An analysis on BPM and EDA data during a VR task between a mindfulness and non-mindfulness group.

One of the first cut analysis of the MM EEG Motor learning v0.3.

ERDS near final doing graphs

Analysis w. Federica for EMG analysis

A cut on the results based on frequencies as the main interest

Rian's analysis and plots for Accuracy and RT

Acceleration results for Task 1 Learning Curves

LC analysis shows that some variance in rate but not sure if can differentiate performance for Task 3 in Dom Hand Sensor, Acceleration in the X direction.

Changes in movement time can be seen in beginners performing the bronchoscopy trials. The biggest learning in Task 1 is between Trial 1 and 2. In Task 3 its a real linear change in that 1 and 2, 1 and 3.

Near final analysis of ACURA results.

These are the final results of the behavioral ERDS experiment. 26 participants in total. Results show that accuracy increases overtime, RT for accurate trials are decreasing and that concatenation phenomenon is consistent with usual DSP task.

Using long format for ERDS modeled with RT. Here we split frequencies instead of channels.

Apr 2019 last visit.

A main of Alpha/Theta power: Group x RoI x Session

Concatenation analysis of 5 real subjects for foot-step task

Dance step DSP of 6 particpants. Linear relationship of RT and workload.

This is an analysis of Motor Sequence Learning based on a step task. ***PS DO NOT REPLICATE AS SOME DATA HAVE BEEN SIMULATED IN THIS ANALYSIS. The basis of this analysis is only for statistical training.

This is an analysis of Motor Sequence Learning based on a step task. ***PS DO NOT REPLICATE AS SOME DATA HAVE BEEN SIMULATED IN THIS ANALYSIS. The basis of this analysis is only for statistical training.