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Blog | shaunpurcell

Tools for the analysis of sleep data

The NSRR is revamping its Tools pages and needs your help! Have you developed a tool for the analysis of sleep data that you'd like others to know about and use? Do you have some tricks and tips for using existing packages that you'd like to share? What about a write-up listing your favorite tools, explaining how you use them and what's good about them? Or perhaps you'd like to share some data analytic problems that aren't met by existing tools? If so, we'd love for you to submit a gues. Keep reading

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By shaunpurcell on September 13, 2019 Sep 13, 2019 in Tools

UMAP clustering of NSRR data

Visualizing data is almost always useful, but this can be difficult when you have a lot of complex data. This is where dimension reduction techniques can play an important role. As described here, we applied one such technique to sleep EEG spectra from over 16,000 individuals in the NSRR, to get a feel for some of the sources of individual differences (both physiological and artefactual) in these data. Keep reading

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By shaunpurcell on May 28, 2019 May 28, 2019 in Data Notes

Luna: software for the analysis of sleep signal data

Luna is a C/C++ library focused on the analysis of large numbers of sleep studies, such as those available from the NSRR. Luna is completely open-source and not dependent on proprietary software. If you're interested in analyzing sleep signals from the NSRR, you might want to start by looking at Luna. Currently, there is a command-line tool (lunaC) and an extension library for R (lunaR). Keep reading

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By shaunpurcell on May 28, 2019 May 28, 2019 in Tools

EEG polarity issues in the NSRR

Many analyses of sleep EEG data are effectively agnostic to the polarity of the EEG signal. That is, you could flip the signal (i.e. multiply every sample value by -1) and still obtain equivalent results, e.g. from most spectral analyses. For certain analyses that consider the phase of a signal, however, it will in fact matter that the polarity of the signal is correct. Keep reading

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By shaunpurcell on May 27, 2019 May 27, 2019 in Data Notes