Albert, J. A., Herdick, A., Brahms, C. M., Granacher, U., & Arnrich, B. [ca. 2023]. PERSIST: a multimodal dataset for the prediction of perceived exertion during resistance training [Cd]. Freiburg: Universität. https://doi.org/10.3390/data8010009
ISO-690 (author-date, English)ALBERT, Justin Amadeus, HERDICK, Arne, BRAHMS, Clemens Markus, GRANACHER, Urs und ARNRICH, Bert, 2023. PERSIST: a multimodal dataset for the prediction of perceived exertion during resistance training. Freiburg: Universität.
Modern Language Association 9th editionAlbert, J. A., A. Herdick, C. M. Brahms, U. Granacher, und B. Arnrich. PERSIST: a multimodal dataset for the prediction of perceived exertion during resistance training. cd, Universität, 2023, https://doi.org/10.3390/data8010009.
Mohr Siebeck - Recht (Deutsch - Österreich)Albert, Justin Amadeus/Herdick, Arne/Brahms, Clemens Markus/Granacher, Urs/Arnrich, Bert: PERSIST: a multimodal dataset for the prediction of perceived exertion during resistance training, Freiburg 2023.
Emerald - HarvardAlbert, J.A., Herdick, A., Brahms, C.M., Granacher, U. und Arnrich, B. (2023), PERSIST: a multimodal dataset for the prediction of perceived exertion during resistance training, Bd. , Universität, Freiburg, verfügbar unter:https://doi.org/10.3390/data8010009.