Simulated motor unit action potentials (MUAPs) for right forearm model

This dataset consist of 4 pickle files containing model parameters for motor unit action potentials (MUAPs) simulation as well as corresponding MUAPs. The simulation was performed with Neurodec's Myoelectric Digital Twin Software (http://neurodec.ai/).How to access data in python:import pickleimport numpywith open('model_0.pkl', 'rb') as f:  model = pickle.load(f)The model is a simple structure of lists and dictionaries of the following structure:MODEL|_ properties |_ sampling_frequency |_ recruitment_rate |_ excitation_frequency_limits |_ tissue_conductivities |_ muscles |_ bones |_ fat |_ skin|_ electrodes |_ electrode_centers |_ electrode_radii |_ electrode_normals|_ skin |_ surface |_ vertices |_ triangles|_ [bones] |_ surface |_ vertices |_ triangles|_ [muscles] |_ label |_ surface |_ vertices |_ triangles |_ [motor_units] |_ [fibers] |_ tendon_1_ratio |_ tendon_2_ratio |_ velocity |_ neuromuscular_junction |_ vertices |_ muapHere are examples of how some model data can be accessed:model['properties']['tissue_conductivities']['skin'] - get the value of the skin electric conductivity used in the modelmodel['muscles'][1]['label'] - get the label of the muscle with index 1Similarly, the MUAP for a specific motor unit can be accessed as follows:muap = model['muscles'][0]['motor_units'][10]['muap']A single muap is a 2d numpy array where first dimension corresponds to the number of electrodes, and the second to the number of time samples.