Literature DB >> 23943580

Combining EEG, MIDI, and motion capture techniques for investigating musical performance.

Clemens Maidhof1, Torsten Kästner, Tommi Makkonen.   

Abstract

This article describes a setup for the simultaneous recording of electrophysiological data (EEG), musical data (MIDI), and three-dimensional movement data. Previously, each of these three different kinds of measurements, conducted sequentially, has been proven to provide important information about different aspects of music performance as an example of a demanding multisensory motor skill. With the method described here, it is possible to record brain-related activity and movement data simultaneously, with accurate timing resolution and at relatively low costs. EEG and MIDI data were synchronized with a modified version of the FTAP software, sending synchronization signals to the EEG recording device simultaneously with keypress events. Similarly, a motion capture system sent synchronization signals simultaneously with each recorded frame. The setup can be used for studies investigating cognitive and motor processes during music performance and music-like tasks--for example, in the domains of motor control, learning, music therapy, or musical emotions. Thus, this setup offers a promising possibility of a more behaviorally driven analysis of brain activity.

Mesh:

Year:  2014        PMID: 23943580     DOI: 10.3758/s13428-013-0363-9

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  6 in total

1.  Methodological aspects of EEG and body dynamics measurements during motion.

Authors:  Pedro M R Reis; Felix Hebenstreit; Florian Gabsteiger; Vinzenz von Tscharner; Matthias Lochmann
Journal:  Front Hum Neurosci       Date:  2014-03-24       Impact factor: 3.169

2.  The Schultz MIDI Benchmarking Toolbox for MIDI interfaces, percussion pads, and sound cards.

Authors:  Benjamin G Schultz
Journal:  Behav Res Methods       Date:  2019-02

3.  "Telling me not to worry…" Hyperscanning and Neural Dynamics of Emotion Processing During Guided Imagery and Music.

Authors:  Jörg C Fachner; Clemens Maidhof; Denise Grocke; Inge Nygaard Pedersen; Gro Trondalen; Gerhard Tucek; Lars O Bonde
Journal:  Front Psychol       Date:  2019-07-25

4.  Predictive error detection in pianists: a combined ERP and motion capture study.

Authors:  Clemens Maidhof; Anni Pitkäniemi; Mari Tervaniemi
Journal:  Front Hum Neurosci       Date:  2013-09-26       Impact factor: 3.169

5.  Error monitoring in musicians.

Authors:  Clemens Maidhof
Journal:  Front Hum Neurosci       Date:  2013-07-26       Impact factor: 3.169

Review 6.  Categorisation of Mobile EEG: A Researcher's Perspective.

Authors:  Anthony D Bateson; Heidi A Baseler; Kevin S Paulson; Fayyaz Ahmed; Aziz U R Asghar
Journal:  Biomed Res Int       Date:  2017-12-04       Impact factor: 3.411

  6 in total

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