PhD position on Physiological-Model-Based Artificial Intelligence for the recovery monitoring of elderly after hip fracture ...

A hip fracture in older adults is associated with complications and a high mortality rate of 10% within one month and 30% within one year after hip fracture surgery. It is therefore crucial to monitor patients’ health condition continuously and accurately after surgery to measure and evaluate patients’ recovery progress, timely detect and even predict clinical adverse events like delirium, cardiac arrhythmias and pneumonia. In this project, the University of Twente (Biomedical Signals and Systems group; BSS) in collaboration with the top clinical hospital Ziekenhuisgroep Twente aims to develop such a health condition monitoring system to assist patients’ recovery management and ultimately reduce the complication and mortality rate and increase their quality of life after hip fracture surgery.

This PhD position will focus on the health monitoring system development mainly based on multimodal physiological signals, for instance, inertial measurement unit (IMU), electrocardiography (ECG), photoplethysmogram (PPG), Electrodermal activity (EDA), and contactless movement and physiology signals. Specifically, the PhD researcher will develop physiological-model-based artificial intelligence technologies to assess patients’ recovery process, detect or even predict the occurrence of clinical adverse events like delirium, cardiac arrhythmias and pneumonia among elderly after hip fracture surgery. To obtain relevant data for the above described technology development and its feasibility test, the PhD candidate will also design medical research experimental protocol for both healthy control population and target patient population, apply for the protocol’s ethical approval (please check this website for more information about the relevant ethical regulations and approval process in the Netherlands), and take main responsibilities for performing the approved experiment.

This PhD position is embedded in the EU Horizon Europe Marie Sklodowska-Curie Doctoral Network (MSCA DN) SMARTTEST project. This position is linked to Doctoral Candidate 8 – DC08. For more information on the SMARTTTEST project, the recruitment process or details of the position, follow this link for more information.

The prospective PhD candidate is expected to perform high quality and internationally visible research with publications in high rank peer-reviewed journals. The candidate will join the Biomedical Signals and Systems group at the University of Twente and will be (co-)supervised by dr. Ying Wang, prof. dr. Johannes H. Hegeman and prof. dr. ir. Peter H. Veltink. The candidate will closely collaborate with dr. Ying Wang and fellow team members and is also expected to closely collaborate with the other partners within the SMARTTEST project. The candidate will be appointed for a period of four years, at the end of which a PhD thesis needs to be delivered. During this period, the PhD candidate will be offered the opportunity to broaden their knowledge by joining MSCA SMARTTEST consortium meetings and by participating in (inter)national conferences and workshops.

We are looking for highly motivated, enthusiastic and curiosity-driven researchers:

• You have, or are about to get, a master’s degree in biomedical engineering, electrical engineering, technical medicine, or a related field.
• You have a solid background in biomedical signal analysis, physiology dynamic system, and machine learning technologies, and preferably have experience in designing and performing experiment on human subjects.
• You have strong programming skills, such as, in Matlab\Python.
• You are creative, like to push boundaries and have strong organization skills in designing, planning and implementing research activities.
• You are highly open-minded and motivated to work on the challenges we are facing in healthcare by developing cutting-edge digital health monitoring technology.
• You are an excellent team player in an enthusiastic and hardworking group of scientists healthcare professionals, engineers, physicians, and working on a joint assignment.
• You are proficient in English and able to collaborate intensively with healthcare professionals as well as with industrial and academic parties in regular meetings and work visits.
• You are able to do independent research, have excellent writing skills and preferably, have publication skills.
• The candidate must fulfil the MSCA mobility condition: The candidate in this project must not have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 36 months immediately before the project start date.

Biomedical Signals and Systems BSS is a multidisciplinary group based in Electrical Engineering, focusing on finding solutions for medical challenges via signal and system analysis. Advanced (ambulatory) sensor technology combined with our broad knowledge of the human body as a dynamic system enables (eHealth) technology to improve prevention, diagnosis and treatment of sensory, motor and internal dysfunction in clinical and home/self-care settings. Our research helps to improve the quality of life ofthe elderly, people with chronic diseases and rehabilitation patients. The research mission of the Biomedical Signals and Systems (BSS) group is to:

• enable improved diagnosis and treatment of patients with motor, sensory and cardiopulmonary dysfunction in clinical and home/self-care setting,
• by developing knowledge, methods and tools for identification, control and modulation of neural, muscular and cardiopulmonary systems, cognition and behaviour,
• using smart sensing, novel data analysis techniques and selective actuation technology or personalized eHealth technologies that enable prevention, timely diagnostics, and personalised coaching & treatment for chronic care and rehabilitation.