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Real-Time Sound and Motion Feedback for Violin Bow Technique Learning: A Controlled, Randomized Trial.

ABSTRACT: The production of good sound generation in the violin is a complex task that requires coordination and spatiotemporal control of bowing gestures. The use of motion-capture technologies to improve performance or reduce injury risks in the area of kinesiology is becoming widespread. The combination of motion accuracy and sound quality feedback has the potential of becoming an important aid in violin learning. In this study, we evaluate motion-capture and sound-quality analysis technologies developed inside the context of the TELMI, a technology-enhanced music learning project. We analyzed the sound and bow motion of 50 participants with no prior violin experience while learning to produce a stable sound in the violin. Participants were divided into two groups: the experimental group (N = 24) received real-time visual feedback both on kinematics and sound quality, while participants in the control group (N = 26) practiced without any type of external help. An additional third group of violin experts performed the same task for comparative purposes (N = 15). After the practice session, all groups were evaluated in a transfer phase without feedback. At the practice phase, the experimental group improved their bowing kinematics in comparison to the control group, but this was at the expense of impairing the sound quality of their performance. At the retention phase, the experimental group showed better results in sound quality, especially concerning control of sound dynamics. Besides, we found that the expert group improved the stability of their sound while using the technology. All in all, these results emphasize the importance of feedback technologies in learning complex tasks, such as musical instrument learning.

SUBMITTER: Blanco AD

PROVIDER: S-EPMC8107276 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Current music technologies can assist in the process of learning to play a musical instrument and provide objective measures for evaluating the improvement of music students in concrete music tasks. In this paper, we investigated the effects of a sound quality visual feedback system (SQVFS) in violin learning. In particular, we studied the EEG activity of a group of participants with no previous violin playing experience while they learned to produce a stable sound (regarding pitch, dynamics, and timbre) in order to find motor learning biomarkers in a music task. Eighteen subjects with no prior experience in violin playing were divided into two groups: participants in the first group (experimental group, N = 9) practiced with instructional videos and offline feedback from the SQVFS provided in alternation with their performance, while participants in a second group (control group, N = 9) practiced with the instructional videos only. A third group of violin experts (players with more than 6 years of experience) performed the same task for comparative purposes (N = 7). All participants were asked to perform 20 trials (4 blocks of 5 trials) consisting of a violin bowing exercise while their EEG activity and their produced sound was recorded. Significant sound quality improvements along the session were found in all participants with the exception of participants in the expert group. In addition, participants in the experimental group showed increased interest in the learning process and significant improvement after the second block not present in the control group. A significant correlation between the levels of frontal gamma band power and the sound improvement along the task was found in both the experimental and control group. This result is consistent with the temporal binding model which associates gamma band power with the role of integrating (binding) information processed in distributed cortical areas. Task complexity demands more cognitive resources, more binding and thus, gamma band power enhancement, which may be reduced as the demanded task begins to be automated as it is likely to be the case in both beginners groups.

Project description:BackgroundSurface-guided radiation therapy (SGRT) employs a non-invasive real-time optical surface imaging (OSI) technique for patient surface motion monitoring during radiotherapy. The main purpose of this study is to verify the real-time tracking accuracy of SGRT for respiratory motion and provide a fitting method to detect the time delay of gating.MethodsA respiratory motion phantom was utilized to simulate respiratory motion using 17 cosine breathing pattern curves with various periods and amplitudes. The motion tracking of the phantom was performed by the Catalyst™ system. The tracking accuracy of the system (with period and amplitude variations) was evaluated by analyzing the adjusted coefficient of determination (A_R2) and root mean square error (RMSE). Furthermore, 13 actual respiratory curves, which were categorized into regular and irregular patterns, were selected and then simulated by the phantom. The Fourier transform was applied to the respiratory curves, and tracking accuracy was compared through the quantitative analyses of curve similarity using the Pearson correlation coefficient (PCC). In addition, the time delay of amplitude-based respiratory-gating radiotherapy based on the OSI system with various beam hold times was tested using film dosimetry for the Elekta Versa-HD and Varian Edge linacs. A dose convolution-fitting method was provided to accurately measure the beam-on and beam-off time delays.ResultsA_R2 and RMSE for the cosine curves were 0.9990-0.9996 and 0.110-0.241 mm for periods ranging from 1 s to 10 s and 0.9990-0.9994 and 0.059-0.175 mm for amplitudes ranging from 3 mm to 15 mm. The PCC for the actual respiratory curves ranged from 0.9955 to 0.9994, which was not significantly affected by breathing patterns. For gating radiotherapy, the average beam-on and beam-off time delays were 1664 ± 72 and 25 ± 30 ms for Versa-HD and 303 ± 45 and 34 ± 25 ms for Edge, respectively. The time delay was relatively stable as the beam hold time increased.ConclusionsThe OSI technique provides high accuracy for respiratory motion tracking. The proposed dose convolution-fitting method can accurately measure the time delay of respiratory-gating radiotherapy. When the OSI technique is used for respiratory-gating radiotherapy, the time delay for the beam-on is considerably longer than the beam-off.

Dataset Information

Real-Time Sound and Motion Feedback for Violin Bow Technique Learning: A Controlled, Randomized Trial.

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