Provides a framework to factorise electromyography (EMG) data.
    Tools are provided for raw data pre-processing, non negative matrix factorisation,
    classification of factorised data and plotting of obtained outcomes.
    In particular, reading from ASCII files is supported, along with wide-used
    filtering approaches to process EMG data. All steps include one or more sensible
    defaults that aim at simplifying the workflow. Yet, all functions are largely
    tunable at need. Example data sets are included.

An aid for learning and using music theory. You can build chords, scales, and chord progressions using 12-note equal temperament tuning (12-ET) or user-defined tuning. Includes functions to visualize notes on a piano using ASCII plots in the console and to plot waveforms using base graphics. It allows simple playback of notes and chords using the 'audio' package.

Analysis of musical scales (& modes, grooves, etc.) in the vein of
    Sherrill 2025 <doi:10.1215/00222909-11595194>.
    The initials MCT in the package title refer to the article's title: "Modal
    Color Theory." Offers support for conventional musical pitch class set
    theory as developed by Forte (1973, ISBN: 9780300016109) and David Lewin
    (1987, ISBN: 9780300034936), as well as for the continuous geometries of
    Callender, Quinn, & Tymoczko (2008) <doi:10.1126/science.1153021>.
    Identifies structural properties of scales and calculates derived values
    (sign vector, color number, brightness ratio, etc.). Creates plots such as
    "brightness graphs" which visualize these properties.

A collection of functions for converting and visualization the free induction decay of mono dimensional nuclear magnetic resonance (NMR) spectra into an audio file. It facilitates the conversion of Bruker datasets in files WAV. The sound of NMR signals could provide an alternative to the current representation of the individual metabolic fingerprint and supply equally significant information. The package includes also NMR spectra of the urine samples provided by four healthy donors. Based on Cacciatore S, Saccenti E, Piccioli M. Hypothesis: the sound of the individual metabolic phenotype? Acoustic detection of NMR experiments. OMICS. 2015;19(3):147-56. <doi:10.1089/omi.2014.0131>.