• In Spain there are 1.5 million COPD patients; it’s the third most common cause of death in the United States
• Monitoring the mechanical signals of the diaphragm will make it possible to evaluate the level of rehabilitation needed for improvement
• A collaborative project between the Institute for Bioengineering of Catalonia (IBEC) and the Germans Trias i Pujol Hospital
The Biomedical Signal Processing and Interpretation group at the Institute for Bioengineering of Catalonia (IBEC) have published a paper in PlosOne describing a new method to evaluate the signals produced by the activity of our respiratory muscles. These signals enable the detection and quantification of the level of muscular weakness caused by pathologies such as chronic obstructive pulmonary disease (COPD).
COPD is the respiratory disease which affects the most people. In the United Kingdom about 30,000 people die per year (more deaths than breast, intestine or prostate cancer), and it is also the third most common cause of death in the United States. In Spain there are about 1.5 million people affected.
In the paper, the team proposes a non-invasive method based on a new algorithm that will improve monitoring of patients. The mechanical activity of the respiratory muscles is measured by accelerometers placed in the chest surface at the level of the diaphragm.
“At the moment, COPD has no cure, but with treatment and rehabilitation patients can increase their muscular activity and compensate for the pulmonary obstruction,” group leader Raimon Jané explains. “That’s why we have developed this non-invasive method to monitor the patient and be able to evaluate the level of improvement.”
Traditionally, the method used to diagnose and evaluate these patients is spirometry, which is based on pressure and measuring respiratory flow. Among the drawbacks of this method are that as well as being intrusive and uncomfortable for sick people and requiring effort on the part of the patient, it delivers a result based only on the activity at the moment tested and is not able to monitor a patient over a period of time.
When we breathe, the diaphragm vibrates, and it is these vibrations which are recorded by the sensors. But during the acquisition of these signals, other components, such as the mechanical signals of the heart, are also recorded. To correctly determine the level of muscular weakness, interferences should be eliminated. The new method, based on the signal sample entropy estimation (fSampEn), is more reliable in estimating the respiratory muscle effort than the existing ones, even at low levels of respiratory flow.
“The mechanical activity is linked to muscular effort, and it has been studied in the peripheral muscles where the signal is more intense,” says Raimon. “The diaphragm has less activity and the mechanical signal recorded is low, and there is a major cardiac interference. What we have been looking for is the most efficient method to suitably estimate this signal, which allows the assessment of the respiratory effort made by COPD patients.”
Reference article: Sarlabous, L., Torres, A., Fiz, J.A., & Jané, R. (2014). Evidence towards Improved Estimation of Respiratory Muscle Effort from Diaphragm Mechanomyographic Signals with Cardiac Vibration Interference Using Sample Entropy with Fixed Tolerance Values. PlosOne, 9(2): e88902