Publications

Breathing pattern has been shown to be different in chronic obstructive pulmonary disease (COPD) patients compared to healthy controls during rest and walking. In this study we evaluated respiratory parameters and the breathing variability of COPD patients as a function of their severity. Thoracic bioimpedance was acquired on 66 COPD patients during the performance of the six-minute walk test (6MWT), as well as 5 minutes before and after the test while the patients were seated, i.e. resting and recovery phases. The patients were classified by their level of airflow limitation into moderate and severe groups. We characterized the breathing patterns by evaluating common respiratory parameters using only wearable bioimpedance. Specifically, we computed the median and the coefficient of variation of the parameters during the three phases of the protocol, and evaluated the statistical differences between the two COPD severity groups. We observed significant differences between the COPD severity groups only during the sitting phases, whereas the behavior during the 6MWT was similar. Particularly, we observed an inverse relationship between breathing pattern variability and COPD severity, which may indicate that the most severely diseased patients had a more restricted breathing compared to the moderate patients.

JTD Keywords: 6mwt, activation, breathing pattern, burden, chronic obstructive pulmonary disease, exercise, muscles, pressure, pulmonary, signals, variability, volumes, wearables, Bioimpedance, Impedance pneumography

© 1964-2012 IEEE. Chronic Obstructive Pulmonary Disease (COPD) is one of the most common chronic conditions. The current assessment of COPD requires a maximal maneuver during a spirometry test to quantify airflow limitations of patients. Other less invasive measurements such as thoracic bioimpedance and myographic signals have been studied as an alternative to classical methods as they provide information about respiration. Particularly, strong correlations have been shown between thoracic bioimpedance and respiratory volume. The main objective of this study is to investigate bioimpedance and its combination with myographic parameters in COPD patients to assess the applicability in respiratory disease monitoring. We measured bioimpedance, surface electromyography and surface mechanomyography in forty-three COPD patients during an incremental inspiratory threshold loading protocol. We introduced two novel features that can be used to assess COPD condition derived from the variation of bioimpedance and the electrical and mechanical activity during each respiratory cycle. These features demonstrate significant differences between mild and severe patients, indicating a lower inspiratory contribution of the inspiratory muscles to global respiratory ventilation in the severest COPD patients. In conclusion, the combination of bioimpedance and myographic signals provides useful indices to noninvasively assess the breathing of COPD patients.

JTD Keywords: Bioimpedance, Chronic obstructive pulmonary disease, Inspiratory threshold protocol, Myographic signals, Wearables

Many studies have focused on novel noninvasive techniques to monitor respiratory rate such as bioimpedance. We propose an algorithm to detect respiratory phases using wearable bioimpedance to compute time parameters like respiratory rate, inspiratory and expiratory times, and duty cycle. The proposed algorithm was compared with two other algorithms from literature designed to estimate the respiratory rate using physiological signals like bioimpedance. We acquired bioimpedance and airflow from 50 chronic obstructive pulmonary disease (COPD) patients during an inspiratory loading protocol. We compared performance of the algorithms by computing accuracy and mean average percentage error (MAPE) between the bioimpedance parameters and the reference parameters from airflow. We found similar performance for the three algorithms in terms of accuracy (>0.96) and respiratory time and rate errors (<3.42 %). However, the proposed algorithm showed lower MAPE in duty cycle (10.18 %), inspiratory time (10.65 %) and expiratory time (8.61 %). Furthermore, only the proposed algorithm kept the statistical differences in duty cycle between COPD severity levels that were observed using airflow. Accordingly, we suggest bioimpedance to monitor breathing pattern parameters in home situations.Clinical relevance - This study exhibits the suitability of wearable thoracic bioimpedance to detect respiratory phases and to compute accurate breathing pattern parameters. © 2021 IEEE.

JTD Keywords: algorithms, copd, signals, Algorithm, Algorithms, Bioimpedance, Breathing rate, Chronic obstructive lung disease, Electronic device, Human, Humans, Lung, Pulmonary disease, chronic obstructive, Respiratory rate, Wearable electronic devices

Bioimpedance is an unobtrusive noninvasive technique to measure respiration and has a linear relation with volume during normal breathing. The objective of this paper was to assess this linear relation during inspiratory loading protocol and determine the best electrode configuration for bioimpedance measurement. The inspiratory load is a way to estimate inspiratory muscle function and has been widely used in studies of respiratory mechanics. Therefore, this protocol permitted us to evaluate bioimpedance performance under breathing pattern changes. We measured four electrode configurations of bioimpedance and airflow simultaneously in ten healthy subjects using a wearable device and a standard wired laboratory acquisition system, respectively. The subjects were asked to perform an incremental inspiratory threshold loading protocol during the measurements. The load values were selected to increase progressively until the 60% of the subject's maximal inspiratory pressure. The linear relation of the signals was assessed by Pearson correlation (r ) and the waveform agreement by the mean absolute percentage error (MAPE), both computed cycle by cycle. The results showed a median greater than 0.965 in r coefficients and lower than 11 % in the MAPE values for the entire population in all loads and configurations. Thus, a strong linear relation was found during all loaded breathing and configurations. However, one out of the four electrode configurations showed robust results in terms of agreement with volume during the highest load. In conclusion, bioimpedance measurement using a wearable device is a noninvasive and a comfortable alternative to classical methods for monitoring respiratory diseases in normal and restrictive breathing.

JTD Keywords: Bioimpedance, Chronic respiratory diseases, Electrode configurations, Inspiratory threshold protocol, Wearable

Bioimpedance is known for its linear relation with volume during normal breathing. For that reason, bioimpedance can be used as a noninvasive and comfortable technique for measuring respiration. The goal of this study is to analyze the temporal behavior of bioimpedance measured in four different electrode configurations during inspiratory loaded breathing. We measured four bioimpedance channels and airflow simultaneously in 10 healthy subjects while incremental inspiratory loads were imposed. Inspiratory loading threshold protocols are associated with breathing pattern changes and were used in respiratory mechanics studies. Consequently, this respiratory protocol allowed us to induce breathing pattern changes and evaluate the temporal relationship of bioimpedance with volume. We estimated the temporal delay between bioimpedance and volume respiratory cycles to evaluate the differences in their temporal behavior. The delays were computed as the lag which maximize the cross-correlation of the signals cycle by cycle. Six of the ten subjects showed delays in at least two different inspiratory loads. The delays were dependent on electrode configuration, hence the appearance of the delays between bioimpedance and volume were conditioned to the location and geometry of the electrode configuration. In conclusion, the delays between these signals could provide information about breathing pattern when breathing conditions change.

JTD Keywords: Bioimpedance, Delays, Electrodes, Protocols, Loading, Electrocardiography, Atmospheric measurements