Listening to the Mind: Earable Acoustic Sensing of Cognitive Load

2025-12-20

AI Summary

Real-time, non-invasive cognitive load monitoring remains challenging in naturalistic settings. Method: This study proposes a novel paradigm leveraging acoustic sensing within the ear canal using off-the-shelf in-ear devices. During speech-based cognitive tasks, ear-canal acoustic signals are recorded while simultaneously embedding stimulus-frequency otoacoustic emissions (SFOAEs) to probe auditory sensitivity dynamics. Contribution/Results: We introduce SFOAEs for the first time into cognitive load inference, revealing a statistically significant association (p < 0.01) between auditory sensitivity changes at 3 kHz and cognitive load; 63.2% of participants exhibited peak responses at this frequency. Moreover, we identify inter-individual response patterns, enabling personalized modeling. The approach demonstrates robustness and scalability of ear-worn devices for real-time cognitive load assessment under ecologically valid conditions, establishing a new pathway toward ubiquitous neurophysiological monitoring.

Technology Category

• Humans and AI: Brain-Sensing and Analysis
• Cognitive Modeling & Cognitive Systems: Affective Computing
• Machine Learning: Hardware-aware ML

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

Earable acoustic sensing offers a powerful and non-invasive modality for capturing fine-grained auditory and physiological signals directly from the ear canal, enabling continuous and context-aware monitoring of cognitive states. As earable devices become increasingly embedded in daily life, they provide a unique opportunity to sense mental effort and perceptual load in real time through auditory interactions. In this study, we present the first investigation of cognitive load inference through auditory perception using acoustic signals captured by off-the-shelf in-ear devices. We designed speech-based listening tasks to induce varying levels of cognitive load, while concurrently embedding acoustic stimuli to evoke Stimulus Frequency Otoacoustic Emission (SFOAEs) as a proxy for cochlear responsiveness. Statistical analysis revealed a significant association (p < 0.01) between increased cognitive load and changes in auditory sensitivity, with 63.2% of participants showing peak sensitivity at 3 kHz. Notably, sensitivity patterns also varied across demographic subgroups, suggesting opportunities for personalized sensing. Our findings demonstrate that earable acoustic sensing can support scalable, real-time cognitive load monitoring in natural settings, laying a foundation for future applications in augmented cognition, where everyday auditory technologies adapt to and support the users mental health.

Problem

• Earable devices sense cognitive load via acoustic signals
• Study links cognitive load changes to auditory sensitivity variations
• Acoustic sensing enables real-time mental health monitoring in daily life

Innovation

• Earable acoustic sensing captures cognitive load signals
• Uses SFOAEs as proxy for cochlear responsiveness changes
• Enables real-time personalized monitoring in natural settings