Tiina M. Seppänen

Reducing the airflow waveform distortions from breathing style and body position with improved calibration of respiratory effort belts.

BackgroundRespiratory effort belt measurement is a widely used method to monitor respiration. Signal waveforms of respiratory volume and flow may indicate pathological signs of several diseases and, thus, it would be highly desirable to predict them accurately. Calibrated effort belts are sufficiently accurate for estimating respiratory rate, but the respiratory volume and flow prediction accuracies degrade considerably with changes in the subject’s body position and breathing style.MethodsAn improved calibration method of respiratory effort belts is presented in this paper. It is based on an optimally trained FIR (Finite Impulse Response) filter bank constructed as a MISO system (Multiple-Input Single-Output) between respiratory effort belt signals and the spirometer in order to reduce waveform errors. Ten healthy adult volunteers were recruited. Breathing was varied between the following styles: metronome-guided controlled breathing rate of 0.1 Hz, 0.15 Hz, 0.25 Hz and 0.33 Hz, and a free rate that was felt normal by each subject. Body position was varied between supine, sitting and standing. The proposed calibration method was tested against these variations and compared with the state-of-the-art methods from the literature.ResultsRelative waveform error decreased 60-70% when predicting airflow under changing breathing styles. The coefficient of determination R2 varied between 0.88-0.95 and 0.65-0.79 with the proposed and the standard method, respectively. Standard deviation of respiratory volume error decreased even 80%. The proposed method outperformed other methods.ConclusionsResults show that not only the respiratory volume can be computed more precisely from the predicted airflow, but also the flow waveforms are very accurate with the proposed method. The method is robust to breathing style changes and body position changes improving greatly the accuracy of the calibration of respiratory effort belts over the standard method. The enhanced accuracy of the belt calibration offers interesting opportunities, e.g. in pulmonary and critical care medicine when objective measurements are required.

Improved calibration method of respiratory belts by extension of multiple linear regression

Respiratory belts are widely used for ventilation monitoring. After calibration they can be used quantitatively to measure breathing volume and flow. This study provides an improved calibration method for respiratory belt signals. An optimized FIR (finite impulse response) filter bank was constructed as a MISO system (multiple input, single output) between the respiratory belts and spirometer. First-order and second-order polynomials with cross-terms were tested in the transfer function. Six subjects were measured with two respiratory belts (piezo and inductive) at the same time. Results show that R2 value increased (piezo belts: 9%, inductive belts: 10%) and RMSE (root mean square error) decreased greatly (piezo belts: 36%, inductive belts: 43%) compared to the golden standard calibration method. It is concluded that the new method improves greatly the accuracy of calibration of respiratory belts.

Dynamic Changes of Nasal Airflow Resistance During Provocation with Birch Pollen Allergen

Over 500 million people suffer from allergic rhinitis around the world. This huge problem causes, in addition to individual impacts, a substantial economic burden to societies. There is a lack of an objective measurement method producing a reliable, accurate and continuous measurement data about the dynamic changes in nasal function. Here, a method to assess the nasal airflow resistance as a continuous signal is proposed and used to compute resistance values during the birch pollen provocation test. The required pressure recording is measured using a nasopharyngeal catheter and the flow recording is measured using respiratory effort belts calibrated with the new method. Ten birch pollen allergic and eleven non-allergic volunteers were challenged with control solution and allergen solution. Continuous nasal airflow resistance signals were computed and analyzed for the dynamic changes in the nasal airflow resistance. The derived signals show in great detail the intensity and timing differences in subjects’ reactions. Quantitative results of resistance changes indicate that allergic and non-allergic subjects can be differentiated in a statistically significant degree using the proposed method. The method opens entirely new possibilities to research accurately the dynamic changes in non-stationary nasal function and could increase the reliability and accuracy of diagnostics and assessment of the effect of nasal treatments.

Accurate measurement of respiratory airflow waveforms using depth data

Respiratory disorders are a very common and growing health problem. Signal waveforms of respiratory airflow and volume may indicate pathological signs of several diseases and, thus, it would be important to measure them accurately. Currently, devices used in respiration measurements are mostly obtrusive in nature interfering with the natural respiration patterns. We used a depth camera for the continuous measurement of respiratory function without contact on a subject. We propose a novel calibration method which enables accurate estimates of the respiratory airflow waveforms from the depth camera data. Eight subjects were measured with the depth camera and spirometer at the same time using different breathing styles. Results show that not only the respiratory volume and respiratory rate (RR) can be computed precisely from the estimated respiratory airflow, but also the respiratory airflow waveforms are very accurate. This offers interesting opportunities, e.g. in pulmonary and critical care medicine, when objective measurements are required.

Continuous postoperative respiratory monitoring with calibrated respiratory effort belts : pilot study

Postoperative respiratory complications are common in patients after surgery. Respiratory depression and subsequent adverse outcomes can arise from pain, residual effects of drugs given during anaesthesia and administration of opioids for pain management. There is an urgent need for a continuous, real-time and non-invasive respiratory monitoring of spontaneously breathing postoperative patients. For this purpose, we used rib cage and abdominal respiratory effort belts for the respiratory monitoring pre- and postoperatively, with a new calibration method that enables accurate estimates of the respiratory airflow waveforms even when breathing style changes. Five patients were measured with respiratory effort belts and mask spirometer. Preoperative measurements were done in the operating room, whereas postoperative measurements were done in the recovery room. We compared five calibration models with pre- and postoperative training data. The postoperative calibration approach with two respiratory effort belts produced the most accurate respiratory airflow waveforms and tidal volume, minute volume and respiratory rate estimates. Average results for the best model were: coefficient of determination R2 was 0.91, tidal volume error 5.8%, minute volume error 8.5% and BPM (Breaths per Minute) error 0.21. The method performed well even in the following challenging respiratory cases: low airflows, thoracoabdominal asynchrony and hypopneic events. It was shown that a single belt measurement can be sufficient in some cases. The proposed method is able to produce estimates of postoperative respiratory airflow waveforms to enable accurate, continuous, real-time and non-invasive respiratory monitoring postoperatively. It provides also potential to optimize postoperative pain management and enables timely interventions.