In this paper we want to present our work on a smartphone application
which aims to provide a mobile monitoring solution for patients suffering
from Parkinson’s disease. By unobtrusively analyzing the speech
signal during phone calls and with a dedicated speech test, we want
to be able to determine the severity and the progression of Parkinson’s
disease for a patient much more frequently than it would be possible
with regular check-ups.
The application consists
of four major parts. There is a phone call detection which triggers
the whole processing chain. Secondly, there is the phone call recording
which has proven to be more challenging than expected. The signal analysis,
another crucial component, is still in development for the phone call
analysis. Additionally, the application collects several pieces of
meta information about the calls to put the results into deeper context.
After describing how the speech signal is affected by Parkinson’s
disease, we sketch the overall application architecture and explain
the four major parts of the current implementation in further detail.
We then present the promising results achieved with the first version
of a dedicated speech test. In the end, we outline how the project
could receive further improvements in the future.
Cite as: Klumpp, P., Janu, T., Arias-Vergara, T., Vásquez-Correa, J.C., Orozco-Arroyave, J.R., Nöth, E. (2017) Apkinson — A Mobile Monitoring Solution for Parkinson’s Disease. Proc. Interspeech 2017, 1839-1843, doi: 10.21437/Interspeech.2017-416
@inproceedings{klumpp17_interspeech,
author={Philipp Klumpp and Thomas Janu and Tomás Arias-Vergara and J.C. Vásquez-Correa and Juan Rafael Orozco-Arroyave and Elmar Nöth},
title={{Apkinson — A Mobile Monitoring Solution for Parkinson’s Disease}},
year=2017,
booktitle={Proc. Interspeech 2017},
pages={1839--1843},
doi={10.21437/Interspeech.2017-416}
}