PlaySafe Week 3 Update

PlaySafe is a digital health wearable that predicts whether someone is about to have a sudden cardiac arrest.

PlaySafe is focused towards three target groups:

  1. Athletes (According to the NIH, sudden cardiac death is the most common cause of death in young athletes)
  2. The elderly (According to Nature Cardiology, sudden cardiac death is a major cause of mortality in the elderly)
  3. ICU patients (Critically ill hospital patients are constantly at risk of dying from sudden cardiac arrest)

Also, these are two “metrics” I’m using to evaluate the overall PlaySafe system:

  1. Raw accuracy (what is the false positive rate?, how accurately does it identify cardiac arrest, etc;)
  2. Time to event (How much prior warning can PlaySafe give while maintaining its accuracy?)

Week 3 Updates:

I accomplished three things this week.

1) Hardware v2.0 (Entirely Re-Designed, Bluetooth Low Energy support, cost reduced by 30%, size reduced by 5x)

Arduino Nano dimensions: 43.18 mm x 18.54 mm
Arduino Uno dimensions: 68.6 mm x 53.3 mm

This week, I redesigned and rebuilt PlaySafe’s hardware. Here is a picture of the new hardware prototype:


I added Bluetooth Low Energy Support with the DMD Tech HC-08 Bluetooth 4.0 Slave:Image result for DMD tech hc08 amazon

I also replaced the Arduino Uno from v1.0 with a much smaller, ATmega328P Arduino Nano-based microcontroller board:

Geekcreit® ATmega328P Arduino Compatible Nano V3 Module Improved Version No Cable

My 3D-printed design hasn’t arrived yet, so I improvised and used plastic casings from Neosporin tubes as the chassis:



Image result for neosporin on the go

Some Pioneers requested a cost analysis with a parts list in last week’s update, so here it is:

Hardware v1.0:

Part Cost
Arduino Uno Board $18.36
PulseSensor $23.99
Wires+ Plastic $1.50
Breadboard $6.99
Total Cost: $50.84

Hardware v2.0:

Part Cost
ATmega328P Microcontroller Board $3.99
HC-08 Bluetooth 4.0 Slave Module $7.99
PulseSensor $23.99
Wires+ Plastic $1.50
Total Cost: $37.47

Improvement in Total Cost from v1.0 to v2.0: ~30%

Some more pictures of the hardware prototype v2.0:


2) Improving Software Prototype

I improved the accuracy of the cardiac arrest prediction software from 79% to 87%, the highest one-week improvement I’ve achieved since the beginning. I’m planning on writing a white-paper with an overview of the algorithm and posting it soon.

3) Mobile Alerts Feature

To integrate PlaySafe with mobile devices and patient monitoring workflows, I made a mobile alerts feature that notifies coaches/family/doctors if a user’s cardiac arrest risk spikes. I used the Twilio API to create this with a Python integration. Here’s a sample message from the PlaySafe Mobile Alerts system:



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