Research & development - Eindhoven | About a week ago
Wearable devices facilitate unobtrusive monitoring during daily activities. In healthcare domain continuously recorded data can give information about patient’s recovery status or readiness for surgery. Recreational and professional athletes can benefit from the same technology as it allows screening for potential health risks and abnormalities before adverse events happen. In broader sense, data collected in ambulatory\home settings can provide insights about personalized activity patterns, sleep quality and overall fitness level.
Extraction of known digital biomarkers still has challenges in the signal processing domain. In particular, motion artefacts are inherent to almost any wearable data. Algorithms are needed to improve motion artefact reduction and automatically assess signals’ quality.
In the context of this project the student will develop signal quality indicators (SQI) and extract digital biomarkers to evaluate the cardio-respiratory status in the domain of health and sports. Student will work with such signals as ECG, PPG or bio-impedance and develop algorithms or machine learning models to detect and compensate artefacts in raw data.
You will be working on cutting-edge research on a topic that is relevant to both academic and industrial research groups. To help you in this journey, we offer a flexible environment where you can be the leader of your own research while at the same time have support of experts to complete your tasks.
IMEC has in-house experts in signal processing, biomedical engineering and clinical applications who can help you in shaping this multi-disciplinary research project.
Click on ‘apply’ to submit your application. You will then be redirected to e-recruiting.