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Human Vital Sign Monitoring and Security Applications Using Correlated MEMS Accelerometer and ZnO x Nanowire Gas Sensors William Branham University of.

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Presentation on theme: "Human Vital Sign Monitoring and Security Applications Using Correlated MEMS Accelerometer and ZnO x Nanowire Gas Sensors William Branham University of."— Presentation transcript:

1 Human Vital Sign Monitoring and Security Applications Using Correlated MEMS Accelerometer and ZnO x Nanowire Gas Sensors William Branham University of Southern California Viterbi School of Engineering

2 Sensor Networks Society's Sensor Needs  Opportunity Large Client Base  Size  Reliability  Cost  Connectivity  Convenience  Signal Processing 2

3 Multi-Sensor Platform Correlation Redundancy USB USB Connector Microcontroller USB UART IC USB SerialClock ADC VCCGND USB-Microcontroller Module Humidity Sensor Temperature Sensor Pressure Sensor Light Sensor Accelerometer DAC Power from PC’s USB port Board’s GND and VCC Nano-electronic FET DG RdRd S Regulator: 5V to 3.3V VCC – 5V V – 3.3V GND 3 GUI Host Controller

4 MEMS Accelerometer 3-Axis 1.5g vs. 6g mode  1.5g more sensitive; 6g for larger accelerations Hardware-based low pass filter Can be dropped from 1.8 meters onto concrete Min/max temperature -25ºC to 145ºC 4

5 In 2 O 3 Nanowire Field Effect Transistor (Gas Sensor)‏ Dimensions:  10 nm diameter  6+ μm length Conductivity Changes  Sensitive to: CO NO2 Humidity Temperature UV Light (resets) Ethanol Hydrogen 5 CO + O - → CO 2 + e - NO2 + e - → NO2 -

6 Manufacturing Method Laser-assisted chemical vapor deposition system  Laser ablates In solid into vapor  Au clusters catalyze nanowire growth  Indium vapor combines with oxygen to form indium oxide  Diameter of the nanowire is directly linked to the catalytic particle size 6

7 Digital Signal Processing Low pass filter – Moving Average Fourier Transforms  High pass filter windows 7 Accelerometer Respiration Accelerometer Walking Real-Time Accelerometer

8 Human Vital Sign/Biorhythm Application - Accelerometer  Respiration measured through diaphagm movement (subject lying on back with sensor taped to diaphragm)  Moving Average Size: 25  Major spike from sensor falling –sensor can detect if patient has fallen at the same time as measuring respiration 8

9 Respiration in Real/Noisy Environment  Subject walking around with accelerometer strapped to stomach/diaphragm area using tape  Each major (~0.4 magnitude changes) peak represents one inhale/exhale  Minor peaks (~.1 magnitude changes) result of walking/major vibration or jostling. 9

10 Human Vital Sign/Biorhythm Application – Nanowire Gas Sensor Respiration: Each peak/valley represents inhale/exhale Simple 20-point moving average Quick responsiveness 10

11 Security Application - Accelerometer Gait Identification - Trespassing  Unfiltered signal – each spike likely correlates with a step, but smaller spikes are ambiguous 11

12 Filtered Signal – Human Gait Human Gait detection  Low pass filter gives clearer delineation of steps  each spike represents step taken Resonance of structures 12

13 Future of Comprehensive Sensor Networks Clients  Infants  People who are elderly or disabled  Emergency medical personnel  Preventative medicine/Medical history  Security Ubiquity Convenience Sustainability  Environmental Control 13

14 Economic Considerations Large Client Base Opportunity  Falls are the leading cause of fatal and non-fatal injuries to older people in the US. 11 million people over age 65 fall per year (1/3 of all seniors) Even larger client base for other forms of monitoring (heart rate/pressure, respiration, etc.) Will increase as baby boom generation ages  Current sensor packages are not as efficient, accurate, cheap, or convenient Example: LifeAlert  Costs ~$300 + $60 monthly and requires user input for assistance  Only deals with falls, not medical monitoring


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