PhD student position in Digital Health for Supporting Acute Incidents

PhD student position in Digital Health for Supporting Acute Incidents

The Biomedical signals and systems research group at the division of Signal processing and Biomedical engineering at the Department of Electrical Engineering is recruiting a qualified candidate for a PhD student position. We are an internationally renowned research group, focusing on research in the fields of Biomedical Engineering and Digital Health. This doctoral position is funded by the Kamprad Family Foundation (https://familjenkampradsstiftelse.se/in-english/) and is part of a strategic investment to develop and expand the Digital Health research and innovation activities at our department.

In this role you will join a research group that provides a stimulating, pleasant and flexible work environment for developing research and teaching, with a network reaching companies and health care representatives with special interest in Digital Health.

Project description
Health care is changing, and more care is being shifted towards home. One result is that medical devices and other equipment from different suppliers are placed in the home and generate individual-related information such as vital data, images, etc. Typical of today's applications, such as Chronic Obstructive Pulmonary Disease (COPD) and heart failure, is that changes occur over relatively long periods of time - days/weeks. Therefore, procedures, processes and technical solutions are not designed to handle acute incidents where rapid response is crucial. At the same time, the possibility of detecting emergency conditions such as a fall with equipment being present in the home, and thus the possibility of acting quickly, increases. A prerequisite is that alarms and individual-related information from different suppliers and sources are provided to the prioritization and assessment process in a standardized way. This forms the foundation of the Autumn Leaves project, which gathers several important actors and companies that together have the possibility to develop a new concept to provide clinical benefits. Autumn Leaves will establish a system innovation model where quick access to individual information from sources like sensors in the home, patient record, social care, etc., together and with various decision support reduces time delays and increases the precision of prehospital care processes generated from emergency conditions in the home.

The project focus on falls, as this is a major and growing societal problem, and at the same time an application that clearly highlights the challenges and opportunities. Other conditions may include arrhythmias, cardiac arrest, epilepsy or diabetes. The core team is the multidisciplinary network that exists in prehospital research, development and innovation in Region Västra Götaland, reinforced by several companies and the City of Gothenburg. The project goal is to design and test a prototype ready for clinical testing.

For Autumn Leaves to become successful it all starts with effectively detecting a fall from a a multitude of sensors. The PhD student's research will involve sensor and data fusion utilization in health care systems for supporting clinical care processes, informed decision making and personalized healthcare. Methods will include the use of signal processing, sensor and data fusion, as well as AI/Machine Learning (ML) to develop and test a method for fall detection that uses various data sources as input, for example fall sensors mounted on the user, such as a smartwatch or other device worn on the wrist, and non-contact techniques, such as radar technology.

Main responsibilities
In this PhD student position you will play an important role in developing an ASAP/Autumn Leaves digital platform. Your research area will cover topics like multiple sensor information fusion, signal processing and interpretation utilizing AI/ML.
Specifically, you will contribute to the development of ASAP/Autumn Leaves through the following three activities:

1) Lay the theoretical foundation for the generic ASAP platform, i.e. define, evaluate and design how different sensors should work together.
2) Be involved in the hardware and software development for the ASAP platform.
3) Scientific dissemination via journal articles and conference publications.

Besides research, the position generally also includes teaching on Chalmers' undergraduate and master level corresponding to about 20 per cent of working hours. Chalmers started a new Master of Science in Biomedical Engineering programme 2020, and has a master programme in Biomedical Engineering since around 2007.

Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.

Application procedure
Learn more and apply here: https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=9536


Application deadline: 16 June, 2021