2.1.2.7. Medical Data

2.1.2.7.1. Main Functions

teaspoon.MakeData.DynSysLib.medical_data.EEG(SampleSize=5000, dynamic_state='normal')

The EEG signal was taken from andrzejak et al. [1]. Specifically, the first 5000 data points from the EEG data of a healthy patient from set A (file Z-093) was used and the first 5000 data points of a patient experiencing a seizure from set E (file S-056) was used (see figure below for case during seizure).

Parameters:

• SampleSize (Optional[int]) – length of sample at end of entire time series

• dynamic_state (Optional[str]) – Set dynamic state as either ‘normal’ or ‘seizure’.

Returns:

Array of the time indices as t and the simulation time series ts

Return type:

array

References

[1]

Ralph G Andrzejak, Klaus Lehnertz, Florian Mormann, Christoph Rieke, Peter David, and Christian E Elger. Indications of nonlinear deterministic and nite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state. Physical Review E, 64(6):061907, 2001.

teaspoon.MakeData.DynSysLib.medical_data.ECG(dynamic_state='normal')

The Electrocardoagram (ECG) data was taken from SciPys misc.electrocardiogram data set. This ECG data was originally provided by the MIT-BIH Arrhythmia Database [2]. We used data points 3000 to 5500 during normal sinus rhythm and 8500 to 11000 during arrhythmia (arrhythmia case shown below in figure).

Parameters:

dynamic_state (Optional[str]) – Set dynamic state as either ‘normal’ or ‘seizure’.

Returns:

Array of the time indices as t and the simulation time series ts

Return type:

array

References

[2]

George B Moody and Roger G Mark. The impact of the mit-bih arrhythmia database. IEEE Engineering in Medicine and Biology Magazine, 20(3):4550, 2001.