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.
In the current project, we focus on the monitoring of audible symptoms (such as cough, wheezing, shortness of breath etc.) by means of the smartphone’s built-in microphone. Of particular interest is the situation, where two people are being monitored in the same room and the detected symptoms have to be assigned to the corresponding person.
The successful applicant will first review related literature. Subsequently collect some data recorded by means of a smartphone and finally, develop an algorithm enabling the localization of human sounds. Ideally, this algorithm 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.
In the current project, we focus on the monitoring of audible symptoms (such as cough, wheezing, shortness of breath etc.) by means of the smartphone’s built-in microphone. Of particular interest is the situation, where two people are being monitored in the same room and the detected symptoms have to be assigned to the corresponding person.
The successful applicant will first review related literature. Subsequently collect some data recorded by means of a smartphone and finally, develop an algorithm enabling the localization of human sounds. Ideally, this algorithm will be deployed in form of an Android mobile application.
The goal of this master or semester thesis, respectively is to develop a machine Learning application enabing the localization of human sounds in a silent environment.
For the application, you should meet the following requirements:
- Experience in programming
- Skills or the interest to learn the basics of machine learning
- Interest in acoustics and mobile technology
- ETH / UZH students are preferred
The goal of this master or semester thesis, respectively is to develop a machine Learning application enabing the localization of human sounds in a silent environment.
For the application, you should meet the following requirements:
- Experience in programming - Skills or the interest to learn the basics of 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.