Healthy Strings: Posture, Movement and Sound in Violin Performance
🎻 Violin Posture, Sound, Performance & Technology
Healthy Strings is an international research collaboration investigating posture, movement, playing technique, sound and physical strain in violin performance. Specialists in music physiology, violin pedagogy, physiotherapy, musical acoustics, movement analysis, sensor technology, biorobotics and data science are developing shared methods for recording and analysing violin performance.
The project does not assume that there is one “correct” violin posture. Instead, it investigates which instrument-specific asymmetries are functional and how potentially demanding movement patterns can be identified and assessed. Movement data are interpreted in relation to the musical task, the resulting sound and the individual performer.
Research Aims
- Develop a standardised protocol for video and audio recordings of violinists that can be used across research sites.
- Improve video-based assessments of posture and movement by physiotherapists and performing arts health specialists.
- Bring together markerless movement analysis, expert assessments and acoustic features.
- Review existing tools, datasets and research approaches, build on suitable methods and develop shared analytical tools where needed.
- Establish a basis for future studies on playing technique, physical strain, prevention and pedagogical feedback.
Key Research Questions
- Which small set of variables can describe posture and movement in violin performance reliably while remaining relevant to practice?
- How can functional asymmetries be distinguished from movement patterns that might be associated with increased physical strain?
- Which playing tasks and camera perspectives produce recordings that are suitable for expert assessment and stable technical analysis?
- How reliable are video-based measurements and assessments across different professional groups?
- How do movement and playing technique relate to acoustic features such as intonation, dynamics and timbre?
Methods and Technical Approach
The planned recordings combine video and audio with a brief assessment protocol. Standardised playing tasks will make different aspects of violin performance visible and allow comparisons across performers and research sites. Potential tasks include basic playing posture, bowing movements, scales and selected technical exercises. The recording protocol is currently being developed.
The project examines markerless methods that estimate body movement from standard video recordings. One starting point is the SInES Tools developed at the University of Vienna, including video-based pose tracking and interactive visualisation of movement data. Other models and tools will also be assessed. Where appropriate, sensor data, motion capture or electromyography (EMG) may provide additional points of comparison.
In parallel, the group is developing a structured approach to video assessment. Physiotherapists, performing arts health specialists and violin pedagogues should be able to record observations from their respective professional perspectives. The work also examines which features can be assessed reliably from video.
A further task is the systematic review of existing tools, datasets and research approaches, including SPD, PyEyesWeb and TELMI. The group will identify methods and data structures that can support Healthy Strings and determine where new tools need to be developed jointly.
Current Project Status
From 28 August to 2 September 2026, members of the international research collaboration met for a retreat in Lucca and Pisa. They discussed recording tasks, physiotherapy and violin pedagogy assessments, audiovisual analysis, technical tools and possible joint research projects.
Current work focuses on three areas: developing the recording protocol, improving video assessments by physiotherapists and performing arts health specialists, and systematically reviewing existing analytical tools and datasets. This work will also define the requirements for new shared tools.
Initial qualitative method comparisons are encouraging for larger movements of the torso and arms. Smaller rotations, particularly of the forearm and wrist, require further validation. These early observations do not yet support conclusions about an individual performer’s health risks.
Collaboration and Next Steps
Through 2027, the group plans to develop the shared study design and research collaboration further. Planned work includes aligning recording and assessment procedures, conducting pilot studies at participating sites, planning data analysis, and preparing joint research projects and funding applications.
In the longer term, recordings and assessments may take place at several international sites. This will require comparable protocols, appropriate consent and data protection procedures, and agreed arrangements for data storage and transfer.
Potential Applications
- Research on movement, sound and physical strain in violin performance.
- Methodologically grounded video assessment in music physiology, violin pedagogy and physiotherapy.
- Development of clear, individualised feedback methods.
- Open and transparent analytical workflows for research and teaching.
Scientific Coordination
- Ao. Univ.-Prof. Mag. Dr. Matthias Bertsch, Motion-Emotion-Lab, Department of Music Physiology, mdw – University of Music and Performing Arts Vienna 🇦🇹. bertsch@mdw.ac.at
- Univ.-Prof. Dr. Christoph Reuter, SInES Lab, Department of Musicology, University of Vienna 🇦🇹.
Contributors and Research Collaboration
The collaboration includes people with different roles and levels of involvement. Contributors to the project’s development and international exchange to date include:
- Bronwen Ackermann 🇦🇺 – performing arts health and physiotherapy; University of Sydney.
- Alberto Bologni 🇮🇹 – violin pedagogy and institutional collaboration; Conservatorio di Musica Luigi Boccherini, Lucca.
- Antonio Camurri 🇮🇹 – expressive movement and multimodal interaction; University of Genoa / Casa Paganini.
- Alberto Carratello 🇮🇹 – violin performance and pedagogy; Conservatorio di Musica Luigi Boccherini, Lucca.
- Giorgio Stefano Gnecco 🇮🇹 – machine learning and data science; Scuola IMT Alti Studi Lucca.
- Elisabeth Grain 🇩🇪 – physiotherapy and movement analysis; Osnabrück University of Applied Sciences.
- Tobias Großhauser 🇦🇹 – sensor technology and interaction design.
- Felix Kloos 🇦🇹 – audiovisual analysis, SInES Tools and data processing; University of Vienna.
- Alessio Nacuzi 🇮🇹 – violin pedagogy, biorobotics and movement analysis; Scuola Superiore Sant’Anna, Pisa / Conservatorio di Musica Luigi Boccherini, Lucca.
- Tina Margareta Nilssen 🇳🇴🇦🇹 – violin performance, music physiology and expert assessment; mdw.
- Calogero Maria Oddo 🇮🇹 – biorobotics and sensor technology; Scuola Superiore Sant’Anna, Pisa.
- Veronica Santoro 🇮🇹 – biorobotics and data analysis; Scuola Superiore Sant’Anna, Pisa.
- Alexandra Türk-Espitalier 🇦🇹 – violin pedagogy and posture assessment; mdw.
- Gualtiero Volpe 🇮🇹 – movement analysis and multimodal interaction; University of Genoa.
- Christoff Zalpour 🇩🇪 – physiotherapy, prevention and functional movement analysis; Osnabrück University of Applied Sciences.
Participating Institutions and Research Groups
- Motion-Emotion-Lab and Department of Music Physiology, mdw – University of Music and Performing Arts Vienna 🇦🇹.
- SInES Lab, Department of Musicology, University of Vienna 🇦🇹.
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa 🇮🇹.
- Conservatorio di Musica Luigi Boccherini, Lucca 🇮🇹.
- Scuola IMT Alti Studi Lucca 🇮🇹.
- INAP/O, Osnabrück University of Applied Sciences 🇩🇪.
- University of Genoa / Casa Paganini 🇮🇹.
- University of Sydney 🇦🇺.
The 2026 international retreat was supported by the Austrian Society for Music and Medicine (ÖGfMM) 🇦🇹.
Conference Poster
Bertsch, M., Reuter, C., Türk-Espitalier, A., Nilssen, T. M., Großhauser, T., Nacuzi, A., Carratello, A., Grain, E., Brüggemann, J., & Leitz, T. (2026). Healthy Strings: AI-Powered Posture Tracking for Violinists: Markerless 3D Motion Analysis in Violin Performance – Validation, Multimodal Synchronisation, and Physiologically Informed Posture Assessment [Conference poster]. Beyond the Score – Health & Well-Being in Music and Performing Arts, Salzburg. https://doi.org/10.13140/RG.2.2.36013.04324
Contact
Ao. Univ.-Prof. Mag. Dr. Matthias Bertsch
Motion-Emotion-Lab, Department of Music Physiology
mdw – University of Music and Performing Arts Vienna 🇦🇹
bertsch@mdw.ac.at
Example of a multimodal SInES app currently under development: The 3D Data Analyzer displays movement data as an interactive stick figure and as graphs. It can import data from OpenCap, OpenSim and Sim2Pose. Its analysis functions draw on the RITMO VideoAnalyser, the MATLAB Motion Toolbox, Bigand PCA and PyEyesWeb (Camurri et al., 2016). Movement measures for the whole body or individual body parts can be exported as a CSV file. See https://sinestools.univie.ac.at/QTMparser.htm