Microprocessor based Design for Biomedical Applications MBE 3 – MDBA XI : Project Outlooks.

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Microprocessor based Design for Biomedical Applications MBE 3 – MDBA XI : Project Outlooks

Transcript of Microprocessor based Design for Biomedical Applications MBE 3 – MDBA XI : Project Outlooks.

Page 1: Microprocessor based Design for Biomedical Applications MBE 3 – MDBA XI : Project Outlooks.

Microprocessor based Design for Biomedical Applications

MBE 3 – MDBA

XI : Project Outlooks

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Resumee of our Project Works (1)

We built 4 AVR Evaluation Board Kits and used them for basic firmware projects with the ATmega8 : ● AVR-GCC, make, AVRStudio toolchains

● Firmware download via direct SPI access

● GPIO, Timer Interrupts, ISRs

● UART, Interrupt driven communication

● Analog/Digital Conversion

● Transfer of multiple channels, data packets

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Resumee of our Project Works (2)

We brought up 4 Monolith-EEGs :

● soldered and debugged the SMD-boards

● soldered the extension boards with SPI connectors

● understood the analog and digtial schematics (nearly ;-)

● ported the firmware to the ATmega168

● used the FTDI UART-USB converter ICs

● investigated the bootloader-mechansim

● evaluated our designs with realtime EEG / ECG recordings

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So I would say :

We did a great job !

http://www.aerotraining.com/awards.htm

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For sure, this project could be extended.

Here come a few ideas ….

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Possible Hardware extensions :

● an EEPROM to store configuration data

● battery driven (offline) operation: what batteries / accus ? Stepup converter ? ● wireless communication: add a bluetooth or zigbee module http://www.bluegiga.com/default.asp?f=2&t=1&p=8700&subp=200

● on-board data-logging: interface with a MMD / SD memory card http://www.ulrichradig.de/home/index.php/avr/mmc-sd

● new sensors: GSR/EDA , temperature, pulse, acceleration .. http://electronicdesign.com/Articles/Index.cfm?AD=1&ArticleID=6343

● evaluate active (dry) electrodes and alternative electrode caps http://www.dcc.uchile.cl/~peortega/ae/

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The Serial Peripheral Interface

Miso: master in slave outMosi: master out slave in

SCK: clock

SS: slave select

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SD / MMC – Interface : SPI - Bus

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TWI – The Two Wire Interface (IIC Bus)

SDA : serial DataSCL : serial ClockR1, R2 : Pullup Resistors on the Bus lines, devices tri-state their outputs line level goes low if any of the connected device outputs 0

START: SDA goes low during SCL high STOP: SDA goes high during SCL high

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TWI – The Two Wire Interface (IIC Bus)

● only two Bus Lines needed for bidirectional communication

● Master and Slave Operation

● Device can Operate as Transmitter or Receiver

● 7-bit Address Space Allows up to 128 Different Slave Addresses

● Multi-master Arbitration Support

● Up to 400 kHz Data Transfer Speed

● Noise Suppression Circuitry Rejects Spikes on Bus Lines

● Wake-up when AVR is in sleep mode and slave address detected

as ever: the AVR datasheet has the details …

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TWI – example: EEPROM interface to AVR

http://www.captain.at/electronic-atmega-eeprom.php

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Some Ideas for Software extensions …

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Possible Software extensions

at the uC (firmware) side:

● on-board filtering ( configure FIR / IIR filters for channels ) http://www.atmel.com/dyn/resources/prod_documents/doc2527.pdf

● on-board feature extraction ( pulse rate ? ) ● Bidirectional communication : change baud- and sampling rate at runtime select relevant channels allow access to I/O-pins ( Events ? ERP-recording ? ) error detection / correction for data transfer

… some of these features are already present in the p21-firmware: http://people.freenet.de/moosec/projekte/simpleeeg/download/firmware212.zip

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Possible Software extensions

at the PC (host) side:

● write our own data packet parser

● write a simple biosignal tracing and recording software in a platform independent environment (JAVA? C++ & GTK / QT / SDL ?)

● investigate algorithms for feature extraction (pattern recognition ? LDA / AR-Filter for SSVEP or μ -BCI ?)

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BrainBay - extensions

Configurations:

● design Biosignal protocols with midi / optical feedback Alpha / Theta Training ? REM-Detection ? Muscle Rehabilitation Training ?

Extend / improve the software:

● add new modules ● remove OS-dependent parts ● improve signal handling …

http://www.shifz.org/brainbay/manuals/brainbay_developer_manual.pdf

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Conclusions:

● This project has lots of potential for future improvements

● in the optimal case, Open Source Projects are a win-win situation

I hope you enjoyed the show - have a good time and much Alpha-Activity !