Bring Your Own Bow: Real-Time Bowing Parameter Estimation from String Sensor Data

Eoghan Ó Néill, Maarten van Walstijn, and Miguel Ortiz

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract

We present methods for real-time estimation of bowing force and bow velocity from a single bowed string using sensors located off-the-bow. Bow velocity is estimated from the voltage induced in the string as it moves through a fixed magnetic field at the bowing point. A histogram-based method is used to isolate the sticking phase of bowed-string motion, when bow and string move at the same velocity. Bowing force is estimated from reaction forces measured at the string supports using load cells. The system is implemented on a compact monochord and provides robust estimates of bowing parameters. We describe the sensing hardware, signal processing, and calibration procedures, and evaluate the accuracy, limitations, and practical operating ranges of the proposed methods. Real-time coupling of the estimated parameters to a bowed-mass physical model demonstrates their use as excitation signals for friction-driven physical models. The results indicate that these methods are well suited for the design of bowed virtual-acoustic instruments.

Citation

Eoghan Ó Néill, Maarten van Walstijn, and Miguel Ortiz. 2026. Bring Your Own Bow: Real-Time Bowing Parameter Estimation from String Sensor Data. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.20784297 [PDF]

BibTeX Entry

@inproceedings{nime2026_99,
 abstract = {We present methods for real-time estimation of bowing force and bow velocity from a single bowed string using sensors located off-the-bow. Bow velocity is estimated from the voltage induced in the string as it moves through a fixed magnetic field at the bowing point. A histogram-based method is used to isolate the sticking phase of bowed-string motion, when bow and string move at the same velocity. Bowing force is estimated from reaction forces measured at the string supports using load cells. The system is implemented on a compact monochord and provides robust estimates of bowing parameters. We describe the sensing hardware, signal processing, and calibration procedures, and evaluate the accuracy, limitations, and practical operating ranges of the proposed methods. Real-time coupling of the estimated parameters to a bowed-mass physical model demonstrates their use as excitation signals for friction-driven physical models. The results indicate that these methods are well suited for the design of bowed virtual-acoustic instruments.},
 address = {London, United Kingdom},
 articleno = {99},
 author = {Eoghan Ó Néill and Maarten van Walstijn and Miguel Ortiz},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.20784297},
 editor = {Benedict Gaster and João Tragtenberg and Anna Xambó and Tom Mitchell},
 issn = {2220-4806},
 month = {June},
 note = {},
 numpages = {7},
 pages = {841--847},
 presentation-video = {https://youtu.be/hkMqzuFD8sE},
 title = {Bring Your Own Bow: Real-Time Bowing Parameter Estimation from String Sensor Data},
 track = {paper},
 url = {http://nime.org/proceedings/2026/nime2026_99.pdf},
 year = {2026}
}