Enhancing the Learning Process of Folk Dances using Augmented Reality and Non-Invasive Brain Stimulation
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Enhancing the Learning Process of Folk Dances using Augmented Reality and Non-Invasive Brain Stimulation
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Enhancing the Learning Process of Folk Dances using Augmented Reality and Non-Invasive Brain Stimulation
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/GA19-02033S" target="_blank" >GA19-02033S: Vyhledávání, analytika a anotace datových toků lidských pohybů</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Entertainment Computing
ISSN
1875-9521
e-ISSN
—
Svazek periodika
40
Číslo periodika v rámci svazku
January 2022
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
10
Strana od-do
1-10
Kód UT WoS článku
000701780400002
EID výsledku v databázi Scopus
2-s2.0-85114099495