danthompson41 / live-sleep-analyzer-1

Hospital Sleep Tracker

This project is funded by Enabling Engineering team at Northeastern University.

Installation

On a Raspberry Pi

The Raspbian distribution of the Raspberry Pi can be used as a host system to log sleep for later analysis. Future plans might use the Pi as a central hub to wirelessly track sleep from multiple patients simultaneously. Installation is pretty simple: first clone the repo into the pi's home directory, then add the following line to the bottom of etc/rc.local (above the exit 0):

/home/pi/live-sleep-analyzer/initialize_sleeptracker.sh &

Then don't forget to set the FTP Credentials

In a Developer Environment

In order to interface with the USB device, you will need the following dependencies on your machine:

• libusb
• virtualenv
• python
• and of course, Git

After cloning the repo, create and activate a virtualenv for your python libraries

git clone [email protected]:hospital-sleep-tracker/live-sleep-analyzer.git
cd live-sleep-analyzer/
virtualenv ~/Virtualenvs/hospital-sleep-tracker
source ~/Virtualenvs/hospital-sleep-tracker/bin/activate
pip install -r requirements.txt

Then don't forget to set the FTP Credentials

FTP Credentials

To enable automatic uploading of logfiles to the server, you will need to create a file with the login credentials. We don't keep this on github for security.

cp sample_credentials.py credentials.py

Then change the IP address, username, and password in credentials.py to the correct values.

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Usage

Data Collection: Logging Live Sleep from Teensy onto Pi via Serial

Primarily run on the Raspberry Pi, this script is useful for pure sleep-data collection. No graphs, analysis, or flashy features. The script searches for a USB connected serial device and begins tracking data into a timestamped logfile. A new logfile can be started simply by disconnecting and reconnecting the USB device. **WARNING: This script may interfere with other connected USB devices. It is recommended to remove any and all unnecessary USB devices before starting the script. **

Usage

python sleep-logger.py [-h]

Data Source:

Serial (Teensy) (future wifi support?)

Supported Operations

• Save to logfile
• Real-time graphing (short-term)
• Session graphing (long-term)
• Real-time analysis
• Session analysis (after-the-fact)

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After-the-fact Analysis: Analyzing Data from Existing Logfile

Useful for testing machine-learning algorithms on existing sleep logfiles. These algorithms are shared by the Nurse Station use case (below).

Usage

python post-analyze.py [-h] FILENAME

Data Source:

Sleep File

Supported Operations

• Save to logfile
• Real-time graphing (short-term)
• Session graphing (long-term)
• Real-time analysis
• Session analysis (after-the-fact)

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Nurse Station: Graphically Analyzing Real-time Data

Useful for testing the actual use case of this product. This simulates the system a nurse or caretaker would be using to monitor the sleep of a patient. This includes live graphs of the patient's sleep movements and information on their current sleep cycle. A logfile is created with sleep data from the current session. This is a sort of 'combination' of the other two use cases.

Usage

python realtime-analysis.py [-h]

Data Source:

Serial (Teensy)

• Save to logfile
• Realtime graphing (short-term)
• Session graphing (long-term)
• Realtime analysis
• Session analysis (after-the-fact)