Postdoc position on signal processing for post-operative patient monitoring
Postdoc position on signal processing for post-operative patient monitoring
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Job description
Program:
Remote monitoring in health is of increasing importance, even more driven by the COVID-19 pandemic. With remote monitoring, patients are continually monitored outside the medical care centers, either before hospitalization (e.g., for chronically ill persons) or afterward (e.g., patients discharged after a clinical intervention such as an operation or after admission for exacerbation of chronic disease). The advantages of remote monitoring are many when compared to acute care monitoring. Patient well-being and comfort are increased compared to hospital care since people can stay in their preferred home environment and close to their relatives. However, this requires that any signs of clinical deterioration can be detected earlier, avoiding emergency or too-late rehospitalizations.
This project is part of a European project (RM4Health) in which multiple partners across Europe collaborate on advancing remote monitoring for applications related to health and will be staffed from TU/e with a Postdoc, a PhD, supported by scientific staff from the Department of Electrical Engineering. The Postdoc and PhD aims to address the challenges related to remote monitoring for post-operative care for surgery patients and for telerehabilitation of chronic heart failure patients in close collaboration with regional clinical and industrial partners.
Project description:
The project investigates out-of-hospital monitoring for early warning for patient deterioration after surgery. In current clinical practice, simple tools such as an Early Warning Score (EWS) are used that based on patients' measured vital signs in lower acuity settings aim to identify their likelihood of deterioration. Examples of deterioration are death or admission to Intensive Care Units. These tools are limited because currently the observation frequency of the vital signs by nursing staff is often limited to only once per 8 hours (every shift). More frequent monitoring is not practical because of the associated workload for hospital staff. Also, completeness of data is a point on contention: the EWS relies on various vital signs and missing one might render the EWS unreliable or even impossible to determine.
In this project, we seek to improve the calculation of EWS based on continuous or continual data measured with wearable technology, ultimately enabling use of the technology in the home environment. Challenges that need to be addressed include the extraction of vital signs from noise sensory data, finding solutions for data incompleteness, and linking the vital signs to improved EWS.
The project will leverage existing datasets that are collected in various trials under controlled (i.e. hospitalized) environments, as well as under free-living conditions. These datasets contain wrist-worn photoplethysmography (PPG) signals together with accelerometry and clinical markers. Concrete topics will be to study the PPG morphology in relation to the patient's condition and to study the coupling between PPG and accelerometry to investigate the response of heartrate and respiration rate to movement, which could be a valuable marker for the overall condition and its possible deterioration.
The Postdoc will be responsible for coaching and collaborating with the PhD student, together addressing the main scientific challenges. In addition, the Postdoc will manage the contacts with consortium partners, will be responsible for progress reports and review meetings during the course of the project, and will ensure that all deliverables of the project are achieved in time.
Responsibilities:
You will be responsible for the development of signal processing methods to monitor post-operative patients in an out-of-hospital setting. You will work closely together with technical and clinical PhDs and senior staff members from the involved partners, mostly on the regional/national level, but also across partners in the European consortium.
You will be responsible for the contacts with other consortium partners and timely reporting the progress of the project for project review meetings.
Remote monitoring in health is of increasing importance, even more driven by the COVID-19 pandemic. With remote monitoring, patients are continually monitored outside the medical care centers, either before hospitalization (e.g., for chronically ill persons) or afterward (e.g., patients discharged after a clinical intervention such as an operation or after admission for exacerbation of chronic disease). The advantages of remote monitoring are many when compared to acute care monitoring. Patient well-being and comfort are increased compared to hospital care since people can stay in their preferred home environment and close to their relatives. However, this requires that any signs of clinical deterioration can be detected earlier, avoiding emergency or too-late rehospitalizations.
This project is part of a European project (RM4Health) in which multiple partners across Europe collaborate on advancing remote monitoring for applications related to health and will be staffed from TU/e with a Postdoc, a PhD, supported by scientific staff from the Department of Electrical Engineering. The Postdoc and PhD aims to address the challenges related to remote monitoring for post-operative care for surgery patients and for telerehabilitation of chronic heart failure patients in close collaboration with regional clinical and industrial partners.
Project description:
The project investigates out-of-hospital monitoring for early warning for patient deterioration after surgery. In current clinical practice, simple tools such as an Early Warning Score (EWS) are used that based on patients' measured vital signs in lower acuity settings aim to identify their likelihood of deterioration. Examples of deterioration are death or admission to Intensive Care Units. These tools are limited because currently the observation frequency of the vital signs by nursing staff is often limited to only once per 8 hours (every shift). More frequent monitoring is not practical because of the associated workload for hospital staff. Also, completeness of data is a point on contention: the EWS relies on various vital signs and missing one might render the EWS unreliable or even impossible to determine.
In this project, we seek to improve the calculation of EWS based on continuous or continual data measured with wearable technology, ultimately enabling use of the technology in the home environment. Challenges that need to be addressed include the extraction of vital signs from noise sensory data, finding solutions for data incompleteness, and linking the vital signs to improved EWS.
The project will leverage existing datasets that are collected in various trials under controlled (i.e. hospitalized) environments, as well as under free-living conditions. These datasets contain wrist-worn photoplethysmography (PPG) signals together with accelerometry and clinical markers. Concrete topics will be to study the PPG morphology in relation to the patient's condition and to study the coupling between PPG and accelerometry to investigate the response of heartrate and respiration rate to movement, which could be a valuable marker for the overall condition and its possible deterioration.
The Postdoc will be responsible for coaching and collaborating with the PhD student, together addressing the main scientific challenges. In addition, the Postdoc will manage the contacts with consortium partners, will be responsible for progress reports and review meetings during the course of the project, and will ensure that all deliverables of the project are achieved in time.
Responsibilities:
You will be responsible for the development of signal processing methods to monitor post-operative patients in an out-of-hospital setting. You will work closely together with technical and clinical PhDs and senior staff members from the involved partners, mostly on the regional/national level, but also across partners in the European consortium.
You will be responsible for the contacts with other consortium partners and timely reporting the progress of the project for project review meetings.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
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Eindhoven University of Technology (TU/e)
Requirements
Who are you:
You have a PhD degree in Electrical Engineering or similar and have strong affinity with (patho)physiology, signal processing, and artificial intelligence. Furthermore, you are able to coordinate and plan your own research, coach PhD students and collaborate with staff in the project, but also with colleagues in academia, industry, and hospital. To this end, you must be capable of and comfortable in interacting with various disciplines and levels of expertise.
You have a PhD degree in Electrical Engineering or similar and have strong affinity with (patho)physiology, signal processing, and artificial intelligence. Furthermore, you are able to coordinate and plan your own research, coach PhD students and collaborate with staff in the project, but also with colleagues in academia, industry, and hospital. To this end, you must be capable of and comfortable in interacting with various disciplines and levels of expertise.
Conditions of employment
What do we offer:
A Postdoc position in a vibrant and dynamic high-tech environment. You can perform research on a highly relevant topic that can influence the quality of life for many patients, with the potential to see and help your research results get implemented in clinical practice. Furthermore, we offer
A Postdoc position in a vibrant and dynamic high-tech environment. You can perform research on a highly relevant topic that can influence the quality of life for many patients, with the potential to see and help your research results get implemented in clinical practice. Furthermore, we offer
- A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
- A full-time employment for two years and nine months.
- A gross monthly salary and benefits in accordance with the Collective Labor Agreement for Dutch Universities.
- Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
- A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
- A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
- Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
