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Novel Sensing Technology and Networks for Music Learning and Education
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Novel Sensing Technology and Networks for Music Learning and Education

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 25 November 2025 | Viewed by 8488

Special Issue Editors

Dr. Fabrizio Taffoni

E-Mail Website
Guest Editor
CREO Lab–Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy
Interests: robotics; mechatronics; human motion analysis; wearable sensors; movement ecological assessment
Prof. Dr. Domenico Formica

E-Mail Website
Guest Editor
Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21-00128 Rome, Italy
Interests: robotics; mechatronic; human motor control; neuroengineering; human-machine interaction
Special Issues, Collections and Topics in MDPI journals
Dr. Nicola Di Stefano

E-Mail Website
Guest Editor
Istituto di Scienze e tecnologie della Cognizione Umana - CNR, Via S. Martino della Battaglia 44, 00185 Rome, Italy
Interests: music perception and cognition; music and technology
Prof. Dr. Marc Leman

E-Mail Website
Guest Editor
Department of Arts, Music and Theatre Sciences, IPEM, Ghent University, 9000 Ghent, Belgium
Interests: systematic musicology, statistics, philosophy; empirical methods for studying embodied music interaction and performance

Special Issue Information

Dear Colleagues,

Learning how to play a musical instrument is a long process that requests several hours of training guided by experienced instructors. Several repetitions of simple exercises are required to learn how to interact with the instrument in a natural, fluid, and smooth way. Such a long process is necessary to bring the sensory motor control to a professional level.

Smart interfaces embedded into everyday objects or directly worn by the users are becoming increasingly relevant to augment, train, or simply assess sensorimotor functions in several application scenarios, even in music. While there are several examples of the application of smart interfaces and software to mimic a musical instrument and increase the possibilities of training, few devices are available for functional assessment of musicians to provide them with additional feedbacks on the quality of their gestures and on how they interact with the real instrument.

Nowadays, several technologies may be used to address this issue: the arsenal of available ammunitions ranges from smart instrumented objects to wearable networks of sensors. These sensing technologies make possible recording interactions with instruments as well as monitoring physiological and biomechanical signals on-field, with improved capability to quantify behaviors at a more fine-grained space-time scale.

This Special Issue of Sensors aims to collect current developments in the design, characterization, and validation of novel sensing technologies and networks for the assessment of instrumental music learning.

Original studies and review papers from human-centered technology, bioengineering, music education, systematic musicology, artificial intelligence and IoT, neuroscience, and other related fields will be considered.

Dr. Fabrizio Taffoni
Prof. Dr. Domenico Formica
Dr. Nicola Di Stefano
Prof. Dr. Marc Leman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human-centered technology
  • technology-enhanced music learning
  • music education
  • smart devices
  • wearables
  • functional assessment
  • tool use
  • body area networks
  • motor learning
  • motor control

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Published Papers (4 papers)

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Research

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23 pages, 8624 KiB  
Article
Method for Using Functional Near-Infrared Spectroscopy (fNIRS) to Explore Music-Induced Brain Activation in Orchestral Musicians in Concert
by Steffen Maude Fagerland, Andreas Løve, Tord K. Helliesen, Ørjan Grøttem Martinsen, Mona-Elisabeth Revheim and Tor Endestad
Sensors 2025, 25(6), 1807; https://doi.org/10.3390/s25061807 - 14 Mar 2025
Viewed by 610
Abstract
The act of performing music may induce a specific state of mind, musicians potentially becoming immersed and detached from the rest of the world. May this be measured? Does this state of mind change based on repetition? In collaboration with Stavanger Symphony Orchestra [...] Read more.
The act of performing music may induce a specific state of mind, musicians potentially becoming immersed and detached from the rest of the world. May this be measured? Does this state of mind change based on repetition? In collaboration with Stavanger Symphony Orchestra (SSO), we developed protocols to investigate ongoing changes in the brain activation of a first violinist and a second violinist in real time during seven sequential, public concerts using functional near-infrared spectroscopy (fNIRS). Using wireless fNIRS systems (Brite MKII) from Artinis, we measured ongoing hemodynamic changes and projected the brain activation to the audience through the software OxySoft 3.5.15.2. We subsequently developed protocols for further analyses through the Matlab toolboxes Brainstorm and Homer2/Homer3. Our developed protocols demonstrate how one may use “functional dissection” to imply how the state of mind of musicians may alter while performing their art. We focused on a subset of cortical regions in the right hemisphere, but the current study demonstrates how fNIRS may be used to shed light on brain dynamics related to producing art in ecological and natural contexts on a general level, neither restricted to the use of musical instrument nor art form. Full article
(This article belongs to the Special Issue Novel Sensing Technology and Networks for Music Learning and Education)
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14 pages, 3852 KiB  
Article
Real-Time Visual Feedback Based on MIMUs Technology Reduces Bowing Errors in Beginner Violin Students
by Cecilia Provenzale, Francesco Di Tommaso, Nicola Di Stefano, Domenico Formica and Fabrizio Taffoni
Sensors 2024, 24(12), 3961; https://doi.org/10.3390/s24123961 - 19 Jun 2024
Cited by 3 | Viewed by 1186
Abstract
Violin is one of the most complex musical instruments to learn. The learning process requires constant training and many hours of exercise and is primarily based on a student–teacher interaction where the latter guides the beginner through verbal instructions, visual demonstrations, and physical [...] Read more.
Violin is one of the most complex musical instruments to learn. The learning process requires constant training and many hours of exercise and is primarily based on a student–teacher interaction where the latter guides the beginner through verbal instructions, visual demonstrations, and physical guidance. The teacher’s instruction and practice allow the student to learn gradually how to perform the correct gesture autonomously. Unfortunately, these traditional teaching methods require the constant supervision of a teacher and the interpretation of non-real-time feedback provided after the performance. To address these limitations, this work presents a novel interface (Visual Interface for Bowing Evaluation—VIBE) to facilitate student’s progression throughout the learning process, even in the absence of direct teacher intervention. The proposed interface allows two key parameters of bowing movements to be monitored, namely, the angle between the bow and the string (i.e., α angle) and the bow tilt (i.e., β angle), providing real-time visual feedback on how to correctly move the bow. Results collected on 24 beginners (12 exposed to visual feedback, 12 in a control group) showed a positive effect of the real-time visual feedback on the improvement of bow control. Moreover, the subjects exposed to visual feedback judged the latter as useful to correct their movement and clear in terms of the presentation of data. Although the task was rated as harder when performed with the additional feedback, the subjects did not perceive the presence of a violin teacher as essential to interpret the feedback. Full article
(This article belongs to the Special Issue Novel Sensing Technology and Networks for Music Learning and Education)
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12 pages, 1891 KiB  
Article
Mobile Devices and Sensors for an Educational Multimedia Opera Project
by Roger B. Dannenberg, Jorge Sastre, Stefano Scarani, Nuria Lloret and Elizabeth Carrascosa
Sensors 2023, 23(9), 4378; https://doi.org/10.3390/s23094378 - 28 Apr 2023
Cited by 2 | Viewed by 2757
Abstract
Interactive computer-based music systems form a rich area for the exploration of collaborative systems where sensors play an active role and are important to the design process. The Soundcool system is a collaborative and educational system for sound and music creation as well [...] Read more.
Interactive computer-based music systems form a rich area for the exploration of collaborative systems where sensors play an active role and are important to the design process. The Soundcool system is a collaborative and educational system for sound and music creation as well as multimedia scenographic projects, allowing students to produce and modify sounds and images with sensors, smartphones and tablets in real time. As a real-time collaborative performance system, each performance is a unique creation. In a comprehensive educational project, Soundcool is used to extend the sounds of traditional orchestral instruments and opera singers with electronics. A multidisciplinary international team participates, resulting in different performances of the collaborative multimedia opera The Mother of Fishes in countries such as Spain, Romania, Mexico and the USA. Full article
(This article belongs to the Special Issue Novel Sensing Technology and Networks for Music Learning and Education)
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Other

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19 pages, 3460 KiB  
Systematic Review
Using Wearable Sensors to Study Musical Experience: A Systematic Review
by Erica Volta and Nicola Di Stefano
Sensors 2024, 24(17), 5783; https://doi.org/10.3390/s24175783 - 5 Sep 2024
Cited by 2 | Viewed by 2536
Abstract
Over the last few decades, a growing number of studies have used wearable technologies, such as inertial and pressure sensors, to investigate various domains of music experience, from performance to education. In this paper, we systematically review this body of literature using the [...] Read more.
Over the last few decades, a growing number of studies have used wearable technologies, such as inertial and pressure sensors, to investigate various domains of music experience, from performance to education. In this paper, we systematically review this body of literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. The initial search yielded a total of 359 records. After removing duplicates and screening for content, 23 records were deemed fully eligible for further analysis. Studies were grouped into four categories based on their main objective, namely performance-oriented systems, measuring physiological parameters, gesture recognition, and sensory mapping. The reviewed literature demonstrated the various ways in which wearable systems impact musical contexts, from the design of multi-sensory instruments to systems monitoring key learning parameters. Limitations also emerged, mostly related to the technology’s comfort and usability, and directions for future research in wearables and music are outlined. Full article
(This article belongs to the Special Issue Novel Sensing Technology and Networks for Music Learning and Education)
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