Respiratory Monitoring Based on Tracheal Sounds: Continuous Time-Frequency Processing of the Phonospirogram Combined with Phonocardiogram-Derived Respiration

Lu, Xinyue; Coste, Christine; Niérat, Marie-Cécile; Renaux, Serge; Similowski, Thomas; Guiraud, David

doi:10.3390/s21010099

Cited by 8 publications

(4 citation statements)

References 22 publications

(29 reference statements)

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“…As shown in Figure 2 and Figure 4 , the amplitude of the LF-FCG and HF-FCG signals appeared to be modulated by respiration. Various studies on SCG [ 8 , 9 , 30 , 31 , 32 ] and heart sounds [ 33 , 34 , 35 , 36 ] have found consistent variation in the amplitude of signals during various phases of the respiratory cycle, and nearly no variability during apnea. These results are consistent with those obtained from this study.…”

Section: Discussionmentioning

confidence: 99%

Respiratory-Induced Amplitude Modulation of Forcecardiography Signals

2022

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Forcecardiography (FCG) is a novel technique that records the weak forces induced on the chest wall by cardio-respiratory activity, by using specific force sensors. FCG sensors feature a wide frequency band, which allows us to capture respiration, heart wall motion, heart valves opening and closing (similar to the Seismocardiogram, SCG) and heart sounds, all simultaneously from a single contact point on the chest. As a result, the raw FCG sensors signals exhibit a large component related to the respiratory activity, referred to as a Forcerespirogram (FRG), with a much smaller, superimposed component related to the cardiac activity (the actual FCG) that contains both infrasonic vibrations, referred to as LF-FCG and HF-FCG, and heart sounds. Although respiration can be readily monitored by extracting the very low-frequency component of the raw FCG signal (FRG), it has been observed that the respiratory activity also influences other FCG components, particularly causing amplitude modulations (AM). This preliminary study aimed to assess the consistency of the amplitude modulations of the LF-FCG and HF-FCG signals within the respiratory cycle. A retrospective analysis was performed on the FCG signals acquired in a previous study on six healthy subjects at rest, during quiet breathing. To this aim, the AM of LF-FCG and HF-FCG were first extracted via a linear envelope (LE) operation, consisting of rectification followed by low-pass filtering; then, the inspiratory peaks were located both in the LE of LF-FCG and HF-FCG, and in the reference respiratory signal (FRG). Finally, the inter-breath intervals were extracted from the obtained inspiratory peaks, and further analyzed via statistical analyses. The AM of HF-FCG exhibited higher consistency within the respiratory cycle, as compared to the LF-FCG. Indeed, the inspiratory peaks were recognized with a sensitivity and positive predictive value (PPV) in excess of 99% in the LE of HF-FCG, and with a sensitivity and PPV of 96.7% and 92.6%, respectively, in the LE of LF-FCG. In addition, the inter-breath intervals estimated from the HF-FCG scored a higher R2 value (0.95 vs. 0.86) and lower limits of agreement (± 0.710 s vs. ±1.34 s) as compared to LF-FCG, by considering those extracted from the FRG as the reference. The obtained results are consistent with those observed in previous studies on SCG. A possible explanation of these results was discussed. However, the preliminary results obtained in this study must be confirmed on a larger cohort of subjects and in different experimental conditions.

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Section: Discussionmentioning

confidence: 99%

Respiratory-Induced Amplitude Modulation of Forcecardiography Signals

2022

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“…The above clinical research was consistent with our study, which illustrated that the EPR combined with EDP therapy could increase the activity of the diaphragm in patients, thereby ensuring the oxygen supply. At the same time, this treatment also promotes the recruitment of and maintains the proportion of diaphragmatic fibres and slows down diaphragmatic atrophy [28].…”

Section: Discussionmentioning

confidence: 99%

Clinical effect of pulmonary rehabilitation combined with diaphragm pacemaker therapy in the treatment of severely ill patients with mechanical ventilation

Liu

Wang

Zhao

et al. 2022

International Journal of Rehabilitation Research

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To investigate the effect of pulmonary rehabilitation combined with diaphragm pacemaker therapy on the diaphragm function of severely ill patients on mechanical ventilation. Forty patients were randomly divided into the control group (CG; n = 20) and experimental group (EG; n = 20). The CG was given basic ICU nursing and conventional rehabilitation treatment. The EG added a diaphragm pacemaker and pulmonary rehabilitation therapies along with basic ICU nursing and conventional rehabilitation treatment. The relevant indexes were compared at baseline and postintervention, including the Glasgow Coma Scale (GCS), Acute Physiology, Chronic Health Evaluation II (APACHE II) scores, diaphragm mobility and thickness. The indexes of mechanical ventilation time, ICU and total hospital stays were compared between the two groups. There was no difference in the GCS and APACHE II scores, and diaphragm mobility and thickness between the two groups before treatment (P > 0.05). After 30 days of treatment, the GCS scores increased in both groups, the APACHE II scores decreased significantly, and diaphragm mobility and thickness decreased compared with before treatment (P < 0.05), but the improvement of each index in the EG was more evident than in the CG. Compared with the CG, the indexes of the EG, including offline, ICU and total hospitalization times, were significantly shorter (P < 0.05). Additionally, there were no adverse events such as accidental tube detachment or falling out of bed during treatment. Pulmonary rehabilitation combined with a diaphragm pacemaker is safe and effective in treating severely ill mechanically ventilated patients.

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“…Lu's team proposed a method of breathing monitoring based on tracheal sounds called cardiac sound-derived respiration (PDR). They collected sound signals, then postprocessed the recordings in both the time domain and frequency detection domains, and finally compared them with electrocardiograms to detect apnea [15]. Preeti Jagadev et al used infrared imaging equipment to detect respiration by observing the temperature changes of the chest, neck, mouth and nose during respiration and extracting dynamic thermal eigenvalues, but this method was greatly affected by ambient temperature [16].…”

Section: Introductionmentioning

confidence: 99%

Cheyne-Stokes Respiration Perception via Machine Learning Algorithms

et al. 2022

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With the development of science and technology, transparent, non-invasive general computing is gradually applied to disease diagnosis and medical detection. Universal software radio peripherals (USRP) enable non-contact awareness based on radio frequency signals. Cheyne-Stokes respiration has been reported as a common symptom in patients with heart failure. Compared with the disadvantages of traditional detection equipment, a microwave sensing method based on channel state information (CSI) is proposed to qualitatively detect the normal breathing and Cheyne-Stokes breathing of patients with heart failure in a non-contact manner. Firstly, USRP is used to collect subjects’ respiratory signals in real time. Then the CSI waveform is filtered, smoothed and normalized, and the relevant features are defined and extracted from the signal. Finally, the machine learning classification algorithm is used to establish a recognition model to detect the Cheyne-Stokes respiration of patients with heart failure. The results show that the system accuracy of support vector machine (SVM) is 97%, which can assist medical workers to identify Cheyne-Stokes respiration symptoms of patients with heart failure.

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Respiratory Monitoring Based on Tracheal Sounds: Continuous Time-Frequency Processing of the Phonospirogram Combined with Phonocardiogram-Derived Respiration

Cited by 8 publications

References 22 publications

Respiratory-Induced Amplitude Modulation of Forcecardiography Signals

Respiratory-Induced Amplitude Modulation of Forcecardiography Signals

Clinical effect of pulmonary rehabilitation combined with diaphragm pacemaker therapy in the treatment of severely ill patients with mechanical ventilation

Cheyne-Stokes Respiration Perception via Machine Learning Algorithms

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