Influence of thoracoabdominal pattern of breathing on respiratory resistance

Is age rating enough to investigate changes in breathing motion pattern associated with aging of physically active women?

The most common way to analyze the effect of aging on breathing is to divide subjects into age groups. However, in addition to the fact that there is no consensus in the literature regarding age group division, such design critically influences the interpretation of the effects attributed to aging. Thus, this study aimed to investigate the feasibility to distinguish different age groups from the 3D kinematic variables of breathing motion (i.e., markers' coordinate as a function of time allowing the calculation of compartmental volume variations) and to analyze whether the aging could influence these variables. Seventy-three physically active women aged 19-80 years performed quiet breathing and vital capacity maneuvers. To record the thoracoabdominal breathing motion, the 3D coordinates of 32 retroreflective markers positioned on the trunk were used to estimate the volume variation of the superior thorax, inferior thorax, and abdomen. The percentage of contribution and the correlation coefficient were calculated to analyze the breathing motion pattern from the estimated volumes. The k-means cluster analysis was performed to analyze the age group classification. Linear regression was performed to investigate whether age can predict changes in the breathing motion pattern. The results showed that physically active women could not be classified into age groups from breathing motion. Despite significant p values of the linear regression, the high variability of the data suggested that age itself is not enough to predict the changes in breathing motion pattern when non-sedentary women are considered.

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.

Thoraco-abdominal asynchrony in children during quiet sleep using Hilbert transform

We present a technique based on the Hilbert transform to quantify the thoraco-abdominal asynchrony (TAA) based on the phase shift between ribcage (RC) and abdomenal (AB) breathing signals acquired using respiratory inductive plethysmography (RIP). We employed this method to investigate RIP during overnight polysomnography (PSG) in 40 healthy children for analysis of their breathing patterns in various stages of sleep (ss 2, 3, 4 and REM) and in two common sleeping positions (supine and lateral). RIP signals free of respiratory or movement artifacts were segmented into 30 second epochs. Those epochs with maximum power in the quiet breathing frequency range and positional invariance throughout were included for further processing. TAA was calculated from corresponding RC and AB excursions. We found a statistically significant influence of sleep position on the level of TAA in all stages of non-REM sleep. In conclusion, the Hilbert transform provides a simple tool for the quantification of thoraco-abdominal asynchrony.

Influence of different breathing maneuvers on internal and external organ motion: Use of fiducial markers in dynamic MRI

PURPOSE

To investigate, with dynamic magnetic resonance imaging (dMRI) and a fiducial marker, the influence of different breathing maneuvers on internal organ and external chest wall motion.

METHODS AND MATERIALS

Lung and chest wall motion of 16 healthy subjects (13 male, 3 female) were examined with real-time trueFISP (true fast imaging with steady-state precession) dMRI and a small inductively coupled marker coil on either the abdomen or thorax. Three different breathing maneuvers were performed (predominantly "abdominal breathing," "thoracic breathing," and unspecific "normal breathing"). The craniocaudal (CC), anteroposterior (AP), and mediolateral (ML) lung distances were correlated (linear regression coefficient) with marker coil position during forced and quiet breathing.

RESULTS

Differences of the CC distance between maximum forced inspiration and expiration were significant between abdominal and thoracic breathing (p < 0.05). The correlation between CC distance and coil position was best for forced abdominal breathing and a marker coil in the abdominal position (r = 0.89 +/- 0.04); for AP and ML distance, forced thoracic breathing and a coil in the thoracic position was best (r = 0.84 +/- 0.03 and 0.82 +/- 0.03, respectively). In quiet breathing, a lower correlation was found.

CONCLUSION

A fiducial marker coil external to the thorax in combination with dMRI is a new technique to yield quantitative information on the correlation of internal organ and external chest wall motion. Correlations are highly dependent on the breathing maneuver.

Relationship between Respiratory Movements and Energy Efficiency in the Post-Exercise Recovery Phase

The breathing movement is highly automated but it can be voluntarily controlled in some situations. Compared with period of exercise and post-exercise, subjects could control breathing more voluntarily in the post-exercise recovery phase. So, we analyzed relationship between the strategy for controlling the breathing movement pattern and energy efficiency in this phase. Fifteen healthy men (mean age, 22.1 years) were subjected to exercise with a bicycle ergometer at 100 W for 5 minutes, then respiratory pattern was measured four times for 5 minutes after exercise. The measurement items were 1) chest expansion, 2) abdomen expansion, 3) tidal volume, 4) respiration rate, 5) minute ventilation, 6) oxygen intake, and 7) heart rate. The items 1) and 2) were measured by a three-dimensional motion analysis system, and the items 3) through 7) were measured by a respiratory gas analyzer. As for the breathing movement pattern, there were differences among the subjects in terms of the rates of increase in chest expansion and in respiration rate after exercise. The subjects were classified into 4 groups according to these differences. The group, in which respiration rate was increased, showed the marked increase in minute ventilation and oxygen intake, and the rapid recovery of heart rate. The group, in which chest expansion rate was increased, on the other hand, showed small increase in minute ventilation and oxygen intake, and the slow recovery of heart rate. The breathing strategies which are beneficial to energy efficiency exist, however, healthy men do not always select the beneficial strategies.