Enhancing the Learning Process of Folk Dances using Augmented Reality and Non-Invasive Brain Stimulation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00119129" target="_blank" >RIV/00216224:14330/22:00119129 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1875952121000525" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1875952121000525</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.entcom.2021.100455" target="_blank" >10.1016/j.entcom.2021.100455</a>

Result language
angličtina
Original language name
Enhancing the Learning Process of Folk Dances using Augmented Reality and Non-Invasive Brain Stimulation
Original language description
Dancing is a very popular entertainment activity which is, however, quite difficult to learn. Our objective is to facilitate the traditional dance-learning process -- based on imitating teacher's movements -- by employing current technological advances. In particular, we record professional dancers' performances using a motion capture system and display the recorded data as moving avatars within a developed mobile-phone application. This application in combination with the mobile phone used as a headset, allows students to observe professional dancing within an augmented-reality environment. To demonstrate the benefits of such environment, we show that students can learn dancing when using the developed application. We assess the dancing quality by determining a similarity with respect to professional performance, based on the Dynamic Time Warping applied to the recorded motion capture data. Also, we analyze the effect of transcranial direct current stimulation (tDCS) on motor learning. We experimentally demonstrate that students with received tDCS perform dancing significantly better. We evaluate all the experiments on a real-life dataset of folk dances.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GA19-02033S" target="_blank" >GA19-02033S: Searching, Mining, and Annotating Human Motion Streams</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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