For scientists

Posture, movement and sound in violin performance

Healthy Strings is an international, interdisciplinary research collaboration that started in 2026. It does not assume one correct violin posture: it investigates which instrument-specific asymmetries are functional and how potentially demanding posture and movement patterns can be identified and assessed – always 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, performing arts health specialists and violin pedagogues.
Bring together markerless movement analysis, expert assessments and acoustic features.
Integrate, where appropriate, sensor data, motion capture and electromyography (EMG).
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?
How can video-based movement analysis be combined with motion capture, EMG and instrument-based sensor data?

Methods and technical approach

Recordings combine video and audio with a brief standardised performance and assessment protocol. The playing tasks are designed to make different aspects of posture, movement and playing technique visible and comparable across performers and sites (recording protocol).

Body movement is estimated markerlessly from standard video. A central starting point is the browser-based SInES Tools platform of the University of Vienna: machine-learning pose tracking such as BlazePose provides 2D and 3D body landmarks, which can be inspected as stick figures and 3D representations and combined with acoustic features. Where appropriate, sensor data, professional motion capture and EMG provide reference information, so that markerless video analysis can be compared with laboratory systems.

In parallel, the group is developing a structured video assessment in which physiotherapists, performing arts health specialists and violin pedagogues record observations from their professional perspectives. A key methodological question is which features can be assessed reliably from short recordings and how expert assessments relate to quantitative movement parameters. Existing tools, datasets and approaches – for example the String Performance Dataset, PyEyesWeb and the TELMI project – are reviewed systematically.

Describe, not diagnose. Our tools describe posture, movement and sound. Early observations do not support conclusions about an individual performer’s health risks; every step from visualisation to validated statements is checked separately.

Current status

From 28 August to 2 September 2026, members of the collaboration met for a research retreat in Lucca and Pisa to work on recording tasks, camera perspectives, physiotherapy and violin-pedagogy assessments, audiovisual analysis, markerless tracking, sensor technologies, existing datasets and possible joint projects. Current work focuses on three areas: developing and validating the recording protocol, refining expert assessments of posture and movement, and building a multimodal analysis workflow that links video, SInES Tools, motion capture, EMG, sensors and sound. First qualitative method comparisons are encouraging for larger movements of the trunk and arms; smaller rotations, particularly of the forearm and wrist, need further validation.

Collaboration and next steps

Through 2027 the group plans to align recording and assessment procedures, run pilot studies at participating sites, analyse existing datasets, develop sensor-based subprojects and prepare joint research applications. Recordings at several international sites require comparable protocols, ethics procedures and informed consent, agreed data-protection standards and secure arrangements for data storage and transfer.

Potential applications

Low-threshold movement analysis with standard cameras or smartphones
Research on movement, sound and physical strain in violin performance
Methodologically grounded video assessment in music physiology, violin pedagogy and physiotherapy

Integration of video, motion capture, EMG, sensor and acoustic data
Clear, individualised feedback for healthy and efficient practice
Open and transparent analysis workflows for research and teaching

Scientific coordination

Matthias Bertsch – Motion-Emotion-Lab, Centre for Music Physiology, mdw – University of Music and Performing Arts Vienna
Christoph Reuter – SInES Lab, Department of Musicology, University of Vienna

All nineteen team members and their focus →

Participating institutions

Institution	Location
Motion-Emotion-Lab, Centre for Music Physiology, mdw – University of Music and Performing Arts Vienna	Vienna, Austria
SInES – Space for Interdisciplinary Experiments on Sound, Department of Musicology, University of Vienna	Vienna, Austria
The BioRobotics Institute, Scuola Superiore Sant’Anna	Pisa, Italy
Conservatorio di Musica Luigi Boccherini	Lucca, Italy
Scuola IMT Alti Studi Lucca	Lucca, Italy
University of Genoa / Casa Paganini – InfoMus	Genoa, Italy
Osnabrück University of Applied Sciences, with INAP/O – Institute of Applied Physiotherapy and Osteopathy	Osnabrück, Germany
The University of Sydney	Sydney, Australia
Austrian Society for Music and Medicine (ÖGfMM), Working Group Science – host of this website	Vienna, Austria

The 2026 research retreat in Lucca and Pisa was supported by the Austrian Society for Music and Medicine (ÖGfMM).

Publication and presentation

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. In Proceedings of the Symposium Beyond the Score – Health & Well-Being in Music and Performing Arts. https://doi.org/10.13140/RG.2.2.36013.04324
Bertsch, M., Reuter, C., Türk-Espitalier, A., Nilssen, T. M., Großhauser, T., Nacuzi, A., Carratello, A., Grain, E., Brüggemann, J., & Leitz, T. (2026, April 10). Healthy Strings: AI-powered posture tracking for violinists [Poster presentation]. Symposium Beyond the Score – Health & Well-Being in Music and Performing Arts, Salzburg, Austria.

Recent work by team members

Rousseau, C., Zalpour, C., Ackermann, B., & Rennie-Salonen, B. (2026). Instrumental musicians’ playing posture: A scoping review of its conceptualisation and application across interdisciplinary research. Frontiers in Psychology, 17, Article 1831920. https://doi.org/10.3389/fpsyg.2026.1831920
Türk-Espitalier, A. (2026). Lessons from nature: Achieving postural balance inspired by biomechanics and natural (a)symmetry. A perspective article. Frontiers in Psychology, 17, Article 1736186. https://doi.org/10.3389/fpsyg.2026.1736186
Rousseau, C., Zalpour, C., Chi, J.-Y., & Ackermann, B. J. (2026). Immediate effect of exercises of scapular stabilization on shoulder and forearm muscle activation patterns while playing the violin (New exercises to strengthen musicians – Part II). Frontiers in Psychology, 17, Article 1825818. https://doi.org/10.3389/fpsyg.2026.1825818
Reuter, C., Czedik-Eysenberg, I., Cui, A.-X., Ambros, S., Klooss, F., Feller, G., Schachner, I., Roos, M., Lindenbauer, H., Li, H., & Bertsch, M. (2026). SInES Tools, helpers, visualizers as your scientific realizers. In Fortschritte der Akustik – DAGA 2026 (pp. 1002–1005). https://doi.org/10.71568/daga2026.094

Selected references

Chi, J.-Y., Halaki, M., & Ackermann, B. J. (2020). Ergonomics in violin and piano playing: A systematic review. Applied Ergonomics, 88, Article 103143. https://doi.org/10.1016/j.apergo.2020.103143
Kok, L. M., Huisstede, B. M. A., Voorn, V. M. A., Schoones, J. W., & Nelissen, R. G. H. H. (2016). The occurrence of musculoskeletal complaints among professional musicians: A systematic review. International Archives of Occupational and Environmental Health, 89(3), 373–396. https://doi.org/10.1007/s00420-015-1090-6
Rousseau, C., Taha, L., Barton, G., Garden, P., & Baltzopoulos, V. (2023). Assessing posture while playing in musicians – A systematic review. Applied Ergonomics, 106, Article 103883. https://doi.org/10.1016/j.apergo.2022.103883
Jin, Y., Qiu, Z., Shi, Y., Sun, S., Wang, C., Pan, D., Zhao, J., Liang, Z., Wang, Y., Li, X., Yu, F., Yu, T., & Dai, Q. (2024). Audio matters too! Enhancing markerless motion capture with audio signals for string performance capture. ACM Transactions on Graphics, 43(4), Article 90. https://doi.org/10.1145/3658235
Uhlrich, S. D., Falisse, A., Kidziński, Ł., Muccini, J., Ko, M., Chaudhari, A. S., Hicks, J. L., & Delp, S. L. (2023). OpenCap: Human movement dynamics from smartphone videos. PLOS Computational Biology, 19(10), e1011462. https://doi.org/10.1371/journal.pcbi.1011462

Literature for each field: physiotherapy and EMG · violin pedagogy and learning technology · movement and sound analysis.