1. The Illinois Society of Electroneurodiagnostic Technologists (ISET) Fall Meeting: Electronics Crash Course for Technologists Saturday, November 9, 2013 Michael A. Stein, MD

2. Electronics Crash Course for Technologists Very broad topic. Very broad topic. Illustrate with an example: Illustrate with an example: Digital EEG system. Digital EEG system. Still very broad topic. Still very broad topic. Simplify by using a model system. Simplify by using a model system.

3. Overview Many devices in engineering can be modeled as black box systems: Many devices in engineering can be modeled as black box systems: Input Input Transformation Transformation Output Output

4. Electronics Crash Course for Technologists

6. Overview Input: Input: Electric Field at Scalp Electric Field at Scalp Sensors/Transducers: Sensors/Transducers: EEG electrodes. EEG electrodes. Transformation: Transformation: Filters Filters Analog-to-Digital Converter (ADC) Analog-to-Digital Converter (ADC) Amplifier Amplifier Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Output: Output: Computer Display Computer Display Memory/Digital Storage Media Memory/Digital Storage Media

7. Other Examples of Black Box Designs Sound Recording System: Sound Recording System: Input: Input: Musical Performance Musical Performance Transducer/Sensor Transducer/Sensor Microphone Microphone Transformation: Transformation: Filters Filters Amplifiers Amplifiers Analog-to-Digital Converter Analog-to-Digital Converter Output: Output: CD burner CD burner

8. Other Examples of Black Box Designs Sound Playback System: Sound Playback System: Input: Input: Recorded Media (e.g. CD- ROM). Recorded Media (e.g. CD- ROM). Transformation: Transformation: Filters Filters Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Amplifiers Amplifiers Output: Output: Sound at Loudspeakers Sound at Loudspeakers

9. Other Examples of Black Box Designs Cellular Phone Transmission: Cellular Phone Transmission: Input: Input: Transmitted Signal Transmitted Signal Sensor/Transducer: Sensor/Transducer: Telephone microphone Telephone microphone Transformation: Transformation: Radio signal generation Radio signal generation Radio signal modulation Radio signal modulation Output: Output: Transmitted signal at radio tower Transmitted signal at radio tower

10. Other Examples of Black Box Designs Cellular Phone Reception: Cellular Phone Reception: Input: Input: Radio modulated telephone signal at receiving antenna Radio modulated telephone signal at receiving antenna Transformation: Transformation: Demodulation by cellular phone receiver Demodulation by cellular phone receiver Filters Filters Amplifiers Amplifiers Output: Output: Sound at telephone earpiece loudspeaker Sound at telephone earpiece loudspeaker

11. Digital EEG System: Overview Input: Input: Electric Field at Scalp Electric Field at Scalp Sensors/Transducers: Sensors/Transducers: EEG electrodes. EEG electrodes. Transformation: Transformation: Filters Filters Analog-to-Digital Converter (ADC) Analog-to-Digital Converter (ADC) Amplifier Amplifier Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Output: Output: Computer Display Computer Display Memory/Digital Storage Media Memory/Digital Storage Media

12. Digital EEG System: Overview Ideally each stage of the EEG system would reproduce the acquired data without any change with high fidelity. Ideally each stage of the EEG system would reproduce the acquired data without any change with high fidelity. In practice however, each stage introduces an undesired change in the signal recorded due to limitations imposed both biophysically and electronically. In practice however, each stage introduces an undesired change in the signal recorded due to limitations imposed both biophysically and electronically. Input: Input: Electric Field at Scalp Electric Field at Scalp Sensors/Transducers: Sensors/Transducers: EEG electrodes. EEG electrodes. Transformation: Transformation: Filters Filters Analog-to-Digital Converter (ADC) Analog-to-Digital Converter (ADC) Amplifier Amplifier Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Output: Output: Computer Display Computer Display Memory/Digital Storage Media Memory/Digital Storage Media Input: True Output: Ideal Output:

13. Digital EEG System: PART 1: PART 1: System Input System Input

14. Digital EEG System: Input Input: Input: Electric Field at Scalp Electric Field at Scalp Sensors/Transducers: Sensors/Transducers: EEG electrodes. EEG electrodes. Transformation: Transformation: Filters Filters Analog-to-Digital Converter (ADC) Analog-to-Digital Converter (ADC) Amplifier Amplifier Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Output: Output: Computer Display Computer Display Memory/Digital Storage Media Memory/Digital Storage Media

15. Digital EEG System: Input EEG activity is created by underlying cortical generators. EEG activity is created by underlying cortical generators. This activity is transmitted to the scalp where it is measured by EEG. This activity is transmitted to the scalp where it is measured by EEG. The difference between cortically generated, and scalp recorded electrical activity can affect & limit interpretation of scalp EEG. The difference between cortically generated, and scalp recorded electrical activity can affect & limit interpretation of scalp EEG.

17. Digital EEG System: Input Electrophysiologic signals may be recorded either intracellularly or extracellularly. Electrophysiologic signals may be recorded either intracellularly or extracellularly. Scalp recorded EEG data are extracellular recordings. Scalp recorded EEG data are extracellular recordings. Electric fields making up EEG waveforms are initially generated in cortex. Electric fields making up EEG waveforms are initially generated in cortex.

18. In EEG, electric fields generated by areas of cortex are measured at a distance over the scalp. In EEG, electric fields generated by areas of cortex are measured at a distance over the scalp.

19. Epileptiform activity: Epileptiform activity: distinguished from normal activity based on degree of rhythmicity & synchrony. distinguished from normal activity based on degree of rhythmicity & synchrony. most common forms: most common forms: Spikes <70 msec in duration. Spikes <70 msec in duration. Sharp waves (70-200) msec in duration. Sharp waves (70-200) msec in duration. Within the cortex, at a cellular level, sustained depolarization leads to multiple action potentials superimposed on the crest of depolarization. This is called a paroxysmal depolarization shift (PDS). Within the cortex, at a cellular level, sustained depolarization leads to multiple action potentials superimposed on the crest of depolarization. This is called a paroxysmal depolarization shift (PDS).

20. Development of a PDS Spatial summation. Spatial summation. Temporal summation. Temporal summation.

21. Development of Scalp-recorded Epileptiform Activity from a PDS A PDS generates a spike w/negativity over the epileptogenic focus if enough neurons are synchronously engaged. A PDS generates a spike w/negativity over the epileptogenic focus if enough neurons are synchronously engaged.

22. Synchronous Activity Because of physical barriers between the cortical source and the EEG electrodes, a single action potential cannot be detected at the scalp. Because of physical barriers between the cortical source and the EEG electrodes, a single action potential cannot be detected at the scalp. A synchronous volley is necessary to detect electrical activity at the scalp. A synchronous volley is necessary to detect electrical activity at the scalp. Typically, synchronous activity from an area of at least 6 cm 2 of cortex (about 10 8 neurons) is needed for detection at the scalp. Typically, synchronous activity from an area of at least 6 cm 2 of cortex (about 10 8 neurons) is needed for detection at the scalp. EEG measures summated postsynaptic potentials (EPSP/IPSP). EEG measures summated postsynaptic potentials (EPSP/IPSP).

23. Insufficient Area of Generator to be Detected at Scalp

24. Volume Conduction The electric field generated by the PDS traverses from cortex through adjacent grey & white matter, CSF, meninges, skull, and scalp before being detected over the scalp, and is therefore greatly altered before being recorded. This is called volume conduction. The electric field generated by the PDS traverses from cortex through adjacent grey & white matter, CSF, meninges, skull, and scalp before being detected over the scalp, and is therefore greatly altered before being recorded. This is called volume conduction.

25. Effect of Distance These fields are altered by distance between cortical generator & EEG scalp electrodes. These fields are altered by distance between cortical generator & EEG scalp electrodes. The electric field falls of exponentially as square of distance. The electric field falls of exponentially as square of distance.

26. Effect of Tissue Heterogenicity Also altered by heterogeneity of tissues traversed. Also altered by heterogeneity of tissues traversed. Different compartments (grey matter, white matter, CSF, meninges, skull, scalp) have different electrical conductivities. Different compartments (grey matter, white matter, CSF, meninges, skull, scalp) have different electrical conductivities.

27. Volume conduction accounts for the difference between the cortically generated field, and the scalp recorded field. Volume conduction accounts for the difference between the cortically generated field, and the scalp recorded field. In other words, the surface EEG activity can be thought of as a 2D projection, or shadow of a complex intracranial 3D electrical generator (Wyllie, 2006). In other words, the surface EEG activity can be thought of as a 2D projection, or shadow of a complex intracranial 3D electrical generator (Wyllie, 2006).

28. Input: Continued

29. Digital EEG System: Input (cont.) Input : Input : Electric Field at Scalp Electric Field at Scalp Sensors/Transducers: Sensors/Transducers: EEG electrodes. EEG electrodes. Transformation: Transformation: Filters Filters Analog-to-Digital Converter (ADC) Analog-to-Digital Converter (ADC) Amplifier Amplifier Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Output: Output: Computer Display Computer Display Memory/Digital Storage Media Memory/Digital Storage Media

30. Digital EEG System: Input: Electrodes The electrodes are the interface between the electric field at the scalp and the input to the digital EEG system. The electrodes are the interface between the electric field at the scalp and the input to the digital EEG system. The electrodes and every other stage in the EEG system alter the signal. The electrodes and every other stage in the EEG system alter the signal. The biophysical properties of the electrodes determine how the signal will be affected at this stage in the system. The biophysical properties of the electrodes determine how the signal will be affected at this stage in the system.

31. Digital EEG System: Input (cont.) Input : Input : Electric Field at Scalp Electric Field at Scalp Sensors/Transducers: Sensors/Transducers: EEG electrodes. EEG electrodes. Transformation: Transformation: Filters Filters Analog-to-Digital Converter (ADC) Analog-to-Digital Converter (ADC) Amplifier Amplifier Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Output: Output: Computer Display Computer Display Memory/Digital Storage Media Memory/Digital Storage Media The EEG electrode acts as a transducer and transforms ionic charge flow to electron charge flow which can be carried by copper wire and processed by the digital EEG/computer system.

32. Digital EEG System: Input (cont.) The EEG electrode acts as a transducer and transforms ionic charge flow to electron charge flow which can be carried by copper wire and processed by the digital EEG/computer system. The EEG electrode acts as a transducer and transforms ionic charge flow to electron charge flow which can be carried by copper wire and processed by the digital EEG/computer system.

33. Digital EEG System: Input: Electrodes The interface between the scalp, the electrolyte/conducting gel/paste/solution, and the EEG electrode can be modeled as a battery. The interface between the scalp, the electrolyte/conducting gel/paste/solution, and the EEG electrode can be modeled as a battery. The presence of an electric field leads to development of a voltage at this interface. The presence of an electric field leads to development of a voltage at this interface.

34. Digital EEG System: Input: Electrodes Electrode factors which can affect the measured signal: Electrode factors which can affect the measured signal: Electrode materials. Electrode materials. Quality of electrode contact. Quality of electrode contact. Different electrode materials (silver chloride, aluminum, tin, platinum, stainless steel, gold, carbon, etc.) and conductive gels/pastes have different properties and therefore affect the signal differently. Different electrode materials (silver chloride, aluminum, tin, platinum, stainless steel, gold, carbon, etc.) and conductive gels/pastes have different properties and therefore affect the signal differently.

35. Digital EEG System: Input: Electrodes The scalp/conductive gel/electrode interface acts as a load on the EEG amplifier input. The scalp/conductive gel/electrode interface acts as a load on the EEG amplifier input. The primary property which differs at the scalp/conductive gel/electrode interface level is the impedance. The primary property which differs at the scalp/conductive gel/electrode interface level is the impedance. Keratin and oils in the skin increase impedance. These can be reduced during skin preparation by use of abrasives and alcohol prep respectively. Keratin and oils in the skin increase impedance. These can be reduced during skin preparation by use of abrasives and alcohol prep respectively. Even with these preparation measures, the skin leads to the highest degree of signal quality loss in the input stage of the EEG system. Even with these preparation measures, the skin leads to the highest degree of signal quality loss in the input stage of the EEG system. The impedance of the electrode/electrolyte interface ranges from 100’s of Ohms (Ωs) to MegaΩs depending on the frequency of the signal and the quality of skin preparation. The impedance of the electrode/electrolyte interface ranges from 100’s of Ohms (Ωs) to MegaΩs depending on the frequency of the signal and the quality of skin preparation.

36. Digital EEG System: Input: Electrodes Terminology: Terminology: Resistance vs. Impedance. Resistance vs. Impedance. Resistance: Resistance: Ohm’s Law: I = V/R Ohm’s Law: I = V/R I = current. I = current. V = voltage. V = voltage. R = resistance. R = resistance. Current is the flow of charge. Current is the flow of charge. Resistors are materials which oppose the flow of charge. Resistors are materials which oppose the flow of charge. Conductance is the inverse of resistance. Conductance is the inverse of resistance. Good conductors have low resistance. Good conductors have low resistance.

37. Digital EEG System: Input: Electrodes I = V/R. I = V/R. In the circuit shown if: In the circuit shown if: V = 1000 mV V = 1000 mV R1 & R2 = 100 Ohms R1 & R2 = 100 Ohms Then, Then, I = 1000mV/200Ω = 5 mA. I = 1000mV/200Ω = 5 mA. If the resistors are increased to 500Ω each, then: If the resistors are increased to 500Ω each, then: I = 1000mV/1000Ω = 1mA. I = 1000mV/1000Ω = 1mA. Higher resistance leads to lower current. Higher resistance leads to lower current.

38. Digital EEG System: Input: Electrodes In these examples, the source is a battery which is a direct current (DC) device. In these examples, the source is a battery which is a direct current (DC) device. Neurologic signals are alternating current (AC) sources made up complex activity with multiple frequencies. Neurologic signals are alternating current (AC) sources made up complex activity with multiple frequencies. Resistance does not change with frequency. Resistance does not change with frequency.

39. Digital EEG System: Input: Electrodes Impedance, like resistance represents opposition to the flow of charge. Impedance, like resistance represents opposition to the flow of charge. Unlike resistance though, impedance varies with frequency. Unlike resistance though, impedance varies with frequency. Types of impedance: Types of impedance: Resistance Resistance Capacitance Capacitance Inductance Inductance Impedance = Resistance + Reactance Impedance = Resistance + Reactance Reactance is related to Capacitance & Inductance Reactance is related to Capacitance & Inductance EEG circuits are predominantly composed of resistive and capacitive elements. EEG circuits are predominantly composed of resistive and capacitive elements.

40. Digital EEG System: Input: Electrodes All materials are characterized by their own unique impedance to electrical current. At this stage in the EEG system, there are 3 distinct impedances: (a) The biophysical impedance of the skin (and sweat,oil, blood, etc.). (b) The electro-mechanical impedance of the conductive gel/paste. (c) The electrical impedance of the electrode.

41. Digital EEG System: Input: Electrodes Resistance is not frequency-dependent. Resistance is not frequency-dependent. Purely resistive circuits therefore do not affect the frequency of the input signal being recorded. Purely resistive circuits therefore do not affect the frequency of the input signal being recorded. Since resistance is the opposition of flow, purely resistive circuits act as “voltage dividers” and simply decrease the amplitude of the output signal compared to the input signal Since resistance is the opposition of flow, purely resistive circuits act as “voltage dividers” and simply decrease the amplitude of the output signal compared to the input signal

42. Digital EEG System: Input: Electrodes For a voltage divider: For a voltage divider: Vout = Vin x (R2/R1+R2) Vout = Vin x (R2/R1+R2) In other words, the voltage divider divides the input voltage by the ratio of resistances in the circuit. In other words, the voltage divider divides the input voltage by the ratio of resistances in the circuit.

43. Digital EEG System: Input: Electrodes Example: Example: Vout = Vin x (R2/R1+R2) Vout = Vin x (R2/R1+R2) Vout = 15V x (10kΩ / (5kΩ + 10kΩ)) = 10V Vout = 15V x (10kΩ / (5kΩ + 10kΩ)) = 10V In this example, the voltage source is a DC battery. For an AC source (e.g. EEG signal), the same ratio would apply for all frequencies since the circuit is purely resistive.

44. Digital EEG System: Input: Electrodes This input stage of the digital EEG system however is not purely resistive. It has capacitive elements and therefore has impedance rather than simple resistance. This leads to a more complex, frequency- dependent effect on the signal being measured (EEG).

45. Digital EEG System: Input: Electrodes Because of this frequency-dependence, this stage of the EEG system: (a) Acts as a transducer as desired. (b) Also acts as a filter which is not desired.

46. Terminology Bandwidth: Bandwidth: The frequency range of the system. The frequency range of the system. Traditionally, scalp EEG is divided into discrete frequency bands: Traditionally, scalp EEG is divided into discrete frequency bands: Delta < 4 Hz Delta < 4 Hz Theta 4-7 Hz Theta 4-7 Hz Alpha 8-13 Hz Alpha 8-13 Hz Beta 13-30 Hz Beta 13-30 Hz Gamma 30-80 Hz Gamma 30-80 Hz In scalp EEG, activity above 30 Hz is typically obscured by muscle and environmental artifact. In scalp EEG, activity above 30 Hz is typically obscured by muscle and environmental artifact. The practical bandwidth of scalp EEG is therefore approximately 0.5 – 30 Hz. The practical bandwidth of scalp EEG is therefore approximately 0.5 – 30 Hz.

47. Terminology With scalp EEG the signal being measured (electric field at the scalp generated by the cortex) is very small. With scalp EEG the signal being measured (electric field at the scalp generated by the cortex) is very small. Recording is complicated by many sources of surrounding noise & artifact which may be larger signals than the desired EEG signal. Recording is complicated by many sources of surrounding noise & artifact which may be larger signals than the desired EEG signal.

48. Terminology Therefore, need to filter out frequencies that are both lower than and higher than the desired bandwidth of the signal being measured (EEG). Therefore, need to filter out frequencies that are both lower than and higher than the desired bandwidth of the signal being measured (EEG). This can be done with either analog or digital electronics by use of both: This can be done with either analog or digital electronics by use of both: (1) Low frequency/high pass filters, and (1) Low frequency/high pass filters, and (2) High frequency/low pass filters. (2) High frequency/low pass filters. These two together (low frequency filter + high frequency filter) form a bandpass or passband filter. Ideally, the bandpass will be the same as the bandwidth of the desired signal (EEG). These two together (low frequency filter + high frequency filter) form a bandpass or passband filter. Ideally, the bandpass will be the same as the bandwidth of the desired signal (EEG).

49. Terminology Ideally, the filters would be designed to pass all frequencies within the desired bandwidth unchanged, and to completely block the unwanted lower and higher frequencies. Ideally, the filters would be designed to pass all frequencies within the desired bandwidth unchanged, and to completely block the unwanted lower and higher frequencies. Such an ideal filter cannot be realistically manufactured though.

50. Terminology Other examples of bandwidth and associated bandpass filtering include: (a) A sound system which is characterized by its frequency response which corresponds to its bandwidth. For a high fidelity system this should pass frequencies of approximately (20 – 20k Hz) with approximately equal gain.

51. Terminology Other examples of bandwidth and associated bandpass filtering include: (b) A cellular phone requires a narrower bandwidth. The frequency response of telephones is characterized by a bandpass filter with bandwidth of approximately (300 – 3 kHz).

52. Terminology Scalp EEGs systems have an even narrower bandwidth. Scalp EEGs systems have an even narrower bandwidth.

53. Digital EEG System: Input: Electrodes Because of this frequency-dependence, this stage of the EEG system: (a) Acts as a transducer as desired. (b) Also acts as a filter which is not desired.

54. Digital EEG System: Input: Electrodes Electronic Filters are characterized by a cutoff frequency (f c ): Electronic Filters are characterized by a cutoff frequency (f c ): This is the frequency by which the voltage has dropped by half of that in the passband. This is the frequency by which the voltage has dropped by half of that in the passband. Power = V 2 /R. Power = V 2 /R. Since power is related to voltage squared, the cutoff frequency is also the frequency at which the power has dropped by a factor of the square root of ½ (0.707). Since power is related to voltage squared, the cutoff frequency is also the frequency at which the power has dropped by a factor of the square root of ½ (0.707). The cutoff frequency is also known as the 3 dB point, since a drop of power by ½ is equivalent to – 3 dB on a logarithmic scale. The cutoff frequency is also known as the 3 dB point, since a drop of power by ½ is equivalent to – 3 dB on a logarithmic scale. They are also characterized by a time constant (t c ) which is inversely proportional to (f c ). They are also characterized by a time constant (t c ) which is inversely proportional to (f c ). t c = the product of the resistance x the capacitance (R x C). t c = the product of the resistance x the capacitance (R x C). Linear Response CurveLogarithmic Response Curve

55. Digital EEG System: Low Frequency Filters (A) Low frequency (aka high pass) filters: (A) Low frequency (aka high pass) filters: (f c ) = 1 / (2π x RC) = (f c ) = 1 / (2π x RC) = 1 / (2π x t c ) 1 / (2π x t c ) Example: Example: R = 10,000Ω R = 10,000Ω C = 16μF C = 16μF (f c ) = 1 / (2π x RC) = (f c ) = 1 / (2π x RC) = 1 / (2π x 10,000 x 16x10 -6 ) = 1 / (2π x 10,000 x 16x10 -6 ) =1Hz. (Therefore, this circuit creates a single pole, low frequency filter with a cutoff frequency of 1 Hz.)

56. Digital EEG System: High Frequency Filters (A) High frequency (aka low pass) filters: (A) High frequency (aka low pass) filters: (f c ) = 1 / (2π x RC) = (f c ) = 1 / (2π x RC) = 1 / (2π x t c ) 1 / (2π x t c ) Example: Example: R = 100Ω R = 100Ω C = 16μF C = 16μF (f c ) = 1 / (2π x RC) = (f c ) = 1 / (2π x RC) = 1 / (2π x 100 x 16x10 -6 ) = 1 / (2π x 100 x 16x10 -6 ) = 100 Hz. (Therefore, this circuit creates a single pole, high frequency filter with a cutoff frequency of 100 Hz.)

57. Digital EEG System: Input: Electrodes Ideally, the input stage at the level of the skin/electrolyte/electrode interface would not filter the measured EEG signal and would have a flat frequency response. Ideally, the input stage at the level of the skin/electrolyte/electrode interface would not filter the measured EEG signal and would have a flat frequency response. Due to the resistive & capacitive nature of the skin/electrolyte/electrode though, this stage leads to undesired filtering of the signal being measured (EEG). Due to the resistive & capacitive nature of the skin/electrolyte/electrode though, this stage leads to undesired filtering of the signal being measured (EEG). Therefore, the quality of the skin preparation has a direct impact on the signal quality in scalp EEG recordings. Therefore, the quality of the skin preparation has a direct impact on the signal quality in scalp EEG recordings.

58. Next: Digital EEG System: Transformation: Filters & Amplification Input: Input: Electric Field at Scalp Electric Field at Scalp Sensors/Transducers: Sensors/Transducers: EEG electrodes. EEG electrodes. Transformation: Transformation: Filters Filters Amplifier Amplifier Analog-to-Digital Converter (ADC) Analog-to-Digital Converter (ADC) Digital-to-Analog Converter (DAC) Digital-to-Analog Converter (DAC) Output: Output: Computer Display Computer Display Memory/Digital Storage Media Memory/Digital Storage Media

59. Break