Abstract
In this document, the creation process of an application is detailed that can use various sensors connected and managed by an Arduino UNO board to capture the movement from the extremities in people with limited movement. It is noteworthy to mention that the results of said application are not discussed here but only the creation process is described. The first part is dedicated to describing the hardware required to use the app’s programmed technology. A brief overview of the Arduino platform is also given followed by a description of the sensors used for calculation and capture of people’s movement. The selection of the sensors is justified, and their operation is presented. The second part focuses on the construction of the application starting by offering a synthesized view of the Unity platform up to the development process. Additionally, the basic concepts to generate the 3D models are explained with the purpose of allowing anyone that reads this document to replicate the project in a simple manner.
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References
Inverse Kinematics - Roblox Developer. http://wiki.roblox.com/index.php?title=Inversekinematics
Mukherjee, S., Paramkusam, D., Dwivedy, S.K.: Inverse kinematics of a NAO humanoid robot using kinect to track and imitate human motion. In: 2015 International Conference on Robotics, Automation, Control and Embedded Systems (RACE). IEEE (2015)
Grochow, K., Martin, S.L., Hertzmann, A., Popovic, Z.: Style-based inverse kinematics. University of Washington (2004)
Inverse Kinematics For Robotic Arms - Alan Zucconi. https://www.alanzucconi.com/2017/04/10/robotic-arms/
Treffers, C., Van Wietmarschen, L.: Position and orientation determination of a probe with use of the IMU MPU9250 and a ATmega328 microcontroller. Electrical Engineering, Mathematics and Computer Science, TUDelft (2016)
Reference image for a gyroscope. https://www.google.com.co/search?q=phone+gyro&source=lnms&tbm=isch&sa=X&ved=0ahUKEwi75eSV1tjaAhXkc98KHck1DwQAUICigB&biw=1920&bih=870#imgrc=EtdQu11uKVo3WM
MagMaster Software download. https://github.com/YuriMat/MagMaster/archive/master.zip
Advanced hard and soft iron magnetometer calibration for dummies. https://diydrones.com/profiles/blogs/advanced-hard-and-soft-iron-magnetometer-calibration-for-dummies
Open-Source-AHRS-With-x-IMU. https://github.com/xioTechnologies/Open-Source-AHRS-With-x-IMU
VRImu Arduino. https://github.com/nviverosb/VRImu
Arduino Android & Microcontrollers/Bluetooth. https://assetstore.unity.com/packages/tools/input-management/android-microcontrollers-bluetooth-16467
Motion Capture Suits. https://optitrack.com/products/motion-capture-suits/
Rokoko Smart Suit. https://www.rokoko.com/en/shop
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Viveros Barrera, N., Salcedo Parra, O.J., Correa Sánchez, L. (2019). Inverse Kinematics Using Arduino and Unity for People with Motor Skill Limitations. In: Renault, É., Mühlethaler, P., Boumerdassi, S. (eds) Machine Learning for Networking. MLN 2018. Lecture Notes in Computer Science(), vol 11407. Springer, Cham. https://doi.org/10.1007/978-3-030-19945-6_9
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DOI: https://doi.org/10.1007/978-3-030-19945-6_9
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