Jan Kleine Deters

TL;DR: A machine learning approach based on six years of meteorological and pollution data analyses is proposed to predict the concentrations of PM2.5 from wind (speed and direction) and precipitation levels and demonstrates that the use of statistical models based on machine learning is relevant to predict PM 2.5 concentrations from meteorological data.

TL;DR: A probabilistic approach based on the development and training of ten Hidden Markov Models is used to discriminate in real time the main faults in the execution of the therapeutic exercises and shows that the models are as reliable as the physiotherapists to discriminate and identify the motion errors.

TL;DR: An experiment evaluates the validity and accuracy of the Kinect motion capture device by a comparison to an accelerometer sensor and shows a significant correlation between both systems, demonstrating that the Kinect is an appropriate tool for the therapeutic purpose of the project.

TL;DR: A cognitive algorithm based on a Hidden Markov Model (HMM) approach to assess in real-time the quality of a human movement recorded through a low-cost motion capture device is proposed.

TL;DR: The present study is part of the ePHoRt project, which is a web-based platform for the rehabilitation of patients after hip replacement surgery, intended to be based on low-cost technologies, especially in terms of motion capture.