PhD Respiratory Monitoring

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.