Quantifying cardiorespiratory thorax movement with motion capture and deconvolution
Keywords:
cardiorespiratory movement, motion capture, deconvolution, biosignal processing, unobtrusive sensingAbstract
Unobtrusive sensing is a growing aspect in the field of biomedical engineering. While many modalities exist, a large fraction of methods ultimately relies on the analysis of thoracic movement. To quantify cardiorespiratory induced thorax movement with spatial resolution, an approach using high-performance motion capture, electrocardiography and deconvolution is presented. In three healthy adults, motion amplitudes are estimated that correspond to values reported in the literature. Moreover, two-dimensional mappings are created that exhibit physiological meaningful relationships. Finally, the analysis of waveform data obtained via deconvolution shows plausible pulse transit behavior.
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Copyright (c) 2018 Christoph Hoog Antink, David Hejj, Bernhard Penzlin, Steffen Leonhardt, Marian Walter
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