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PulseOximetry Fiber Optics 555 DAC ADC 6.101 Spring 2017 Lecture 11 1 Quiz 4/6 Quiz Design Problem – How to Ace it Understand characteristics and behavior of diodes, bjt, mosfet, jfets and their limitations Understand opamp circuits Understand RC time constants Past design topics Hysteresis comparator zener diode + mosfet Partial credit given for statement key design elements; optimization not required for full credit. 6.101 Spring 2017 Lecture 11 2 PulseOximetery A noninvasive photoplethysmographical approach for measuring pulse rate and oxygen saturation in blood. Oximetry developed in 1972, by Takuo Aoyagi and Michio Kishi Commercialized by Biox in 1981 and Nellcor in 1983. 6.101 Spring 2017 Lecture 11 3 PulseOximetry Sensor 6.101 Spring 2017 Lecture 11 4 http://energymicroblog.files.wordpress.com/2012/11/figure-1.png Why plastic DB-9? finger

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• Pulse‐Oximetry• Fiber Optics• 555• DAC• ADC

6.101 Spring 2017 Lecture 11 1

Quiz 4/6

Quiz Design Problem – How to Ace it

• Understand characteristics and behavior of diodes, bjt, mosfet, jfets and their limitations

• Understand op‐amp circuits• Understand RC time constants• Past design topics

– Hysteresis– comparator– zener diode + mosfet

• Partial credit given for statement key design elements; optimization not required for full credit.

6.101 Spring 2017 Lecture 11 2

Pulse‐Oximetery

• A non‐invasive photoplethysmographicalapproach for measuring pulse rate and oxygen saturation in blood.

• Oximetry developed in 1972, by TakuoAoyagi and Michio Kishi

• Commercialized by Biox in 1981 and Nellcorin 1983.

6.101 Spring 2017 Lecture 11 3

Pulse‐Oximetry Sensor

6.101 Spring 2017 Lecture 11 4

http://energymicroblog.files.wordpress.com/2012/11/figure-1.png

Why plastic DB-9?

finger

Reflective PPG*

Fitbit Patent: US 2014/0275852 Wearable Heart Rate Monitor

Pulse‐Oximetry

• Two measurements:– Pulse rate– Oxygen saturation – Challenge: measuring 5‐20 nA!

• Lab 6 – Photoplethysmogram (PPG): generate tone with each pulse or flash a LED.

6.101 Spring 2017 Lecture 11 6

Frequency Spectrum

6.101 Spring 2017 Lecture 11 7

Pulse‐Ox LEDs ‐ TI

6.101 Spring 2017 Lecture 11 8

IR

Pulse‐Ox Photodiode

6.101 Spring 2017 Lecture 11 9

Photodiode Model

6.101 Spring 2017 Lecture 11 10

)1( kTqv

sD

D

eII

• Photovoltaic: diode forward biased

• Photoconductive: diode reversed biased– Better linearity, larger

dynamic range, better speed over photovoltaic

– IDARK = diode current under reverse bias without light

• Diode current 5‐10 nA

* HP Optoelectronics Handbook

Typical Photodiode VI Curve*

6.101 Spring 2017 Lecture 11 11

* HP Optoelectronics Handbook

Transimpedance Amplifier(Current to Voltage Converter)

6.101 Spring 2017 Lecture 11 12

Ir

Ir = Ip

Vout = Ip Rf

http://en.wikipedia.org/wiki/File:TIA_simple.svg

Transimpedance Amplifier(Current to Voltage Converter)

6.101 Spring 2017 Lecture 11 13

Idiode

At low frequency

outV

3RIV diodeout

mvVxRxI

out

diode

201043105 69

0.96V

Probe Interface

6.101 Spring 2017 Lecture 11 14

Virtual ground at 4.5V not shown

negative battery terminal

add resistor

Pulse‐Ox Lab

6.101 Spring 2017 Lecture 11 15

negative battery terminal

20-30 dB gain

Dark Current Compensation Technique #1

6.101 Spring 2017 Lecture 11 16

transimpedance output

LPF output

LPF

virtual ground

• LPF output is compared against virtual ground

• Difference added to input to LPF• C3 R7 time constant ~2‐10 sec• R7/R6 gain 2‐10

Dark Current Compensation Technique #2

6.101 Spring 2017 Lecture 11 17

transimpedance output

LPF outputLPF

virtual ground

• Implement HPF• Set corner frequency to 0.1hZ• One fewer op‐amp adder

Pulse Ox ‐ Design Problem

• Design a circuit that flashes a LED or generate a tone with each heart beat without noise/false beats or missing beats. (Generating a tone will result in a higher grade.)

6.101 Spring 2017 Lecture 11 18

Component count 1 LF353 = 2 op‐amp Points

(4) op‐amps + BJT’s / MOSFET’s with tone 4

(4) op‐amps + BJT’s / MOSFET’s with LED 3

(5) op‐amps + BJT’s / MOSFET’s LED or tone 2.5

(>5) op‐amps + BJT’s / MOSFET’s LED or tone 2

Oxygen Saturation – SpO2

• To determine blood oxygen saturation, two different wavelengths LED are used 660nm (red) and 905 nm (infrared)

• The two LEDs are alternately pulsed. Hemoglobin (present in oxygenated blood) and deoxyhemoglobin (present in deoxygenated blood) have different absorption for different wavelengths of light

• The oxygenation level determined by comparing the ratio of the two wavelengths absorbed by the blood, running some calculations and . then using a lookup table. Thus SpO2 determination is more suitable for digital processing.

6.101 Spring 2017 Lecture 11 19

Red Blood Cell Functional Hemoglobin Types

Functional Arterial Oxygen Saturation, SaO2:

Reduced Hemoglobin

Red Blood Cell

Oxygenated Hemoglobin

2HbO

Hb

Reduced Hemoglobin

Red Blood Cell

Oxygenated Hemoglobin

2HbO

Hb

Maximum of four Oxygen Molecules can attach to the Hemoglobin Molecule

%1002

22

HbHbO

HbOa CC

COS

• Oxygenated blood HbO2 has wavelength‐dependent absorption characteristic (fig below).

• Absorption also depends on oxygen saturation level.• Hb & HbO2 have almost same absorptions at the isobetric point of 805nm

Wavelength‐Dependent Light Absorption TI – Pulse‐Ox Design

6.101 Spring 2017 Lecture 11 22

H Bridge

• Circuit to apply voltage/current in either direction

• Used in pulse‐ox and motor controllers

6.101 Spring 2017 Lecture 11 23

PhotonicsWhat is “photonics”?

Answer: the generation and manipulation of photons for applications such as sensing, communication, or information processing (analogous to electronics, which is the manipulation of electrons for the same purpose)

Clarification: Isn’t that the same as “optics”?– Some might say it is the same; convention seems to say it isn’t– Optics is, more generally, the study of light. To work with

photonics therefore requires understanding of optics.– You’ll see lots of terms like these used almost interchangeably.

Some almost interchangeable adjectives:• Optic vs Photonic vs Lightwave• Electro‐optic vs Opto‐electronic

6.101 Spring 2017 Lecture 11 24

Acknowledgement: Edward Ackerman, Photonic Systems, Inc.

Fiber Optical Signal Quality

6.101 Spring 2017 Lecture 11 25

Atte

nuat

ion

(dB

in 1

00 m

) in

Coa

xial

Cab

les

Frequency (MHz)Acknowledgement: Edward Ackerman, Photonic Systems, Inc.

Compare these data to attenuation in optical fiber (next slide)

Compare these data to attenuation in optical fiber (next slide)

Typical Attenuation for Silica‐Based Optical Fiber

6.101 Spring 2017 Lecture 11 26

5

2

1

0.5

0.2

0.1

0.05

0.02

0.01

0.005

600 800 1,000 1,200 1,400 1,600 1,800 2,000Wavelength (nm)

Infrared absorption tail from lattice transitions

Rayleigh Scattering

“Dry” fiber

0.002

Fibe

r Atte

nuat

ion

(dB

in 1

00 m

)

–OH absorption peaks

“Near” infrared

400 300 200 150Frequency (THz)

Acknowledgement: Edward Ackerman, Photonic Systems, Inc.Source: C. Cox, Analog Optical Links, Cambridge University Press, 2004.

Optical Fiber – Size Weight

6.101 Spring 2017 Lecture 11 27

250 feet of typical coax vs optical fiber

Acknowledgement: Edward Ackerman, Photonic Systems, Inc.

~$3/ft

Fiber Optic Properties• Attenuation

– Absorption: by the basic constituent atoms of the material itself (intrinsicabsorption) or by impurity atoms

– Radiative loss: caused by bending– Rayleigh scattering: arises from variations in the material density

• Dispersion– Intermodal dispersion: different spatial modes travel at different velocities– Chromatic dispersion: different wavelengths travel at different velocities– Polarization‐mode dispersion: different polarizations travel at different

velocities• Nonlinearity

– Stimulated Brillouin scattering: arises when the photons generate acoustic waves along the fiber length, producing periodic variations in refractive index

– Stimulated Raman scattering: absorption of photons and re‐emission at a longer wavelength

6.101 Spring 2017 Lecture 11 28

Acknowledgement: Edward Ackerman, Photonic Systems, Inc.

Fiber Optics

6.101 Spring 2017 Lecture 11 29

Fiber spool

Single-mode optical fiber

Multi-mode optical fiber

Polarization-maintaining optical fiber

Acknowledgement: Edward Ackerman, Photonic Systems, Inc.Source: C. Cox, Analog Optical Links, Cambridge University Press, 2004.

Electronic (e.g. coaxial‐cable) vs Photonic (e.g. fiber‐optic)

6.101 Spring 2017 Lecture 11 30

LNA LNA

LO

Electronic Mixer

LO

Electronic Mixer

Coax Link with RF Amplification

Coax

Low-noise Amplifier

(LNA)

Coax

Low-noise Amplifier

(LNA)

EDFAOptical Source

Photodetector

Fiber-optic Link with Optical Amplification

Optical Fiber

Erbium-Doped Fiber Amplifier

(EDFA)

Optical Fiber

Modulator EDFAErbium-Doped Fiber Amplifier

(EDFA)

Acknowledgement: Edward Ackerman, Photonic Systems, Inc.

Analog Photonic LinkDirect Modulation

6.101 Spring 2017 Lecture 11 31

RFInput

RFInput

PhotodetectorDiodeLASERor LED

RFOutput

RFOutput

DC

Optical Propagation Medium(e.g., optical fiber)

Direct Modulation Photonic Link

DC

31

Acknowledgement: Edward Ackerman, Photonic Systems, Inc.

Fiber Optics

• Fiber optic transmitters/receivers inexpensive• No fiber stripping• Mates with standard fiber cable• $5‐20

6.101 Spring 2017 Lecture 11 32

6.101 Spring 2017 33

555 Timers• Simple, versatile, low cost IC

for timing applications:– oscillators, – one-shot pulse generator, – pulse width modulator, – missing pulse detector

• Circuit: two comparators, flip flop, resistor divider and a discharge transistor.

• CMOS verison available

• $0.25

555 Datasheet

6.101 Spring 2017 Lecture 11 34

Wide supply range

Small temperaturedrift

voltage independence

two outputs

6.101 Spring 2017 35

555 Block Diagram

trigger threshold Reset Output

1/3 1 high

2/3 1 low

NA NA 0 Low

6.101 Spring 2017 36

Vc

RC Equation

dtdVC c

cc V

dtdVRC

Vs = 5 V

Switch is closed t<0

Switch opens t>0

Vs = VR + VC

Vs = iR R+ Vc iR =

Vs =

R

C

Vs = 5 V

RC

t

sc eVV 1

RCt

c eV 15

6.101 Spring 2017 37

Monostable Circuit

Ra

6.101 Spring 2017 38

Oscillator (Astable)

Rb

555 Design Lab

• The objective: a timer that is resettable.

– when the switch is open, the output of the 555 goes high turning on a LED for an interval T.

– If the switch remains open, after the interval T, the output goes low.

– If the switch is closed before the interval T has elapsed, the output goes low, ie resets.

6.101 Spring 2017 39

Component count Points555 + Rs + Cs + LED + diodes 2555 + Rs + Cs + LED + diodes + 1 BJT/MOSFET 1.5

Design works >1 BJT/MOSFET 1

MOSFET Design Lab

• The objective: design a touch sensitive switch which turns on a LED light for approximately 30 seconds.

• The resistance between two electrodes when touched by a finger is between 5kΩ and 20mΩ, depending on the amount of moisture on the finger and humidity.

• Off current <100ua

6.101 Spring 2017 40

Component count Points2 mosfets or less 23 mosfets 1

Full Credit555 Ramp Generator 2555 Timer Circuit 2Plethysmography 4MOSFET Design 2Report 3Total Lab 13

6.101 Spring 2017 41

Important Missing Links

• The real world is an analog world. However, computing is best perform via digital systems (i.e. the processing of data with 0’s and 1’s).

• Digital-Analog conversion

• Analog-Digital Conversion

6.101 Spring 2017 42

Analog vs Digital

• Analog systems/devices work with information in a continuous stream: clock with hands, mercury thermometer, vinyl records, analog meters, calipers.

• Digital systems/devices work with information in a discontinuous stream (0,1): digital thermometer, digital meters, computers.

6.101 Spring 2017 43

Music – An Example

• CD’s are digital systems that sample and stores audio data– sampling rate: 44.1 khz– data stored in 16 bit format; implies

216 = 65,536 possible output levels

• DVD Audio samples at 96-192kHz/24 bits

• Analog records have an infinite number of output levels.

Do Bits Matter? Quantization*

How many bits are needed to represent 256 shades of gray (from white to black)?

6.101 Spring 2017 44

Bits Range Bits Range1 2 5 322 4 6 643 8 7 1284 16 8 256

* Acknowedgement: Quantization slides and photos by Prof Denny Freemen 6.003

Quantization: Images

6.101 Spring 2017 45

Converting an image from a continuous representation to a discrete representation involves the same sort of issues.

This image has 280 × 280 pixels, with brightness quantized to 8 bits.

Quantizing Images

6.101 Spring 2017 46

8 bit image 7 bit image

Quantizing Images

6.101 Spring 2017 47

8 bit image 6 bit image

Quantizing Images

6.101 Spring 2017 48

8 bit image 5 bit image

Quantizing Images

6.101 Spring 2017 49

8 bit image 4 bit image

Quantizing Images

6.101 Spring 2017 50

8 bit image 3 bit image

Quantizing Images

6.101 Spring 2017 51

8 bit image 2 bit image

Quantizing Images

6.101 Spring 2017 52

8 bit image 1 bit image

Quantizing Colors

6.101 Spring 2017 53

4 bit – 16 colors

8 bit – 256 colors24 bit – 16M colors

6.101 Spring 2017 54

D-A Conversion (DAC)• Problem: take a digital signal and convert to an analog voltage: R-2R ladder

0001 -> 1/16 * 5 volt 0010 -> 2/16 * 5 volt0011 -> 3/16 * 5 volt. . .1101 -> 14/16 * 5 volt1111 -> 15/16 * 5 volt

• Note that the outputs are at discrete levels – not continuous!

R

R

+5

R

+5

R

+5

R

+5

2R 2R 2R 2R

Vo

Bo B3B2B1

031223 2

121

21

21 BBBB 5

6.101 Spring 2017 Lecture 11 55

R‐2R Theory

• For linear circuits, superposition applies. Calculate contribute of bit n by setting all other inputs to zero.

• Equivalent resistance looking left or right is R ohms!

• Use Thevenin equivalent to show division by 2n

R

R R R R

2R 2R 2R 2R

Vo

+5V

same as R ohms

same as R ohmssame as R ohms

6.101 Spring 2017 Lecture 11 56

Analog to Digital Conversion (ADC)

• Successive approximate conversion steps– Scale the input to 0-3 volts (example)– Sample and hold the input– Internally generate and star case ramp and compare

• Flash Compare– Compare voltage to one of 2n possible voltage levels. 8

bit ADC would have 255 comparators.

• Note that most ADC have quantizing errors (number of bits resolution)

Digital to Analog

6.101 Spring 2017 Lecture 11 57

• Common metrics:• Conversion rate – DC to ~500 MHz (video) • # bits – up to ~24 • Voltage reference source (internal / external; stability)• Output drive (unipolar / bipolar / current) & settling time• Interface – parallel / serial• Power dissipation

• Common applications:

• Real world control (motors, lights)• Video signal generation• Audio / RF “direct digital synthesis”• Telecommunications (light modulation)• Scientific & Medical (ultrasound, …)

6.101 Spring 2017 Lecture 11 58

Successive Approximation AD

Sigma Delta ADC

6.101 Spring 2017 Lecture 11 59

integrator

1‐bit DAC

+ +‐ Bit stream

‐+

Analoginput

1‐bit ADC

DecimatorBit stream samples

REFV

REFINREF VVV

0: add VREF, 1: subtract VREF

With VREF=1V: VIN=0.5: 1110…, VIN=‐0.25: 00100101…, VIN=0.6: 11110

http://designtools.analog.com/dt/sdtutorial/sdtutorial.html#instructions

Average of bit stream (1=VREF, 0=‐VREF) gives voltage

Computes average, produces N‐bit result

Only need to keep enough samples to meet Nyquist rate

6.101 Spring 2017 Lecture 11 60

http://www.analog.com/en/design-center/interactive-design-tools/sigma-delta-adc-tutorial.html

6.101 Spring 2017 Lecture 11 61

So, what’s the big deal?

• Can be run at high sampling rates, oversampling by, say, 8 or 9 octaves for audio applications; low power implementations

• Feedback path through the integrator changes how the noise is spread across the sampling spectrum.

Signal

Noise

Power

2sk

Spectrum of modulator’s output

Frequencies attenuated by LPF2

s

6.101 Spring 2017 Lecture 11 62

Binary code

Analo g

Ideal

Offseterror

Offset – a constant voltage offset that appears at the output when the digital input is 0

Binary code

Analog

Ideal

Gainerror

Gain error – deviation of slope from ideal value of 1

Binary code

Ana log

Ideal

Integralnonlinearity

Integral Nonlinearity – maximum deviation from the ideal analog output voltage

Differential nonlinearity – the largest increment in analog output for a 1‐bit change

Binary code

Analog

Ideal

Non‐monoticity

Non‐idealities in Data Conversion

Have a nice spring break!

6.101 Spring 2017 Lecture 11 63