Hand-tremor Frequency Estimation in Videos

Hand-tremor Frequency Estimation in Videos

Zheng, Jian (TU Delft Electrical Engineering, Mathematics and Computer Science)

van Gemert, J.C. (mentor)
Pintea, S. (mentor)

Delft University of Technology

Electrical Engineering | Embedded Systems

2018-08-22

We focus on the problem of estimating human hand-tremor frequency from input RGB video data. Estimating tremors from video is important for non-invasive monitoring, analyzing and diagnosing patients suffering from motor-disorders such as Parkinson’s disease. We consider two approaches for hand-tremor frequency estimation: (a) a Lagrangian approach where we detect the hand at every frame in the video, and estimate the tremor frequency along the trajectory; and (b) an Eulerian approach where we first localize the hand, we subsequently remove the large motion along the movement trajectory of the hand, and we use the video information over time encoded as intensity values or phase information to estimate the tremor frequency. We estimate hand tremors on a new human tremor dataset, TIM-Tremor, containing 55 tremor patient recordings together with: associated ground truth accelerometer data from the most affected hand, RGB video data, and aligned depth data, as well as a multitude of more dynamic tasks, involving larger motion of the hands.

Video hand-tremor analysis
Phase-based tremor frequency detection
Human tremor datase
Eulerian hand tremors

http://resolver.tudelft.nl/uuid:e32aabd8-6bd4-4dc5-bf82-0508702f67a3

Student theses

master thesis

© 2018 Jian Zheng