Heart rate monitoring using wrist-type using photoplethysmographic (PPG) signals during subjects' intensive exercises is a challenging problem, since signals are strongly affected by motion artifacts caused by unexpected movements. This paper presents a method that uses both time and frequency characteristics of signals; using sparse signal reconstruction for high-resolution spectrum estimation. Experimental results on type data sets recorded from 12 subjects during fast running at peak speed of 15 km/hour. The results have a performance with the average absolute error being 1.80 beat per minute.
Motivation
The molecular mechanisms of self-organization that orchestrate embryonic cells to create astonishing patterns have been among major questions of developmental biology. It is recently shown that embryonic stem cells (ESCs), when cultured in particular micropatterns, can self-organize and mimic the early steps of pre-implantation embryogenesis. A systems-biology model to address this observation from a dynamical systems perspective is essential and can enhance understanding of the phenomenon.
Results
Here, we propose a multicellular mathematical model for pattern formation during in vitro gastrulation of human ESCs. This model enhances the basic principles of Waddington epigenetic landscape with cell–cell communication, in order to enable pattern and tissue formation. We have shown the sufficiency of a simple mechanism by using a minimal number of parameters in the model, in order to address a variety of experimental observations such as the formation of three germ layers and trophectoderm, responses to altered culture conditions and micropattern diameters and unexpected spotted forms of the germ layers under certain conditions. Moreover, we have tested different boundary conditions as well as various shapes, observing that the pattern is initiated from the boundary and gradually spreads towards the center. This model provides a basis for in-silico modeling of self-organization.
Availability and implementation
https://github.com/HFooladi/Self_Organization.
Supplementary information
Supplementary data are available at Bioinformatics online.
The molecular mechanisms of self-organization that orchestrate embryonic cells to create astonishing patterns have been among major questions of developmental biology. It is recently shown that embryonic stem cells (ESCs), when cultured on particular micropatterns, can self-organize and mimic early steps of pre-implantation embryogenesis. A systems-biology model to address this observation from a dynamical systems perspective is essential. Here, we propose a multicellular mathematical model for pattern formation during in vitro gastrulation of human ESCs. This model enhances the basic principles of Waddington epigenetic landscape with cell-cell communication, in order to enable pattern and tissue formation. To prevent overfitting of the model, there is a minimal number of parameters in the model, which are sufficient to address different experimental observations such as the formation of three germ layers and trophectoderm, responses to altered culture conditions and micropattern diameters, and unexpected spotted forms of the germ layers under certain conditions. This model provides a basis for in-silico modeling of self-organization.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.