This is a standalone accelerometer based tremor quantification system for patients with Parkinson's or Essential Tremor (ET). Using an array of signal processing techniques, the diagnostic system provides insight into the characteristics of hand/arm tremors. Along with a number of other metrics, analysis includes tremor detection, amplitude quantification, and frequency analysis in the Fourier domain. Using these calculated metrics, a score indicative of the severity of tremor is devised. Additionally, the MDS Unified Parkinson's Disease Rating Scale (MDS-UDPRS) has been fully integrated for physican input. Duke BME 464 senior capstone design project.
Simply clone and run tk_GUI.py. Makefile in progress.
git clone git@github.com:snimmagadda1/tremor_quant.git
python3.5 Tkinter/tk_GUI.py
- Standalone Park & Son's Co. Essential Tremometer
- Embedded Software
- Python v3.5 and Python v2.7 (Anaconda + packages)
- Adafruit Bluefruit LE SPI python library
- Pyobjc
- poster_bme_464.pdf
- Tkinter: GUI program files
- data_analysis: signal processing and data manipulation
- data_receive: data manipulation and bluetooth calls
v1.0.0-b
- Sai Nimmagadda - Software - LinkedIn
- David Whisler - Electronics - LinkedIn
- Caroline Kittle - Testing - LinkedIn
- Eric Musselman - Physical Design - LinkedIn
See also the list of contributors who participated in this project. Note: Due to the nature of this project, overlap existed between job responsibilities.
This project is licensed under the MIT License - see the LICENSE.md file for details
For general insight and guidance: