Date of Award
Thesis and Dissertation
Master of Science (MS)
School of Kinesiology and Recreation
Adam E Jagodinsky
Background: Recent advances in the field of wearable technology are now at a peak in the sports field and the medical field. The validity, reliability, and application of such systems are still under research and yet to be revealed.
Purpose: This study aims to design and constructing the Inertial Measurement Unit (IMU) hardware with the required software to collect accelerometer data for potential use in human movement studies and test the efficacy of the collected IMU accelerometer data by comparing it with the motion capture data.
Methods: In this study, the IMU sensor is coupled with the Arduino, loaded with software code used for data collection. To test the efficacy, the sensor was placed on the lumbar region during quiet standing task and an exaggerated sway of random high amplitude anteroposterior and mediolateral deviations of the model in tandem stance. A correlation analysis was conducted to assess the relationship between the measured signals as a form of comparison.
Results: The construction of the sensor was successful with certain limitations and the correlation analysis results varied for across trials. Comparisons conducted for the X and Y axes values ranged from weak to strong, while Z axis comparisons were generally weak.
Conclusions: The aims of the study were successful, although the results were not anticipated. The IMU sensor appears to be viable for biofeedback applications. However, the acceleration patterns varied across trials, which is most likely attributed to discrepancies in sampling frequency, accumulated noise, and signal processing procedures.. Further research is needed to optimize data collection and processing procedures when constructing the IMU for human movement research.
Vasudevaraja, Umaiyaal, "Developing And Comparing Sensor For Movement Analysis And Biofeedback" (2020). Theses and Dissertations. 1314.
Available for download on Thursday, November 17, 2022