Finite Element Modelling and Experimental Characterisation of Auricle Mechanics for Earable Design

Wearable devices are rapidly evolving into the next generation of smart technologies with the potential to transform daily life. Among these, auricle-mounted “earables” are emerging as a promising platform for neural interfaces, leveraging the ear’s anatomical accessibility, social acceptability, and structural stability. The auricle provides a natural site for integrating miniaturised EEG electrodes and sensors, but its compliant, anisotropic mechanics and susceptibility to deformation under motion pose significant challenges for device stability, comfort, and signal fidelity. This thesis develops a systematic framework for characterising auricle biomechanics and translating these insights into earable design. A multi-stage methodology was implemented, combining physical phantoms, volunteer experiments, and finite element (FE) simulations. First, simplified and anatomically refined auricle phantoms were constructed to develop controlled experiment methods under static and dynamic loading, from which stiffness, deformation angle, and natural frequency were quantified. In vivo experiments with 31 volunteers validated these findings, revealing gender and morphology dependent variations in auricle mechanics. Dynamic analysis further established resonance frequencies in the 20–30 Hz range, critical for understanding gait and motion induced artefacts. A FE model was then developed and validated against phantom and volunteer data. The nonlinear tissue behaviour of the auricle was captured by hyperelastic material model, while parametric studies demonstrated the influence of geometry, material parameters, and boundary constraints on auricle response. Finally, prototype earable devices were simulated and tested to assess contact pressure, impedance, and decoupling behaviour under locomotion. Results showed that device mass distribution and interface geometry critically affect both comfort and motion robustness. Together, this work establishes an experimentally validated computational platform for earable design. By linking auricle mechanics to electrode stability and motion artefact susceptibility, it fills a key gap in wearable neural interface research and provides practical guidance for future earable development.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2025

Author dc:creator

• Li, Yunpeng

Advisors dc:contributor.advisor

• Sutcliffe, michael
• Bance, manohar

• Finite element
• Biomechanics
• Wearable
• Earable
• Human Auricle

Licence

• https://www.repository.cam.ac.uk/bitstreams/4c2b9010-28a3-4eba-bd07-35acfd7e4c1d/download
• http://purl.org/NET/rdflicense/allrightsreserved

Language dc:language

eng

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.127205

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/398317