Mastering fine motor tasks, such as playing the guitar, takes years of time-consuming practice. Commonly, expensive guidance by experts is essential for adjusting the training program to the student's proficiency. In our work, we showcase the suitability of Electromyography to detect fine-grained hand and finger postures in an exemplary guitar tutor scenario. We present EMGuitar, an interactive guitar tutoring system, that assists students by reporting on play correctness and adjusts playback tempi automatically. We report person-dependent classification utilizing a ring of electrodes around the forearm with an F1 score of up to 0.89 on recorded calibration data. Furthermore, our system was received well by neither diminishing ease of use nor being disruptive for the participants. Based on the received comments, we identified the need for detailed play accuracy feedback down to individual chords, for which we suggest an adapted visualization and an algorithmic approach.
%0 Conference Paper
%1 conf/ACMdis/KarolusSKW018
%A Karolus, Jakob
%A Schuff, Hendrik
%A Kosch, Thomas
%A Wozniak, Pawel W.
%A Schmidt, Albrecht
%B Proceedings of the Designing Interactive Systems Conference (DIS)
%D 2018
%E Koskinen, Ilpo
%E Lim, Youn-Kyung
%E Pargman, Teresa Cerratto
%E Chow, Kenny K. N.
%E Odom, William
%I ACM
%K 2018 C02 from:leonkokkoliadis sfbtrr161
%P 651-655
%R 10.1145/3196709.3196803
%T EMGuitar: Assisting Guitar Playing with Electromyography
%U https://doi.org/10.1145/3196709.3196803
%X Mastering fine motor tasks, such as playing the guitar, takes years of time-consuming practice. Commonly, expensive guidance by experts is essential for adjusting the training program to the student's proficiency. In our work, we showcase the suitability of Electromyography to detect fine-grained hand and finger postures in an exemplary guitar tutor scenario. We present EMGuitar, an interactive guitar tutoring system, that assists students by reporting on play correctness and adjusts playback tempi automatically. We report person-dependent classification utilizing a ring of electrodes around the forearm with an F1 score of up to 0.89 on recorded calibration data. Furthermore, our system was received well by neither diminishing ease of use nor being disruptive for the participants. Based on the received comments, we identified the need for detailed play accuracy feedback down to individual chords, for which we suggest an adapted visualization and an algorithmic approach.
@inproceedings{conf/ACMdis/KarolusSKW018,
abstract = {Mastering fine motor tasks, such as playing the guitar, takes years of time-consuming practice. Commonly, expensive guidance by experts is essential for adjusting the training program to the student's proficiency. In our work, we showcase the suitability of Electromyography to detect fine-grained hand and finger postures in an exemplary guitar tutor scenario. We present EMGuitar, an interactive guitar tutoring system, that assists students by reporting on play correctness and adjusts playback tempi automatically. We report person-dependent classification utilizing a ring of electrodes around the forearm with an F1 score of up to 0.89 on recorded calibration data. Furthermore, our system was received well by neither diminishing ease of use nor being disruptive for the participants. Based on the received comments, we identified the need for detailed play accuracy feedback down to individual chords, for which we suggest an adapted visualization and an algorithmic approach.},
added-at = {2020-03-11T13:36:48.000+0100},
author = {Karolus, Jakob and Schuff, Hendrik and Kosch, Thomas and Wozniak, Pawel W. and Schmidt, Albrecht},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2b0d5b793a5b9bef284ed268f959ebe2d/sfbtrr161},
booktitle = {Proceedings of the Designing Interactive Systems Conference (DIS)},
crossref = {conf/ACMdis/2018},
doi = {10.1145/3196709.3196803},
editor = {Koskinen, Ilpo and Lim, Youn-Kyung and Pargman, Teresa Cerratto and Chow, Kenny K. N. and Odom, William},
ee = {https://doi.org/10.1145/3196709.3196803},
interhash = {5723ad6c7aed1ac04df4e60a739e83bd},
intrahash = {b0d5b793a5b9bef284ed268f959ebe2d},
keywords = {2018 C02 from:leonkokkoliadis sfbtrr161},
pages = {651-655},
publisher = {ACM},
timestamp = {2020-03-11T12:39:18.000+0100},
title = {EMGuitar: Assisting Guitar Playing with Electromyography},
url = {https://doi.org/10.1145/3196709.3196803},
year = 2018
}
