Petr Volf

Background

About Petr Volf

In the scope of my research, I focus on the development and utilization of MoCap (Motion Capture) systems and systems for measuring biosignals of the body. I have experience from my work at Kinmedica, where I measured the movement of professional athletes using the optical MoCap system Qualysis. I preprocessed motion data for activities such as cycling, golf swings, softball pitching, implemented new algorithms, and created models. As part of my research, I contributed to the design of several MoCap systems and gained experience in the development and processing of data from stabilometric platforms. Additionally, in a collaborative project with Taiwan Tech, I processed data from basketball players during bilateral and unilateral double jump tests using nonlinear analysis methods. For my doctoral thesis, I investigated eye and head movements analysis during eccentric human rotation in collaboration with the 2nd Faculty of Medicine, Charles University. This analysis is used in evaluating the function of the vestibular apparatus. In this work, I proposed a system for measuring the movement of vestibular labyrinth, including the implementation of a modified Poincaré plot for analyzing per-rotational and post-rotational nystagmus. I have also been involved in the design of equipment for measuring the movement of animals on a treadmill, which utilized camera systems. Additionally, I worked on the diagnostic and training-rehabilitation extension of the car simulator for people with brain damage, where, in addition to biosignals, I evaluated data from the simulator. Regarding the processing of other biosignals, I have experience working with ECG, EEG, EMG, and IMU data, actively participating in the development of custom hardware solutions. Currently, my focus has been on analyzing the aforementioned motion data and biosignals for analog missions and military/emergency services, where AR/VR methods are employed along with data aggregation for AI to assess physical condition, mental state, and cognitive load.