Early experience with remote pressure sensor respiratory plethysmography monitoring sedation in the MR scanner

Caldiroli, Dario; Minati, Ludovico

doi:10.1017/s0265021507000312

Cited by 4 publications

(5 citation statements)

References 23 publications

(31 reference statements)

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“…Three documents investigated the accuracy of either pressure [ 19 , 37 ] or tactile sensors [ 43 ]. Caldiroli and Minati explored the feasibility of using remote pressure sensor plethysmography to monitor children undergoing sedation in an MR scanner [ 37 ]. However, the authors could only report the outcome of the proposed sensory strategy compared to that assessed by a high-precision spirometer in healthy subjects underquasi-static conditions.…”

Section: Discussionmentioning

confidence: 99%

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Assessing the Tidal Volume through Wearables: A Scoping Review

Monaco

Stefanini

2021

Sensors

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The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable devices to monitor the tidal volume during both daily activities and clinical settings. A screening of the literature (Pubmed, Scopus, and Web of Science) was carried out in December 2020 to collect studies: i. comparing one or more methodological approaches for the assessment of tidal volume with the outcome of a state-of-the-art measurement device (i.e., spirometry or optoelectronic plethysmography); ii. dealing with technological solutions designed to be exploited in wearable devices. From the initial 1031 documents, only 36 citations met the eligibility criteria. These studies highlighted that the tidal volume can be estimated by using different technologies ranging from IMUs to strain sensors (e.g., resistive, capacitive, inductive, electromagnetic, and optical) or acoustic sensors. Noticeably, the relative volumetric error of these solutions during quasi-static tasks (e.g., resting and sitting) is typically ≥10% but it deteriorates during dynamic motor tasks (e.g., walking). As such, additional efforts are required to improve the performance of these devices and to identify possible applications based on their accuracy and reliability.

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Section: Discussionmentioning

confidence: 99%

Section: Alternative Strategiesmentioning

confidence: 99%

Assessing the Tidal Volume through Wearables: A Scoping Review

Monaco

Stefanini

2021

Sensors

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“…Eight frontal electrodes were excluded due to headrest contact. The respiratory activity was monitored, separately for the thorax and abdomen compartments, using pneumatic sensor belts [22]. The plethysmographic signal, indexing cardiovascular arousal, was recorded via a photoplethysmograph (type 8600; Nonin Medical Inc., Plymouth, MN, USA).…”

Section: Plos Onementioning

confidence: 99%

Behavioral and physiological correlates of kinetically tracking a chaotic target

et al. 2020

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Humans can innately track a moving target by anticipating its future position from a brief history of observations. While ballistic trajectories can be readily extrapolated, many natural and artificial systems are governed by more general nonlinear dynamics and, therefore, can produce highly irregular motion. Yet, relatively little is known regarding the behavioral and physiological underpinnings of prediction and tracking in the presence of chaos. Here, we investigated in lab settings whether participants could manually follow the orbit of a paradigmatic chaotic system, the Rö ssler equations, on the (x,y) plane under different settings of a control parameter, which determined the prominence of transients in the target position. Tracking accuracy was negatively related to the level of unpredictability and folding. Nevertheless, while participants initially reacted to the transients, they gradually learned to anticipate it. This was accompanied by a decrease in muscular co-contraction, alongside enhanced activity in the theta and beta EEG bands for the highest levels of chaoticity. Furthermore, greater phase synchronization of breathing was observed. Taken together, these findings point to the possible ability of the nervous system to implicitly learn topological regularities even in the context of highly irregular motion, reflecting in multiple observables at the physiological level.

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“…The resulting signal was epoched in the [-0.5,5] s peristimulus range and averaged across trials. Respiratory motor function was recorded within the MRI environment via respiratory bands, a technique referred to as remote pressure sensor respiratory plethysmography ( Caldiroli and Minati, 2007 ). Again the signal was low-pass filtered at 1 Hz and processed with a peak-picking algorithm yielding breathing rate measurements ( Figure 2 ).…”

Section: Methodsmentioning

confidence: 99%

Neuroanatomical substrates for the volitional regulation of heart rate

et al. 2015

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The control of physiological arousal can assist in the regulation of emotional state. A subset cortical and subcortical brain regions are implicated in autonomic control of bodily arousal during emotional behaviors. Here, we combined human functional neuroimaging with autonomic monitoring to identify neural mechanisms that support the volitional regulation of heart rate, a process that may be assisted by visual feedback. During functional magnetic resonance imaging (fMRI), 15 healthy adults performed an experimental task in which they were prompted voluntarily to increase or decrease cardiovascular arousal (heart rate) during true, false, or absent visual feedback. Participants achieved appropriate changes in heart rate, without significant modulation of respiratory rate, and were overall not influenced by the presence of visual feedback. Increased activity in right amygdala, striatum and brainstem occurred when participants attempted to increase heart rate. In contrast, activation of ventrolateral prefrontal and parietal cortices occurred when attempting to decrease heart rate. Biofeedback enhanced activity within occipito-temporal cortices, but there was no significant interaction with task conditions. Activity in regions including pregenual anterior cingulate and ventral striatum reflected the magnitude of successful task performance, which was negatively related to subclinical anxiety symptoms. Measured changes in respiration correlated with posterior insula activation and heart rate, at a more lenient threshold, change correlated with insula, caudate, and midbrain activity. Our findings highlight a set of brain regions, notably ventrolateral prefrontal cortex, supporting volitional control of cardiovascular arousal. These data are relevant to understanding neural substrates supporting interaction between intentional and interoceptive states related to anxiety, with implications for biofeedback interventions, e.g., real-time fMRI, that target emotional regulation.

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Early experience with remote pressure sensor respiratory plethysmography monitoring sedation in the MR scanner

Cited by 4 publications

References 23 publications

Assessing the Tidal Volume through Wearables: A Scoping Review

Assessing the Tidal Volume through Wearables: A Scoping Review

Behavioral and physiological correlates of kinetically tracking a chaotic target

Neuroanatomical substrates for the volitional regulation of heart rate

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