PROTOTYPE DESIGN OF IMU-BASED MOTION CAPTURE FOR SPORTS BIOMECHANIC INSTRUMENTATION

The limited access to many research equipment is one of the many obstacles to the development of sports science, especially in the field of sports biomechanics. In this field, when the focus is measuring and analyzing athlete’s movement using specified tools, the limitation makes it even harder....

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Bibliographic Details
Main Author: Ibrahim, Targhib
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/66878
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Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:The limited access to many research equipment is one of the many obstacles to the development of sports science, especially in the field of sports biomechanics. In this field, when the focus is measuring and analyzing athlete’s movement using specified tools, the limitation makes it even harder. Many cause these phenomena, but some reasons that most people believe are the absent of local producer and the pricy cost of the equipment. To overcome this, it is necessary to conduct research and design prototypes to solve this problem. One of most popular equipment that often used in sports biomechanics is motion capture. This tool can measure position of the athlete and determine their acceleration. Unfortunately, most company used an industrial-grade components such as cameras and sensors thus the high cost. However, there are several low-cost alternatives to those components. One of them are inertial sensor or IMU. This sensor will be the main focus of this design, specifically the 9-dof IMU or MARG. There are several weaknesses to this alternative such as the cumulative error. So, in the process of designing this prototype, several calibration algorithms will be used. Madgwick filter and I2S calibration will be the main focus of this project. To complete the system, the prototype also consists of user interface that build on python programming, with I2C and UDP/IP communication protocol. Most of subsystem can perform normally. The average calibration bias of the sensor is 33.8, 5.861, -65.212 for accelerometer, -0.529, 0.038, -1.01 for gyroscope, and 192.1, 143.4, -241.971 for magnetometer.