Medical electronics part 9b Electroencephalography (EEG)

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1 Medical electronics part 9b (EEG) Prezentacja multimedialna współfinansowana przez Unię Europejską w ramach Europejskiego Funduszu Społecznego w projekcie pt. Innowacyjna dydaktyka bez ograniczeń - zintegrowany rozwój Politechniki Łódzkiej - zarządzanie Uczelnią, nowoczesna oferta edukacyjna i wzmacniania zdolności do zatrudniania osób niepełnosprawnych Politechnika Łódzka, ul. Żeromskiego 116, Łódź, tel. (042)

2 2 Paweł Poryzała Medical Electronics Division Institute of Electronics Lodz University of Technology room 203, B9 building Four lectures (originally prepared by Marcin Byczuk):, Physiological transducers, Biomedical signal instrumentation, Noise, interferences and artifacts.

3 3 What is EEG? (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations resulting from ionic current flows within the neurons of the brain. (Niedermeyer E. and da Silva F.L. (2004). : Basic Principles, Clinical Applications, and Related Fields. Lippincot Williams & Wilkins) 1st used in humans by the German psychiatrist Hans Berger in 1924 (first report published in 1929), a trace of voltage fluctuations versus time recorded from electrodes placed over scalp in a specific array, Voltage >>> average activity of many neurons over a large area (the more synchronized population of neurons, the greater their contribution to the EEG), required amplification (amplitude of electrical activity measured on the scalp is about 50µV, measured on the brains surface is about 1-2mV), deep parts of the brain are not well sampled

4 What is EEG? 4

5 4 How to measure brain activity? method EEG MEG PET fmri time resolution 1 ms 1 ms 1 min 5 s spatial resolution 1 cm 5 cm 5 mm 1 5 mm cons only cerebral cortex, complex signal interpretation poor spatial resolution, complex signal interpretation, high price only blood flow, short-life radionuclides, high price only blood flow, high price pros relatively cheap, easy to implement structures beneath cerebral cortex functional analysis, medical imaging functional analysis, medical imaging MEG >>> Magnetoencephalography PET >>> Positron Emission Tomography fmri >>> Functional Magnetic Resonance Imaging

6 Measurement of the EEG signals 6 Bipolar (A) and unipolar (B) measurement Source: CONCLUSION: Recorded EEG waveform depends on the location and montage of the measurement electrodes!!!

7 EEG lead systems 7 Motivation: compare measurements for different patients / from different hospitals First standard: electrode system was established in 1958 The placement of electrodes is based on anatomic landmarks on the skull: nasion (Nz), which is the delve at the top of the nose, level with the eyes, inion (Iz), which is the bony lump at the base of the skull on the midline at the back of the head, left and right preauricular points (LPA and RPA).

8 8 EEG lead systems system (10%-20% intervals, 21 electrodes) Source: bci/laurabig.jpg Source: A = Ear lobe, C = central, Pg = nasopharyngeal, P = parietal, F = frontal, Fp = frontal polar, O = occipital, even numbers on the right, odd numbers on the left

9 EEG lead systems system (10%-10% intervals, 74 electrodes) Source: Source: four electrodes (T 7, T 8, P 7, and P 8 ) have different names compared to the system (marked black)

10 EEG lead systems system (10%-10% intervals, 74 electrodes) Black circles indicate positions of the original system, gray circles indicate additional positions introduced in the extension.

11 EEG lead systems system (10%-5% intervals, around 345 electrodes) Black circles indicate positions of the original system, gray circles indicate system positions, dots and white circles indicate 10-5 system electrodes. Black + gray + white circles = 145 electrodes.

12 EEG lead systems channel system Black circles indicate positions of the original system, gray circles indicate system positions, dots and white circles indicate 10-5 system electrodes. Black + gray + white circles = 128 electrodes.

13 EEG lead systems channel system Source:

14 Structure of the brain 14 Brain lobes Source: ervoussystem/brain/cerebrum_1.gif

15 Structure of the brain 15 Functional areas Source: ervoussystem/brain/brain_2.gif

16 16 Structure of the brain Somatosensory cortex and motor cortex Source: somatosenzoricky_a_motoricky_homunculus.jpg

17 Structure of the brain 17 Homunculus (little man) Source:

18 18 Characteristics of the EEG signal Amplitude: 0 50uV pp (max. 300uV pp ) Frequency band: Hz (max. 100Hz) Power of frequency components proportional to 1/f Source:

19 19 Characteristics of the EEG signal Components of the EEG signal: EEG noise spontaneuos activity of neurons Brainwaves quasi-periodic components Evoked potentials responses to external stimulus or mental task: Event-Related Potentials (ERP) Event-Related Synchonization/Desynchronization (ERS/ERD) Auditory Evoked Potentials (AEP) Somatosensory Evoked Potentials (SEP) Visual Evoked Potentials (VEP) Steady-State Visual Evoked Potentials (SSVEP)

20 Components of the EEG signal 20 Brainwaves Source:

21 Components of the EEG signal 21 Event-Related Potentials Source:

22 Components of the EEG signal 22 Steady-State Visual Evoked Potentials Fourier Transform SSVEP f x f x Source: index.shtml?main=/tbi/brain.html

23 Processing and analysis of the EEG signal 23 Time domain: band-pass filtering averaging correlation Frequency domain: Fourier transform power spectral density Time and frequency: wavelet transform Short-time Fourier Transform (STFT)

24 Processing and analysis of the EEG signal 24 EEG mapping Source:

25 25 Applications of the EEG signals Medicine Rehabilitation Research Therapy Neurofeedback Brain-Computer Interface

26 Applications of the EEG signals 26 Neurofeedback Source:

27 Applications of the EEG signals 27 Brain-Computer Interface (BCI) Source:

28 Brain-Computer Interface 28 ERS/ERD based BCI (TU Graz, Austria) Event Related Desynchronization and Event Related Synchronization for right and left arm movement used to control the device.

29 Brain-Computer Interface 29 P300 based BCI (TU Graz, Austria) Event Related Potentials

30 Brain-Computer Interface 30 SSVEP based BCI (LUT, Poland)

31 31 Summary EEG lead systems EEG meaurements Structure of the brain Characteristics of the EEG signal Components of the EEG signal Processing and analysis of the EEG signal Applications of the EEG signal

32 Medical electronics part 9b (EEG) Prezentacja multimedialna współfinansowana przez Unię Europejską w ramach Europejskiego Funduszu Społecznego w projekcie pt. Innowacyjna dydaktyka bez ograniczeń - zintegrowany rozwój Politechniki Łódzkiej - zarządzanie Uczelnią, nowoczesna oferta edukacyjna i wzmacniania zdolności do zatrudniania osób niepełnosprawnych Politechnika Łódzka, ul. Żeromskiego 116, Łódź, tel. (042)