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PhD Respiratory Monitoring

PhD Respiratory Monitoring

Are you interested in developing fundamental knowledge in signal processing to push the neurorehabilitation of the future? Do you enjoy technical challenges? This stimulating PhD position might be the right one for you!
Position
PhD-student
Department(s)
Electrical Engineering
FTE
1,0
Date off
22/02/2022
Reference number
V36.5424

Job description

The Biomedical Diagnostic (BM/d) Lab at the Eindhoven University of Technology (TU/e) is seeking an outstanding PhD candidate to work in the field of electrophysiological signal processing within the e/MTIC collaboration with Philips Research, the Catharina Ziekenhuis, and the Kempenhaeghe Center for Sleep Disorders.

Project description

The respiratory effort is defined as the effort of the muscles aimed at driving respiration. The respiratory effort is a key parameter to assess the condition of the respiratory system and holds potential for multiple clinical applications, from detection of sleep apnea, to mechanical ventilation and cardiorespiratory monitoring.

The esophageal pressure is the gold standard technique currently used to acquire information about the respiratory effort. This obtrusive method uses a sensorized catheter placed in the patient’s esophagus to record changes in pressure due to respiration. A possible non-invasive alternative is still under investigation.

Surface electromyography (EMG) is a technique to non-invasively study the muscular electrical activity by electrodes placed on the skin surface.

During breathing, electrical activity is generated by the activation of groups of innervated muscle fibers, called motor units, in the diaphragm muscle, the intercostal muscles and other respiratory muscles. It could therefore be possible to measure the respiratory effort non-invasively by using surface EMG from respiratory muscles (rEMG). Indeed, previous studies showed that rEMG contains information about breathing patterns and neural respiratory drive [Bockelmann et al. 2019]. However, the relation between rEMG and respiratory effort is obscured by the presence of multiple disturbances such as cardiac activity and crosstalk from other trunk muscles. This impacts the clinical uptake of rEMG to estimate the respiratory effort.

This PhD project will focus on the non-invasive investigation of respiratory effort by using rEMG. In vivo measurements will be carried out on healthy subjects as well as patients. Dedicated algorithms for rEMG analysis and feature extraction will be developed. Machine learning algorithms will be employed for the signal interpretation and classification.

During your PhD, you will work on the conceptualization and development of decomposition strategies for rEMG analysis. To this end, a probabilistic framework and “informed” blind source separation algorithms will be developed that account for the full measurement chain, including the characterization of signal and interference sources, noise statistics, and major artifacts. During the PhD trajectory there will be active involvement in rEMG recording, both in healthy and pathological individuals. Together with a team of engineers and clinicians, you will aid the clinical translation of the developed solutions.

Academic and Research Environment:

Eindhoven University of Technology (TU/e) is one of Europe’s top technological universities, situated in the heart of one of Europe’s largest high-tech innovation ecosystems. Research at TU/e is characterized by a combination of academic excellence and a strong real-world impact. This impact is pursued via close collaboration with high-tech industries and clinical partners.

Research related to this position will be carried out at the Biomedical Diagnostics (BM/d) lab of the Signal Processing Systems (SPS) group, which is part of the Electrical Engineering department. The BM/d lab, chaired by Prof. Mischi, has a strong track record in electrophysiological signal processing, physiological modelling, and quantitative analysis of biosignals, ranging from ultrasound and MRI to electrophysiology. For more information, see: https://www.tue.nl/en/research/research-groups/signal-processing-systems/biomedical-diagnostics-lab/.

The candidate will have the opportunity to work with various members of the SPS group and will be embedded in the e/MTIC collaboration, combining TU/e wih Philips Research and clinical partners such as the Kempenhaeghe Center for Sleep Disorders and the Catharina Ziekenhuis in the area of Eindhoven.

Job requirements

We are looking for candidates that match the following profile:

  • Master's degree in Electrical Engineering/Biomedical Engineering/Applied Physics or related disciplines with excellent grades.
  • Excellent knowledge of signal processing and systems.
  • Strong programming skills (e.g., in Matlab, Python, C, C++).
  • Team player attitude, interested in collaborating with different and multidisciplinary teams.
  • High motivation and creativity.
  • Good communication and organization skills.
  • Excellent English language skills (writing and presenting).

Additional qualifications:

  • Knowledge of electrophysiological signal processing.

Conditions of employment

  • A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
  • A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
  • To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
  • To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
  • A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) 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.
  • Should you come from abroad and comply with certain conditions, you can make use of the so-called ‘30% facility’, which permits you not to pay tax on 30% of your salary.
  • A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
  • Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.
  • Assistance for finding accommodation is offered.

Information and application

For more information about the project and any informal enquiries, please contact prof. M. Mischi (m.mischi[at]tue.nl) or dr. E. Peri (e.peri[at]tue.nl).

For information about terms of employment, click here or contact HR Services, (HRServices.Flux[at]tue.nl).

Please visit www.tue.nl/jobs to find out more about working at TU/e!

Application
If interested, please use 'apply now'-button at the top of this page. You should upload the following:

  • a cover letter explaining your motivation and suitability for the position;
  • a detailed Curriculum Vitae (including English proficiency level, nationality, VISA requirements, date of birth as well as programming skills, experience overview, publication list (if any), and key achievements in research project(s));
  • contact information of two academic references;
  • copies of diplomas with course grades;

Candidates will be selected based on graduation mark and proficiency at university including consideration of the reputation of the university, relevant experience and skills, writing skills and publications, work experience as well as performance in interviews.

Application deadline: 22 Frebruary 2022.

We look forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled.

We do not respond to applications that are sent to us in a different way.

Please keep in mind you can upload only 5 documents up to 2 MB each. If necessary, please combine files.