noise on the efficiency of the human activity recognition system. In this paper, the robustness of the investigated classifiers are also studied in various level of Sensor noises to find the best robust solution for this purpose. The experimental results, which is provided on a well-known human activity recognition dataset, show that the support vector machine with averaged accuracy of 96. 34% perform more robust than the other classifiers on different level of Sensor noises.

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APA: Copy

Yazdian Dehkordi, Mahdi, ABEDI, ZAHRA, & Khani, Nasim. (2020). Robust Human Physical Activity Recognition Using Smartphone Sensors. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, 18(2 ), 159-164. SID. https://sid.ir/paper/401878/en

Vancouver: Copy

Yazdian Dehkordi Mahdi, ABEDI ZAHRA, Khani Nasim. Robust Human Physical Activity Recognition Using Smartphone Sensors. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR[Internet]. 2020;18(2 ):159-164. Available from: https://sid.ir/paper/401878/en

IEEE: Copy

Mahdi Yazdian Dehkordi, ZAHRA ABEDI, and Nasim Khani, “Robust Human Physical Activity Recognition Using Smartphone Sensors,” NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, vol. 18, no. 2 , pp. 159–164, 2020, [Online]. Available: https://sid.ir/paper/401878/en

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