Abstract
By using the most rudimentary microcontroller chips, that receive data from sensors, and transmit the data to a computer system, thorough a virtual serial port, motion of many objects, bodies and joints can be captured. Capturing the motion and reproducing it live is not the only destination for the data usage. Recording and studying the motion data, can reduce a lot of work in a wide range of domains. Using the simplest methods to capture the data, also means making it so widely accessible for learning, editing and also developing systems that use very little processing power, granting data access for the less efficient computers. We propose using the MPU-6050 MEMS sensor in a dual instance, and the Arduino UNO microcontroller, connected to a computer for data acquisition, to capture the motion of a human arm, and reproduce it in a projected environment. Other experiments, conducted by other researchers and developers have used a higher number of sensors, and the data acquisition and recording systems were much more complex, but our research reduced the number of sensors to just two. One of the high impact innovations brought by this system, in particular, is that we’ve virtually hooked the end of one sensor to the tip of the other, creating a virtual motion chain.
Highlights
During the last decade, multiple approaches on the techniques and methods of motion capture have been the guidelines of the motion capture processes, regardless of the work domains they've been incorporated in [1]
Multiple inertial sensors [2,3], ranging from accelerometers, magnetometers, gyroscopes, cameras, infrared sensors have all been put to the test in the race to which of the sensors were most fit for the job [4,5,6]
The technique we are using is, one that employs the MPU6050 a 3-axis accelerometer and gyroscope sensor, capable of communication with the I2C interface, requiring only two connections. Two such devices are connected to an Arduino UNO development board, all these, connected to a computer's USB port, while using the Arduino IDE and the Processing IDE
Summary
Multiple approaches on the techniques and methods of motion capture have been the guidelines of the motion capture processes, regardless of the work domains they've been incorporated in [1]. Multiple inertial sensors [2,3], ranging from accelerometers, magnetometers, gyroscopes, cameras, infrared sensors have all been put to the test in the race to which of the sensors were most fit for the job [4,5,6]. These sensors each have their own way of perceiving motion or displacement. In the field of virtual reality, the benefit can be indoor exercising in confined spaces, yet give the users (patients) better insight [16] of their movement
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