From affordable personal informatics technologies such as smartphones and tablet computers, new possibilities to support treatment of patients with chronic diseases have arisen. In particular, smartphones enable recording and monitoring of symptoms in near real-time and therefore provide a low-cost and scalable scope for a sensing application, which is able to trigger evidence based health interventions for people with chronic diseases.
The successful applicant will first get familiar with TensorFlow and android development. Subsequently, he will learn the technicalities of recording audio by means of the smartphone's microphone. Ideally, this model will be deployed in form of an Android mobile application.
From affordable personal informatics technologies such as smartphones and tablet computers, new possibilities to support treatment of patients with chronic diseases have arisen. In particular, smartphones enable recording and monitoring of symptoms in near real-time and therefore provide a low-cost and scalable scope for a sensing application, which is able to trigger evidence based health interventions for people with chronic diseases.
The successful applicant will first get familiar with TensorFlow and android development. Subsequently, he will learn the technicalities of recording audio by means of the smartphone's microphone. Ideally, this model will be deployed in form of an Android mobile application.
In the current project we focus on the development cough detection model for the smartphone. This works builds upon previous works and focus on building a cough detection model in Python and its integration in an android application. The result of this work will be a hands-on prototype.
For the application, you should meet the following requirements:
Experience in programming
Skills or the interest to learn the basics of deep/ machine learning
Interest in acoustics and mobile technology
ETH / UZH students are preferred
In the current project we focus on the development cough detection model for the smartphone. This works builds upon previous works and focus on building a cough detection model in Python and its integration in an android application. The result of this work will be a hands-on prototype.
For the application, you should meet the following requirements: Experience in programming Skills or the interest to learn the basics of deep/ machine learning Interest in acoustics and mobile technology ETH / UZH students are preferred
Please send your application with a short motivation letter (~250 words), transcript of records and CV to Filipe Barata (fbarata@ethz.ch).
If you have any further questions or comments, please do not hesitate to contact me.
Please send your application with a short motivation letter (~250 words), transcript of records and CV to Filipe Barata (fbarata@ethz.ch).
If you have any further questions or comments, please do not hesitate to contact me.