A telemedicine instrument for Internet-based home monitoring of thoracoabdominal motion in patients with respiratory diseases

Instantaneous phase difference analysis between thoracic and abdominal movement signals based on complementary ensemble empirical mode decomposition

BACKGROUND

Thoracoabdominal asynchrony is often adopted to discriminate respiratory diseases in clinics. Conventionally, Lissajous figure analysis is the most frequently used estimation of the phase difference in thoracoabdominal asynchrony. However, the temporal resolution of the produced results is low and the estimation error increases when the signals are not sinusoidal. Other previous studies have reported time-domain procedures with the use of band-pass filters for phase-angle estimation. Nevertheless, the band-pass filters need calibration for phase delay elimination.

METHODS

To improve the estimation, we propose a novel method (named as instantaneous phase difference) that is based on complementary ensemble empirical mode decomposition for estimating the instantaneous phase relation between measured thoracic wall movement and abdominal wall movement. To validate the proposed method, experiments on simulated time series and human-subject respiratory data with two breathing types (i.e., thoracic breathing and abdominal breathing) were conducted. Latest version of Lissajous figure analysis and automatic phase estimation procedure were compared.

RESULTS

The simulation results show that the standard deviations of the proposed method were lower than those of two other conventional methods. The proposed method performed more accurately than the two conventional methods. For the human-subject respiratory data, the results of the proposed method are in line with those in the literature, and the correlation analysis result reveals that they were positively correlated with the results generated by the two conventional methods. Furthermore, the standard deviation of the proposed method was also the smallest.

CONCLUSIONS

To summarize, this study proposes a novel method for estimating instantaneous phase differences. According to the findings from both the simulation and human-subject data, our approach was demonstrated to be effective. The method offers the following advantages: (1) improves the temporal resolution, (2) does not introduce a phase delay, (3) works with non-sinusoidal signals, (4) provides quantitative phase estimation without estimating the embedded frequency of breathing signals, and (5) works without calibrated measurements. The results demonstrate a higher temporal resolution of the phase difference estimation for the evaluation of thoracoabdominal asynchrony.

A new system for continuous and remote monitoring of patients receiving home mechanical ventilation

Home mechanical ventilation is the treatment of patients with respiratory failure or insufficiency by means of a mechanical ventilator at a patient's home. In order to allow remote patient monitoring, several tele-monitoring systems have been introduced in the last few years. However, most of them usually do not allow real-time services, as they have their own proprietary communication protocol implemented and some ventilation parameters are not always measured. Moreover, they monitor only some breaths during the whole day, despite the fact that a patient's respiratory state may change continuously during the day. In order to reduce the above drawbacks, this work reports the development of a novel remote monitoring system for long-term, home-based ventilation therapy; the proposed system allows for continuous monitoring of the main physical quantities involved during home-care ventilation (e.g., differential pressure, volume, and air flow rate) and is developed in order to allow observations of different remote therapy units located in different places of a city, region, or country. The developed remote patient monitoring system is able to detect various clinical events (e.g., events of tube disconnection and sleep apnea events) and has been successfully tested by means of experimental tests carried out with pulmonary ventilators typically used to support sick patients.

Forced oscillation, integer and fractional-order modeling in asthma

The purpose of this study was to evaluate the use of fractional-order (FrOr) modeling in asthma. To this end, three FrOr models were compared with traditional parameters and an integer-order model (InOr). We investigated which model would best fit the data, the correlation with traditional lung function tests and the contribution to the diagnostic of airway obstruction. The data consisted of forced oscillation (FO) measurements obtained from healthy (n=22) and asthmatic volunteers with mild (n=22), moderate (n=19) and severe (n=19) obstructions. The first part of this study showed that a FrOr was the model that best fit the data (relative distance: FrOr=4.3±2.4; InOr=5.1±2.6%). The correlation analysis resulted in reasonable (R=0.36) to very good (R=0.77) associations between FrOr parameters and spirometry. The closest associations were observed between parameters related to peripheral airway obstruction, showing a clear relationship between the FrOr models and lung mechanics. Receiver-operator analysis showed that FrOr parameters presented a high potential to contribute to the detection of the mild obstruction in a clinical setting. The accuracy [area under the Receiver Operating Characteristic curve (AUC)] observed in these parameters (AUC=0.954) was higher than that observed in traditional FO parameters (AUC=0.732) and that obtained from the InOr model (AUC=0.861). Patients with moderate and severe obstruction were identified with high accuracy (AUC=0.972 and 0.977, respectively). In conclusion, the results obtained are in close agreement with asthma pathology, and provide evidence that FO measurement associated with FrOr models is a non-invasive, simple and radiation-free method for the detection of biomechanical abnormalities in asthma.

Development of an integrated sensor module for a non-invasive respiratory monitoring system

A respiratory monitoring system has been developed for analyzing the carbon dioxide (CO2) and oxygen (O2) concentrations in the expired air using gas sensors. The data can be used to estimate some medical conditions, including diffusion capability of the lung membrane, oxygen uptake, and carbon dioxide output. For this purpose, a 3-way valve derived from a servomotor was developed, which operates synchronously with human respiratory signals. In particular, the breath analysis system includes an integrated sensor module for valve control, data acquisition through the O2 and CO2 sensors, and respiratory rate monitoring, as well as software dedicated to analysis of respiratory gasses. In addition, an approximation technique for experimental data based on Haar-wavelet-based decomposition is explored to remove noise as well as to reduce the file size of data for long-term monitoring.

Airflow pattern complexity and airway obstruction in asthma

The scientific and clinical value of a measure of complexity is potentially enormous because complexity appears to be lost in the presence of illness. The authors examined the effect of elevated airway obstruction on the complexity of the airflow (Q) pattern of asthmatic patients analyzing the airflow approximate entropy (ApEnQ). This study involved 11 healthy controls, 11 asthmatics with normal spirometric exams, and 40 asthmatics with mild (14), moderate (14), and severe (12) airway obstructions. A significant (P < 0.02) reduction in the ApEnQ was observed in the asthmatic patients. This reduction was significantly correlated with spirometric indexes of airway obstruction [FEV(1) (%): R = 0.31, P = 0.013] and the total respiratory impedance (R = -0.39; P < 0.002). These results are in close agreement with pathophysiological fundamentals and suggest that the airflow pattern becomes less complex in asthmatic patients, which may reduce the adaptability of the respiratory system to perform the exercise that is associated with daily life activities. This analysis was able to identify respiratory changes in patients with mild obstruction with an adequate accuracy (83%). Higher accuracies were obtained in patients with moderate and severe obstructions. The analysis of airflow pattern complexity by the ApEnQ was able to provide new information concerning the changes associated with asthma. In addition, this analysis was also able to contribute to the detection of the adverse effects of asthma. Because these measurements are easy to perform, such a technique may represent an alternative and/or a complement to other conventional exams to help the clinical evaluations of asthmatic patients.