An Alternative Way to Measure Tidal Volumes

Laufer, Bernhard; Krueger-Ziolek, Sabine; Docherty, Paul; Höflinger, Fabian; Reindl, Leonhard M.; Möeller, Knut

doi:10.1007/978-3-030-64610-3_9

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…Nine of the retained studies tested the feasibility and accuracy of using an optical sensor-based approach to assess the tidal volume ( Table 2 ) [ 12 , 34 , 50 , 52 , 54 , 55 , 56 , 58 , 60 ]. Noticeably, these studies have been carried out by five independent research groups; thus, some of the reported results appeared redundant.…”

Section: Discussionmentioning

confidence: 99%

“…Remarkably, this approach is intrinsically magnetic-resonance compatible, as highlighted by Massaroni and colleagues [ 55 ]. The second approach is based on optical encoders sliding over an inextensible code strip coupled with stretchable bands; it is sensitive to changes in trunk circumference due to breathing [ 52 ]. In both cases, sensors can be arranged in a network whose output is parsed out by a suitable calibration model to provide an estimation of the tidal volume.…”

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: Discussionmentioning

confidence: 99%

Assessing the Tidal Volume through Wearables: A Scoping Review

Monaco

Stefanini

2021

Sensors

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“…A previous study [3] has shown that upper body movements are in some cases highly correlated with changes in respiratory volumes. This fact can be utilized for the determination of respiratory volumes via upper body movements, and some current approaches used inertial measurement units [18][19][20], others used strain gauges [21,22] or optical encoder systems, as in belts measuring changes in circumferences [23][24][25]. However, a real breakthrough has not been achieved yet despite the potential of new, improved and miniaturized sensors or sensor technologies [26,27].…”

Section: Introductionmentioning

confidence: 99%

Sensor Selection for Tidal Volume Determination via Linear Regression—Impact of Lasso versus Ridge Regression

Laufer,

Docherty,

Murray

et al. 2023

Sensors

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The measurement of respiratory volume based on upper body movements by means of a smart shirt is increasingly requested in medical applications. This research used upper body surface motions obtained by a motion capture system, and two regression methods to determine the optimal selection and placement of sensors on a smart shirt to recover respiratory parameters from benchmark spirometry values. The results of the two regression methods (Ridge regression and the least absolute shrinkage and selection operator (Lasso)) were compared. This work shows that the Lasso method offers advantages compared to the Ridge regression, as it provides sparse solutions and is more robust to outliers. However, both methods can be used in this application since they lead to a similar sensor subset with lower computational demand (from exponential effort for full exhaustive search down to the order of O (n2)). A smart shirt for respiratory volume estimation could replace spirometry in some cases and would allow for a more convenient measurement of respiratory parameters in home care or hospital settings.

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