A Minimal Set of Sensors in a Smart-Shirt to Obtain Respiratory Parameters

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

doi:10.1016/j.ifacol.2020.12.627

Cited by 6 publications

(6 citation statements)

References 21 publications

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“…It should be noted that some of the parameters of the markers carrying system information were highly correlated with each other. In particular, especially the markers at the thorax generally moved in unison and thus, simply selecting the markers with the highest individual correlations may lack information uniqueness and may not represent the highest information content with respect to respiratory volumes possible [ 38 ]. Therefore, further increasing the number of sensors could have a very minor effect on the information content of the overall measurement system.…”

Section: Discussionmentioning

confidence: 99%

“…Movements in the direction of the principal component of the marker movement of each marker were obtained. In a previous work (Laufer et al [ 38 ]), it was evident that each marker moved predominantly along a particular line. Therefore, for each marker, this line (the main component of the marker motion) was identified using a singular value decomposition SVD.…”

Section: Methodsmentioning

confidence: 97%

“…The projection was done by using the dot function of MATLAB, which delivered the length of the projected vector L i , which was then used for further analysis. Details on the calculation of L can be obtained from Laufer et al [ 38 ].…”

Section: Methodsmentioning

confidence: 99%

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Characterisation and Quantification of Upper Body Surface Motions for Tidal Volume Determination in Lung-Healthy Individuals

Laufer

Höflinger

Docherty

et al. 2023

Sensors

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Measurement of accurate tidal volumes based on respiration-induced surface movements of the upper body would be valuable in clinical and sports monitoring applications, but most current methods lack the precision, ease of use, or cost effectiveness required for wide-scale uptake. In this paper, the theoretical ability of different sensors, such as inertial measurement units, strain gauges, or circumference measurement devices to determine tidal volumes were investigated, scrutinised and evaluated. Sixteen subjects performed different breathing patterns of different tidal volumes, while using a motion capture system to record surface motions and a spirometer as a reference to obtain tidal volumes. Subsequently, the motion-capture data were used to determine upper-body circumferences, tilt angles, distance changes, movements and accelerations—such data could potentially be measured using optical encoders, inertial measurement units, or strain gauges. From these parameters, the measurement range and correlation with the volume signal of the spirometer were determined. The highest correlations were found between the spirometer volume and upper body circumferences; surface deflection was also well correlated, while accelerations carried minor respiratory information. The ranges of thorax motion parameters measurable with common sensors and the values and correlations to respiratory volume are presented. This article thus provides a novel tool for sensor selection for a smart shirt analysis of respiration.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 97%

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Characterisation and Quantification of Upper Body Surface Motions for Tidal Volume Determination in Lung-Healthy Individuals

Laufer

Höflinger

Docherty

et al. 2023

Sensors

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“…Motions of the MoCap markers were dimensionally reduced to their major axis using the methods of Laufer et al [42], as they move predominantly on a specific line (Figure 5). By projecting the marker movements onto their major axis of movement, the dimension of the MoCap data was reduced by a factor of three.…”

Section: Data Processingmentioning

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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“…Thus, validation of respiratory models of healthy or partially assisted (non-invasive MV) poses particular difficulty, as these measurements are not ethically or clinically feasible for conscious subjects. However, motion capture, inductance plethysmography, and strain gauge belts/ garments have been used to non-invasively measure changes in thoracic and abdominal volumes, but they require careful calibration, specific location conditions such as unobstructed view, and/or purchase of specialty equipment [6] , [7] , [8] , [9] . In this study, a basic tape measure is modified using a rotary encoder and spring to output dynamic change in unspooled length, which generates similar data to commercial analogs, at a much lower cost and higher degree of customization.…”

Section: Hardware In Contextmentioning

confidence: 99%

Respiratory bi-directional pressure and flow data collection device with thoracic and abdominal circumferential monitoring

2022

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A Minimal Set of Sensors in a Smart-Shirt to Obtain Respiratory Parameters

Cited by 6 publications

References 21 publications

Characterisation and Quantification of Upper Body Surface Motions for Tidal Volume Determination in Lung-Healthy Individuals

Characterisation and Quantification of Upper Body Surface Motions for Tidal Volume Determination in Lung-Healthy Individuals

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

Respiratory bi-directional pressure and flow data collection device with thoracic and abdominal circumferential monitoring

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