Athena Project.

Transcription

1 Athena Project Jaime Ciriaco Michael Dunn Aaron Marquez Sonoma State University Department of Engineering Science Advisor: Farid Farahmand Client: Arthur Obuchowicz

2 Overview Introduction Problem Marketing & Engineering Requirements Functional Diagram Block Diagram Parts List Testing & Results Challenges & Risks Gantt Chart What did we learn? Supporting Courses Questions/Comments Athena Project

3 Introduction One of the most common disorders in the world is epilepsy It can be dangerous for someone with epilepsy to be left home alone because a seizure can leave them incapacitated and unable to call for help This can be especially dangerous if certain appliances such as a stove or iron were left on Epilepsy is a big problem around the world There are only a few devices that monitor this disorder Funding for these devices are very minimal. If a person has a seizure then they could be incapacitated for a period of time.

4 Problem Statement 65 million people around the world who have epilepsy Government funding for epilepsy is minimal There is no cure for epilepsy Dangerous for epileptics living alone Fire hazard for unsupervised appliances Build device that meets client s needs

5 Existing Work Sami Alert Empatica How s our device different? Smart-Monitor

6 Our Solution - Differentiating Features Simple user interface with dedicated radio link Detect tonic-clonic seizures Real time data logging for doctor or caregiver to postprocess and study trends Send SMS/ Automatic appliance shutoff

7 Marketing Requirements 1. Seizure detection will be a bracelet worn on the wrist that needs to reliably detect a seizure 2. The wearable device will have an ok button to let the central module know that user is not having seizure. 3. The wearable device will have a panic button if the user is knowingly having a seizure 4. The monitoring station needs to send a shutoff signal to automatically turn off appliances 5. The monitoring station needs to auto dial a list of caregivers that will be done by SMS text and 6. The shutoff device needs to safely disable the appliance. After the seizure has ended, the person will notify the monitoring station he/she is okay. Then the monitoring station will turn on the appliances 7. The shutoff device needs to receive a wireless signal to trigger shutdown 8. The system should cost less than $ End user data must be presented in a web page graph 10. Bracelet must have capability to indicate alarm or no alarm state 11. Monitoring station settings such as phone number of caregiver should be re-configurable from remote locations

8 Engineering Requirements Bracelet 1. The bracelet needs to have a 3-axis accelerometer/gyroscope to detect seizures 2. The bracelet needs to run 16 hours / day 3. The bracelet needs to charge in < 8 hours 4. The bracelet needs to have a wireless transmitter 5. The bracelet must be put to sleep whenever possible to reduce power consumption. 6. The bracelet must have OK and PANIC buttons 7. The bracelet must have a status LED Central Monitoring Station 1. The monitoring station needs to have a wireless receiver to receive signals from the bracelet 2. The monitoring station needs to use Amazon SNS to send SMS and notification 3. The monitoring station needs to have a wireless transmitter to send the disconnect signal to shut off devices 4. Must use Amazon EC2 to set up a website utilizing Django web server to display table and graph for each customer in order for a doctor, caregiver or family member to see the status throughout the day of the patient. 5. Must use Amazon DynamoDB to gather data received from wearable store it and push the event to Amazon Lambda in order to send it to My SQL to create a table for the data Power Disconnect Device(s) 1. The power disconnect devices need to receive a wireless signal from the monitoring station 2. The power disconnect device needs to disconnect 110VAC circuits 3. The power disconnect device must have an override switch

9 System Functional Diagram

10 System Block Diagram Wearable Module Adafruit Feather M0 RFM69HCW Packet Radio ATSAMD21G18 ARM Cortex M0 Battery charging circuitry Central Gateway Module Raspberry Pi 3 Appliance Control Module Adafruit Feather M0 RFM69HCW Packet Radio ATSAMD21G18 ARM Cortex M0 AC-DC power converter

11 Parts List for 1 unit - Under budget! Parts Quantity Cost (w/o tax) Total Accelerometer / Gyroscope 1 $29.95 $29.95 Raspberry Pi 3 Model B 1 $39.95 $39.95 Lithium Ion Polymer Battery 1 $7.95 $7.95 Feather M0 RFM69HCW Packet Radio 915MHz 3 $24.95 $74.85 Buttons 2 $7.84 $15.68 Relays 2 $2.49 $4.98 PCB 2 $ 7 $14 Antenna 3 $ 7 $21 Total (Each Complete System) $208.36

12 Printed Circuit Boards Two Prototypes of wearable device First prototype of wearable was too large One prototype of central module Central Module V1 Wearable Prototype #1 Wearable Prototype #2

13 Wearable Seizure detection algorithm Onboard buttons OK and Panic Audio feedback (piezo buzzer) 3D Printed Housing Panic OK Radio Transceiver Circuit Board Accelerometer Microcontroller

14 Seizure Detection Algorithm Calculate Difference: VRMS(n) VRMS(n-1) > THRMS (1) Calculate Counter: Count(n) = Count(n-1) + 1 > THC (2) (2) (1)

15 Central Module 1. Cloud 2. AWS IoT 3. AWS SNS (E.R. 9) 4. AWS Dynamo DB (E.R. 12) 5. AWS Lambda 6. AWS RDS (My SQL) (E.R. 12) 7. AWS EC2 (E.R.11) 8. Django (E.R. 11)

16 Text Message Notifications

17 Home

18 Login

19 Customer Account

20 Customer Account

21 Customer Account

22 Appliance Controller Controls the appliances with an external relay Accepts control signals Seizure/Panic/OK flag from Central Module Radio link communicates with Central Module custom data and control packets Customer supplied Relay Original Relay Custom Data / Control Packets

23 1. Power consumption on the wearable a. Optimizing battery size vs battery life vs radio power 2. Range and communications of radio modules 3. Small size of wearable 4. Accuracy of the seizure detection algorithm in the wearable device a. Tonic Seizures (rapid movement 20 seconds duration) b. Tonic-Clonic Seizures (stiffening 1-5 minutes duration) c. Myoclonic (contractions and relaxations) d. Absence Seizures (blanking out) 5. Using tapping as buttons 6. Interfacing AWS with Django Challenges

24 Gantt Chart

25 Future Work 1. Improve Django site 2. Use Atmel Cortex M0 on a single circuit board instead of Feather Module 3. Use test data to optimize seizure detection algorithm 4. Add dial for user to adjust sensitivity

26 What did we learn? 1. We learned a lot about the challenges of individuals with seizures and their caregivers a. Learned about epilepsy from our primary customer b. Attended seizure support group meetings c. Presented our algorithm at Math Conference 2. Central Module : Amazon Web Services, My SQL and Django 3. System integration, wireless communications protocol 4. PCB Design

27 Supporting Courses 1. ES310 (Microcontrollers) 1. ES442 (Digital and Analog Signals) 1. ES465 (Networking) 1. CS 115 (Computer Programming) Thank you to our adviser Farid Farahmand, our client Arthur Obuchowicz, all of our professors at SSU, and for the SOURCE Funding! 2. EE 485 (Digital Signal Processing) 3. EE 444 (RF Design)

28 Questions/Comments Webpage:

29 References [1] S. M. 2016, "Smart-monitor," [Online]. Available: Accessed: Nov. 16, [2] "Samialert," SAMi : The Sleep Activity Monitor, [Online]. Available: Accessed: Nov. 16, [3] "Seizure Detection MedPage Ltd," in MedPage Ltd. [Online]. Available: Accessed: Nov. 16, [4] E. Inc, "Monitor stress, seizures, activity, sleep," in Empatica, Empatica, [Online]. Available: Accessed: Nov. 16, [5] 2013, "Emfit international," [Online]. Available: Accessed: Nov. 16, [6] SeizAlarm, "Seizure alert service featuring support for apple watch," SeizAlarm, [Online]. Available: Accessed: Nov. 16, [7] "Send SMS from a raspberry pi,". [Online]. Available: Accessed: Nov. 16, [8] "Epilepsy foundation," Epilepsy Foundation, [Online]. Available: Accessed: Nov. 16,