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  Brain Signal Decoding
Real-time decoding of different levels of force
Parkinson's disease (PD) patients implanted with deep brain stimulation (DBS) electrodes in the Subthalamic Nucleus (STN) brain area attempts to extend the leg with 3 different force levels (0%, 33%, 66% of maximum force) while sitting. The decoder takes local field potentials (LFP) signals from the STN and predicts the intended force level in real time while the patient is executing the action.






Offline decoding of walking and freezing of gait
PD patients implanted with DBS electrodes in STN area of the brain walks with two different lengths of stride. Occasionally, the patient exhibits freezing of gait (FoG). The decoder takes as input the LFP signals from STN to classify different states of walking and FoG.






Brain signal dynamics while walking
PD patients implanted with DBS electrodes attempts in the STN brain area walks on the ground with different strides and their corresponding brain dynamics are reflected on LFP signals.






Non-invasive real-time decoding of human brain signals
A paraplegic subject attempts to move his own paralyzed legs. His intention is recognized and feedback for the corresponding leg is shown in real time.






Brain-controlled lower-limb exoskeleton
5 able-bodied subjects perform a 3-way control (front, turn left & right) of a powered lower-limb exoskeleton using motor imagery.






Representation Learning
Hierarchical task representation learning
The computer learns hierarchical representation of a task by observing human demonstrator performing a series of actions.




iCub predictive action execution using music structure

Musical primitives composed and produced by Jonas Golland





Fun stuff during my student years
Micromouse - Quantum (handmade custom circuit design)



Line Tracer - Goombeng (handmade custom circuit design)



Lightning in Rhythm
The swinging rhythm of a human body is captured at 10 Hz and reproduced in the form of thunder and lightning with electric discharges at 50,000 V. Created for a demonstration at Vision Language Research course in Fine Arts department.