by Keyword: Patient monitoring

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Lozano-García, M., Estrada-Petrocelli, L., Moxham, J., Rafferty, G. F., Torres, A., Jolley, C. J., Jané, R. , (2019). Noninvasive assessment of inspiratory muscle neuromechanical coupling during inspiratory threshold loading IEEE Access 7, 183634-183646

Diaphragm neuromechanical coupling (NMC), which reflects the efficiency of conversion of neural activation to transdiaphragmatic pressure (Pdi), is increasingly recognized to be a useful clinical index of diaphragm function and respiratory mechanics in neuromuscular weakness and cardiorespiratory disease. However, the current gold standard assessment of diaphragm NMC requires invasive measurements of Pdi and crural diaphragm electromyography (oesEMGdi), which complicates the measurement of diaphragm NMC in clinical practice. This is the first study to compare invasive measurements of diaphragm NMC (iNMC) using the relationship between Pdi and oesEMGdi, with noninvasive assessment of NMC (nNMC) using surface mechanomyography (sMMGlic) and electromyography (sEMGlic) of lower chest wall inspiratory muscles. Both invasive and noninvasive measurements were recorded in twelve healthy adult subjects during an inspiratory threshold loading protocol. A linear relationship between noninvasive sMMGlic and sEMGlic measurements was found, resulting in little change in nNMC with increasing inspiratory load. By contrast, a curvilinear relationship between invasive Pdi and oesEMGdi measurements was observed, such that there was a progressive increase in iNMC with increasing inspiratory threshold load. Progressive recruitment of lower ribcage muscles, serving to enhance the mechanical advantage of the diaphragm, may explain the more linear relationship between sMMGlic and sEMGlic (both representing lower intercostal plus costal diaphragm activity) than between Pdi and crural oesEMGdi. Noninvasive indices of NMC derived from sEMGlic and sMMGlic may prove to be useful indices of lower chest wall inspiratory muscle NMC, particularly in settings that do not have access to invasive measures of diaphragm function.

Keywords: Cardiovascular system, Diaphragms, Diseases, Electromyography, Medical signal processing, Neurophysiology, Patient monitoring, Pneumodynamics, Inspiratory muscle neuromechanical coupling, Diaphragm neuromechanical coupling, Neural activation, Transdiaphragmatic pressure, Diaphragm function, Respiratory mechanics, Diaphragm NMC, Invasive measurements, Crural diaphragm electromyography, iNMC, Noninvasive assessment, nNMC, Lower chest wall inspiratory muscles, Inspiratory threshold loading protocol, Noninvasive sMMGlic measurements, sEMGlic measurements, oesEMGdi measurements, Inspiratory threshold load, Lower ribcage muscles, Lower intercostal plus costal diaphragm activity, Crural oesEMGdi, Noninvasive indices, sEMGlic sMMGlic, Lower chest wall inspiratory muscle NMC, Surface mechanomyography, Electromyography, Inspiratory threshold loading, Mechanomyography, Neuromechanical coupling, Respiratory muscles

Giraldo, B.F., Gaspar, B.W., Caminal, P., Benito, S., (2012). Analysis of roots in ARMA model for the classification of patients on weaning trials Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 698-701

One objective of mechanical ventilation is the recovery of spontaneous breathing as soon as possible. Remove the mechanical ventilation is sometimes more difficult that maintain it. This paper proposes the study of respiratory flow signal of patients on weaning trials process by autoregressive moving average model (ARMA), through the location of poles and zeros of the model. A total of 151 patients under extubation process (T-tube test) were analyzed: 91 patients with successful weaning (GS), 39 patients that failed to maintain spontaneous breathing and were reconnected (GF), and 21 patients extubated after the test but before 48 hours were reintubated (GR). The optimal model was obtained with order 8, and statistical significant differences were obtained considering the values of angles of the first four poles and the first zero. The best classification was obtained between GF and GR, with an accuracy of 75.3% on the mean value of the angle of the first pole.

Keywords: Analytical models, Biological system modeling, Computational modeling, Estimation, Hospitals, Poles and zeros, Ventilation, Autoregressive moving average processes, Patient care, Patient monitoring, Pneumodynamics, Poles and zeros, Ventilation, ARMA model, T-tube test, Autoregressive moving average model, Extubation process, Mechanical ventilation, Optimal model, Patient classification, Respiratory flow signal, Roots, Spontaneous breathing, Weaning trials

Leder, R. S., Schlotthauer, G., Penzel, T., Jané, R., (2010). The natural history of the sleep and respiratory engineering track at EMBC 1988 to 2010 Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 288-291

Sleep science and respiratory engineering as medical subspecialties and research areas grew up side-by-side with biomedical engineering. The formation of EMBS in the 1950's and the discovery of REM sleep in the 1950's led to parallel development and interaction of sleep and biomedical engineering in diagnostics and therapeutics.

Keywords: Practical/ biomedical equipment, Biomedical measurement, Patient diagnosis, Patient monitoring, Patient treatment, Pneumodynamics, Sleep/ sleep engineering, Respiratory engineering, Automatic sleep analysis, Automatic sleep interpretation systems, Breathing, Biomedical, Engineering, Diagnostics, Therapeutics, REM sleep, Portable, Measurement, Ambulatory measurement, Monitoring