Activity Recognition Using Multiple Inertial Measurement Units

Basketball Activity Recognition using Wearable Inertial Measurement Units

Analysis of human movement is a growing research area within the field of sport monitoring which aims to enhance the performance of athletes, predicting injuries or optimizing training programs. Camera-based techniques are the most spread method to evaluate although frequently this method can be cumbersome and, furthermore, specific movements where performance is analyzed are not possible to di...

Human Activity Recognition Using Inertial/Magnetic Sensor Units

This paper provides a comparative study on the different techniques of classifying human activities that are performed using bodyworn miniature inertial and magnetic sensors. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), the least-squares method (LSM), the k-nearest neighbor algorithm (k-NN), dynamic time warping (DTW), support vector ...

Accurate Position Tracking Using Inertial Measurement Units

Indoor Positioning Using Inertial Measurement Units

With the increase in the number of smart phone users worldwide there comes a high demand for smart phone based location systems. Within the project “Indoor positioning using inertial measurement units” an android application has been developed wherein the position of the smart phone user with respect to the floor environment is determined. This has been achieved using the smart phone sensors st...

Data Fusion Algorithms for Multiple Inertial Measurement Units

A single low cost inertial measurement unit (IMU) is often used in conjunction with GPS to increase the accuracy and improve the availability of the navigation solution for a pedestrian navigation system. This paper develops several fusion algorithms for using multiple IMUs to enhance performance. In particular, this research seeks to understand the benefits and detriments of each fusion method...