A Body Knows the Pattern: A Performance System Exploring Embodied Rhythm and Phrasing via NIME

Evan O'Donnell

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract

This project builds on several decades of gesture mapping research in NIME to explore connections between body movement and tension and rhythmic phrasing in live electronic music performance. While there have been many applications of wearable sensors in performance practice, comparatively few NIME studies have applied these to work with rhythm and expressive timing. However, embodied cognition research suggests strong links between rhythm and movement, making this a fertile area for exploration. In this performance, I will harness inertial measurement units (IMU) and electromyogram (EMG) sensors to shape the outputs of a bespoke composed system using both direct mapping and interactive machine learning. I will explore and unpack multiple strategies for connecting arm and hand gestures to rhythmic phrasing, pattern, and texture, applying these to shape a library of field recordings and processed room samples in the context of both free and grid-based musical timing. By investigating embodied rhythm through wearable sensors and this library of sonic materials, I will unpack and reflect on the influences of the body's lived daily environment on expressive timing, and how this may emerge in both intuitive and unexpected ways.

Citation

Evan O'Donnell. 2026. A Body Knows the Pattern: A Performance System Exploring Embodied Rhythm and Phrasing via NIME. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.20782120 [PDF]

BibTeX Entry

@inproceedings{nime2026_music_32,
 abstract = {This project builds on several decades of gesture mapping research in NIME to explore connections between body movement and tension and rhythmic phrasing in live electronic music performance. While there have been many applications of wearable sensors in performance practice, comparatively few NIME studies have applied these to work with rhythm and expressive timing. However, embodied cognition research suggests strong links between rhythm and movement, making this a fertile area for exploration. In this performance, I will harness inertial measurement units (IMU) and electromyogram (EMG) sensors to shape the outputs of a bespoke composed system using both direct mapping and interactive machine learning. I will explore and unpack multiple strategies for connecting arm and hand gestures to rhythmic phrasing, pattern, and texture, applying these to shape a library of field recordings and processed room samples in the context of both free and grid-based musical timing. By investigating embodied rhythm through wearable sensors and this library of sonic materials, I will unpack and reflect on the influences of the body's lived daily environment on expressive timing, and how this may emerge in both intuitive and unexpected ways.},
 address = {London, United Kingdom},
 articleno = {32},
 author = {Evan O'Donnell},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.20782120},
 editor = {Lia Mice and Nicole Robson and Tara Pattenden},
 issn = {2220-4806},
 month = {June},
 note = {Live Performance},
 numpages = {3},
 pages = {131--133},
 presentation-video = {https://vimeo.com/1162290842},
 title = {A Body Knows the Pattern: A Performance System Exploring Embodied Rhythm and Phrasing via NIME},
 track = {Music},
 url = {http://nime.org/proceedings/2026/nime2026_music_32.pdf},
 year = {2026}
}