Search Results for author:
Found 3 papers, 0 papers with code
Studying the Effects of Deep Brain Stimulation and Medication on the Dynamics of STN-LFP Signals for Human Behavior Analysis
This paper discovers how the performance and accuracy of automated behavior recognition from the LFP signals are affected under different paradigms of stimulation on/off.
An FFT-based Synchronization Approach to Recognize Human Behaviors using STN-LFP Signal
Classification of human behavior is key to developing closed-loop Deep Brain Stimulation (DBS) systems, which may be able to decrease the power consumption and side effects of the existing systems.
A Multiple Kernel Learning Approach for Human Behavioral Task Classification using STN-LFP Signal
Classification of human behavior is an important step in the design of the next generation of DBS systems that are closed-loop.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
