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Eyelid movement sensor device

Eyelid movement sensor device. Danielle Perez & Shuki Eizner Boaz Blankrot & Leon Karabchevsky Adi Hanuka. January 8 th , 2013. Acknowledgments. Prof. Schächter Levi Mr. Eli Shoshan Mr. Alex Kinko Mr. Stanislav Shapira. Contents. 1. 2. 3. 4. 5. Overview. Overview.

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Eyelid movement sensor device

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  1. Eyelid movement sensor device Danielle Perez & ShukiEizner Boaz Blankrot & Leon Karabchevsky AdiHanuka January 8th, 2013

  2. Acknowledgments Prof. Schächter Levi Mr. Eli Shoshan Mr. Alex Kinko Mr. StanislavShapira

  3. Contents 1 2 3 4 5

  4. Overview Overview Doctors: Monitoring neurologic diseases and eyelid disorders by analyzing eyelid movements. Our Main Goal: Develop a device for monitoring eyelid motion, acquiring the eyelid movements and enabling analysis of the results. 1

  5. How it works? Overview 1

  6. Basic Concept Overview Patient Doctor Eyelid Movement Sensor PC Application Results of analysis 1

  7. Collaboration Hardware part - Memory - Power - Schematics draws Overview USB cable • Software part • User experience • Integration • - Robust • Physical part • Magnetic field measurement • - Algorithm 1

  8. Device Requirements Overview • Portable system • Samples each eye separately • Evoked motion • Device’s output: position, velocity , frequency • Two operating modes: • Real time - data stored on the computer • Offline - data stored on the device’s memory • User friendly interface • Data analysis and presentation • Multiple tests for a single patient 1

  9. 1 2 3 4 5

  10. Physical part • Physical Goals • Measure the field of a tiny magnet attached to the upper eyelid • Establish the voltages of 4 Hall probes located on the device • The voltages are indicative to the motion of the magnet • Inverse algorithm that establishes the motion from the voltage measurements 2

  11. Physical part • Physical Hall probes magnet 1 2 4 Glasses Sensors system Sample & processing 3 2 - Algorithm Computer Presentation & analysis Data Base 1 - Signal Characterization Magnetic field measurement 2

  12. 1 - Signal Characterization Experiment • Physical 2- Hall probes and circuit holder 3- Complete device 1- Artificial eyelid and magnet 2 4- Typical voltage measurements from 2 probes (V1,V3)

  13. 1 - Signal Characterization Hall probe sensor • Physical • The strength of the magnet’s field varies with the distance • A voltage is applied to the sensor which returns a voltage that is linear with the strength of the magnetic field • If properly calibrated, the system’s voltage represents the distance between the magnet and the sensor B=f(r) V B V=g(r) 2

  14. 2 - Algorithm Physical part • Physical magnet Glasses Sensors system Sample & processing 2 - Algorithm Computer V=g(r) Presentation & analysis r=f(V) Data Base 1 - Signal Characterization Magnetic field measurement r r V r V V V V r r r V V 2

  15. 2 - Algorithm The challenge • Physical 1 2 4 3 y V1 B1 V3 B3 x z 2

  16. 2 - Algorithm Simulation-Magnetic field in time • Physical B1 B3 2

  17. 2 - Algorithm Solution- Probe plane • Physical B1=f(r1,r3) B3=f(r1,r3) r1=h(B1, B3) r3=h(B1, B3) • Once “r1 “ and “r3“ are determined, knowing “d” makes the location • of the magnet a trivial geometric problem 2

  18. Simulation-Magnetic field vs. thedistance • Physical 2

  19. 1 2 3 4 5

  20. Hardware part Overview Hardware part -Memory -Power - Schematics draws USB cable 1

  21. System Requirements • hardware • Design and implementation of portable PCB with the following capabilities: • The system can store the data in two non-volatile memories, • micro-SD and EEPROM. • Computer interface using a USB cable. • Alerts & Control (LEDS and switches). • Capable to measure each eye separately. • Powered by rechargeable battery 3

  22. Design Flow • hardware • Market survey • Schematics • Routing • PCB production • HW debug- software • Integration 3

  23. Block Diagram • hardware 3

  24. 1 2 3 4 5

  25. Software Overview Software The demand for an easy to use, fast to learn, robust & all-encompassing environment led to the development of: Eyelid Pro, combined with the Eyelid Sensor Device embedded software, forms a complete and user-friendly solution for recording, analyzing and documenting patients’ eyelid movement. Eyelid Sensor Device embedded software Eyelid Pro USB 4

  26. Main Concept Software • Portable, low-power plug & play system • Well- defined doctor-patient work flow • Based on customer specifications, flowchart design • Built-in operating assistant & user’s manual • Tool-tips, guided installation, fully documented design • Utilized & fine-tuned for maximum performance and user experience 4

  27. Eyelid Pro Software • End-to-end, flow-oriented design • Real-Time data acquisition • Simply accessible results database • Simultaneousmultiple device support • Easily deployable platform • Powerful results viewer & analyzer • Integrated results comparison tool 4

  28. Eyelid Pro Software • End-to-end, flow-oriented design • High review rate • User error fail-safes • End case reference 4

  29. Eyelid Pro Software • Real-Time data acquisition • Incorporates the abilities of the results viewer with a real-time data link • Ability to store the session • Adjustable sample viewing window • Simply accessible results database • Easily updatable patients record • Ignore\un-ignore session data • Simultaneous multiple device support • Automatic device detection & user selection option • Easily deployable platform • Just press “install”… 4

  30. Eyelid Pro Software • Powerful results viewer & analyzer • Annotation support • Session remarks • Advanced toolbar • Full screen view • Cursor positioning • Image export 4

  31. Eyelid Pro Software • Integrated results comparison tool • Visually compare date between different session & even different patients • Ability to adjust all axes simultaneously or separately 4

  32. Eyelid Sensor Embedded SW Software • Easy to operate user-end controls • On/Off/Sleep mode switch • Start/Stop sampling switch • Device is ‘foolproof’ – device operates only according to pre-defined workflow • Integrated user notification system • Device state indication by 2 tri-color LEDs and buzzer • High speed device-PC data streaming link using USB • Maximum throughput – 1.2MB/sec 4

  33. Eyelid Sensor Embedded SW Software • Accurate multi-sensor data acquisition • 8 sensor sampling at 400Hz effective rate each • x4 oversampling (1600Hz) for noise reduction • 80% data compression ratio • High capacity micro-SD storage solution for long recording time • Data acquisition rate of 3.1KB/sec – or almost 3MB for a 15 minute session • Due to storage restrictions a microSD card is used to store information (up to 2GB of storage) • When connected, the device is recognized as a disk-on-key drive, enabling: robustness, speed, ease-of-use& future development 4

  34. 1 2 3 4 5

  35. What’s next? What’s next? Full integration of the system Adaption for clinical tests 5

  36. Questions ?

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