Volume acceleration as an index of neuromuscular output

Cotton, David; Sheiban, M.; Engel, L. A.

doi:10.1016/0034-5687(88)90119-3

Cited by 8 publications

(1 citation statement)

References 24 publications

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“…Inspiratory (ViVol) and expiratory volumes (VeVol), minute ventilation (Vent), and the peak inspiratory acceleration (PiaAB) are obviously highest and respiratory timing parameters are lowest (more rapid breathing) in the CO 2 inhalation phase (see Figure 4). This is exactly what can be expected, since inhaling CO 2 -enriched air leads to an increase in arterial CO 2 pressure, due to the excess level of CO 2 in the blood (hypercapnic state), and thereby reflexively increases the neuronal respiratory drive (as reflected in PiaAB; Cotton, Sheiban, & Engel, 1988; DiFiore et al, 1997) and concomitantly also minute ventilation (Pappens et al, 2012; Woods, Charney, Loke, & Goodman, 1986). Compared to the baseline phase, heart rate is increased and the cardiac RR interval is decreased during the CO 2 inhalation phase.…”

Section: Illustrative Applicationsupporting

confidence: 73%

Switching principal component analysis for modeling means and covariance changes over time.

Roover¹,

Timmerman²,

Diest³

et al. 2014

Psychological Methods

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Many psychological theories predict that cognitions, affect, action tendencies, and other variables change across time in mean level as well as in covariance structure. Often such changes are rather abrupt, because they are caused by sudden events. To capture such changes, one may repeatedly measure the variables under study for a single individual and examine whether the resulting multivariate time series contains a number of phases with different means and covariance structures. The latter task is challenging, however. First, in many cases, it is unknown how many phases there are and when new phases start. Second, often a rather large number of variables is involved, complicating the interpretation of the covariance pattern within each phase. To take up this challenge, we present switching principal component analysis (PCA). Switching PCA detects phases of consecutive observations or time points (in single subject data) with similar means and/or covariation structures, and performs a PCA per phase to yield insight into its covariance structure. An algorithm for fitting switching PCA solutions as well as a model selection procedure are presented and evaluated in a simulation study. Finally, we analyze empirical data on cardiorespiratory recordings.

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Section: Illustrative Applicationsupporting

confidence: 73%

Switching principal component analysis for modeling means and covariance changes over time.

Roover¹,

Timmerman²,

Diest³

et al. 2014

Psychological Methods

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Pneumotachographic Recording of Ventilatory Pattern

Sanchís¹,

Diez-Betoret²,

Canet³

et al. 1991

Update in Intensive Care and Emergency Medicine

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Current advances in rhinomanometry

Naito

Iwata

1997

Eur Arch Otorhinolaryngol

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Current advances in rhinomanometry were reviewed in this paper. Active posterior rhinomanometry with a "head-out" body plethysmography may be the least invasive method currently available for measuring nasal patency. In general, active anterior rhinomanometry with a face mask or a nasal nozzle has been employed in various studies throughout the world. Nasal resistance as calculated from the equation R = 0.78 (delta P/V)1.33 at any points on a pressure/flow curve, or averaged nasal resistance may be the most suitable expression for nasal patency. Values for nasal resistance at delta P 100 Pa in Japanese patients or delta P 150 Pa in Caucasians have been widely employed as standard objective data for nasal obstruction, although rhinomanometric results sometimes do not agree with subjective evaluation of nasal obstruction. Nasal airflow acceleration or peak flow index during nasal breathing at rest can be applied as warranted to confirm an objective diagnosis of symptomatic nasal obstruction. Further, nationality and anthropological characteristics can be related to the severity and type of stuffiness.

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Volume acceleration as an index of neuromuscular output

Cited by 8 publications

References 24 publications

Switching principal component analysis for modeling means and covariance changes over time.

Switching principal component analysis for modeling means and covariance changes over time.

Pneumotachographic Recording of Ventilatory Pattern

Current advances in rhinomanometry

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