Noninvasive multimodal analysis of thoracic bioimpedance and myographic signals for the assessment of chronic obstructive pulmonary disease
Dolores Blanco, Biomedical Signal Processing and Interpretation
Chronic respiratory diseases cause morbidity and premature mortality in adult population. In particular, chronic obstructive pulmonary disease (COPD) represents a socioeconomic burden worldwide. COPD is usually evaluated by a spirometry test to quantify the airflow limitation. Classical spirometry requires the patients to move to the medical centers making difficult the continuous monitoring. Alternatively, other noninvasive methods have been studied to monitor respiration because of their capability to provide valuable respiratory-related information. These techniques would lighten the intrusiveness of the measurements and ease the ambulatory monitoring of respiration. However, the applicability of these methods into the clinics is still limited because of the lack of evidence in these applications.
The objective of this thesis is to propose and evaluate novel noninvasive methods to monitor respiration and assess obstructive diseases. We proposed a setup and a protocol to evaluate the applicability of thoracic bioimpedance and surface myographic signals for respiration assessment in healthy subjects and COPD patients. We acquired bioimpedance, airflow and surface myographic signals in ten healthy subjects and fifty COPD patients. The physiological data was measured during an inspiratory threshold loading protocol to evaluate the methods during restrictive conditions. The thesis consisted of three different studies published in high impact factor journals. The two first studies delved into the changes of thoracic bioimpedance during restrictive breathing and, the third one focused on the combination of bioimpedance and myographic signals for the assessment of COPD.
Previous studies showed a linear relationship between thoracic bioimpedance and respiratory volume during normal breathing. Firstly, we assessed this linear relationship in healthy subjects for the first time, during a loading protocol. We found a strong correlation between the signals even during highest loads. Nevertheless, bioimpedance measurement is the combination of the different impedances of body tissues, organs and fluids and consequently, not only volume contributes to its measurement. Accordingly, our second study aimed to evaluate the relevance of volume and chest movement to bioimpedance measurement at different levels of inspiratory muscle activity. We characterized bioimpedance using chest movement and volume signals by linear models and neural networks for different muscle effort. The results agreed with our previous results, indicating that respiratory volume was the main contribution to bioimpedance, but chest movement contributed substantially and more notably at high muscle activity. Both studies provided better knowledge of thoracic bioimpedance measurements which reinforces its use for noninvasive respiratory monitoring.
Finally, we evaluated the combination of thoracic bioimpedance and surface myographic signals in the COPD population. We proposed two novel ratios derived from the bioimpedance amplitude and myographic activity. These ratios showed significant differences between the mild and severe COPD patients meaning that the severest patients had lower inspiratory ventilation contribution of the inspiratory muscles. Consequently, we suggest these novel ratios to provide valuable information to noninvasively monitor and complement the classical assessment of COPD.
The multimodal approach proposed in this thesis supports the application of thoracic bioimpedance for respiratory monitoring during normal and restrictive breathing. Furthermore, the combination of bioimpedance and myographic information exhibited differences between COPD severity. The proposed methods will provide additional information about COPD condition which will be easily tracked by a single wearable device. Consequently, the results of this thesis open up the way for a high-quality noninvasive monitoring of chronic respiratory patients.
This thesis defense will take place on Monday, 9th November, at 15:00 hours.
Location: The defense will be online using Microsoft Teams. People are invited to attend upon receiving a link that you have to request to Dolores Blanco (firstname.lastname@example.org) or Raimon Jané (email@example.com).