Micro/Nanotechnologies and

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Matheus Henrique Mota
4 Há anos
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1 Micro/Nanotechnologies and Biomedical Applications Group José Afonso MAP-i Seminar, 06/10/2010 1

2 R&D Areas Solid-state integrated sensors, microactuators and micro/nano systems. Analog and digital integrated circuits. Neural microsystems for brain-computer interface. Lab-on-a-chip systems. X-rays microdetectors for medical imaging Wireless sensor networks and protocols. Wearable systems for monitoring ECG, body posture, heart-rate and respiratory frequency. Microcomputer-based instrumentation and dataacquisition systems for biomedical applications. Energy scavenging thermoelectric microsystems. RF transceivers in CMOS technology. Chip-size antennas. 2

3 EEG Monitoring and Brain-Computer Interface 3

4 Brain-Computer Interface A Brain Computer Interface (BCI) is a device that lets people communicate without movement. People can send information simply by thinking. BCIs translate brain s electrical activity into messages or commands. To operate a BCI, a user performs certain simple tasks like imagining movement or counting flashes on a monitor. These tasks produce distinct patterns of electrical activity that can be detected by an electrodes set. P300 Virtual Keyboard EEG and EOG cursor control 4

5 Neural dry electrodes, wireless system 5

6 Endoscopic Capsule System 6

7 Endoscopic capsule system Array of antennae for sensing Capsule Data recorder portable 7

8 Capsule 8

9 Image processing and analysis 9

10 Smart Pill new generation Small-size: 9 mm diameter by 26 mm length Locomotion controlled Vision system in CMOS technology, instead CCD To have biosensors for local diagnostic To deliver local therapy To do a biopsy To reduce the power consumption and optimizing batteries To be applied in colon examination and not only in the small bowel 10

11 Wireless Sensor Network for Remote Health Monitoring 11

12 Overall architecture 12

13 System prototype 13

14 ECG sensor (a) case; (b) board; (c) being used by a patient ECG signal: (a) measured in the lab (b) displayed in the nurses station 14

15 QRS detection algorithm Heart rate estimation based on a modified Pan- Thompkins algorithm, asystole and arrhythmia detection (tachycardia, brachycardia, and backgroud arrhythmia) R peak delay HR = 64 bpm HR = 65 bpm ECG sample Filter LP Filter (16 Hz cutoff) HP Filter (8 Hz cutoff) Derivative Moving Average Peak Detection Detection Rules HR calculation Heart Rate 15

16 Wireless Real-Time Body Posture Monitoring System 16

17 PELLISAQUAE A smart suit for hydrotherapy rehabilitation in swimmingpools Characteristics: Wired BSNs Wireless stations (one per user) and base station MICAz motes LPRT MAC protocol Motion capture sensors Inertial sensing modules Heart rate sensor Respiratory rate sensor 17

18 PELLISAQUAE Hardware Inertial sensing modules o 3-axis accelerometers o 3-axis magnetometers MICAz mote (left) o Wireless stations o Base station MIB510 (right) o Interface base station/pc 18

19 Wireless Posture Monitoring System System architecture Base Station Fully wireless sensor nodes Sensor node PCB CC2430 IC Microcontroller Transceiver Integrated Antenna Inertial Sensors Enhanced LPRT MAC protocol Sensor node 19

20 Chip-size Antennas 20

21 Chip-size antennas, RF CMOS 0.18 um HRS (7x7mm 2 ) HRPS (7x7mm 2 ) Glass (12x12mm 2 ) 21

22 Wafer-Level Chip-Scale Packaging (WLCSP) techniques two adhesively bonded glass wafers with patterned metallization 4 mm L 4 mm Alimentação 22

23 Thank you! 23

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