Implementasi Algoritma Complementary Filter untuk Merancang Bangun Interaksi Manusia dan Smartphone Menggunakan Gerakan Kepala

DOI: https://doi.org/10.32722/pt.v19i3.3024

Pingky Alfa Ray Leo Lede

Abstract


This study proposes an approach to design and build interaction systems for smartphone users with hand disabilities using the user's head movements through the implementation of the fusion complementary filter algorithm to get the angle of orientation and position of the user’s head. The main objective of this experimental research is to get the best constant function of complementary filters that have the highest accuracy result. The results of this study indicate that the fusion complementary filter algorithm can be used to measure the angle of the user's head movements using a combination of 3 sensors; namely, the accelerometer, gyroscope, and magnetometer, with the best constants function are 0.99 for the gyroscope and 0.01 for the accelerometer. Complementary filter performance results using fusion of 3 sensors to measure the user's head angle obtained from the calculation of the root mean squared error (RMSE) with an average value of 0.364 on the x-axis (roll), 0.578 on the y-axis (pitch), and 0.767 on the z-axis (yaw).

Keywords


Interaksi Manusia dan Smarphone; Mesin Cerdas; Complementary Filter; Algoritma Fusion

References


Kim, J., Park, H., Bruce, J., Rowles, D., Holbrook, J., Nardone, B., Ghovanloo, M., (2016), Assessment of the Tongue-Drive System using a Computer, a Smartphone, and a Powered-Wheelchair by People With Tetraplegia, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(1), 68–78, http://doi.org/10.1109/TNSRE.2015.2405072.

Lavalle, S. M., Yershova, A., Katsev, M., Antonov, M., (2014), Head tracking for the Oculus Rift, Proceedings - IEEE International Conference on Robotics and Automation, 187–194.

Lopez, M. B., Hannuksela, J., Silven, O., Fan, L., (2012), Head-Tracking Virtual 3-D Display for Mobile Devices, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 27–34.

Masters, M., Osborn, L., Thakor, N., (2015), Real-Time Arm Tracking for HMI Applications. IEEE.

Naizhong, Z., Jing, W., Jun, W., (2015), Hand-Free Head Mouse Control Based on Mouth Tracking, (ICCSE), 707–713.

Naizhong, Z., Jing, W., Jun, W., (2015), Hand-Free Head Mouse Control Based on Mouth Tracking, (ICCSE), 707–713.

Valeriani, D., & Matran-Fernandez, A., (2015), Towards a Wearable Device for Controlling a Smartphone with Eye Winks, 7th Computer Science and Electronic Engineering Conference (CEEC15), 41–46, http://doi.org/10.1109/CEEC.2015.7332697


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