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Background: The ear has become an attractive site for integrating biosensing technology due to its stable placement and unobtrusive character. A wide range of acoustic, mechanical, optical, and electrical sensors has been explored and is increasingly being integrated into modern ear-worn devices. Previous reviews, such as Röddiger et al. [1], have catalogued measurable phenomena and potential applications of earables. However, the usability of the resulting sensor data and the maturity of these sensors in ear-worn devices have not yet been systematically assessed.

Methods: A systematic review of approximately 130 studies focusing on ear-worn sensors was conducted using Google Scholar and IEEE Xplore. Each sensor type was evaluated for raw data, derivable physiological parameters, use cases in research studies and commercially available devices and implementation status in ear-worn devices. A maturity score (0–10) was assigned based on weighted criteria including market availability, data quality, validation, form factor and power use, reflecting both technical feasibility and practical usability.

Results: Acoustic sensors, including outward- and in-ear microphones, showed moderate maturity scores (6–7/10), with high market availability but variable validation and data quality. Inertial measurement units (IMUs) and photoplethysmography (PPG) sensors achieved higher maturity scores (7–9/10), benefiting from established validation and favorable form factors. Infrared and thermistor-based thermometers also scored highly (7–9/10), while electrical sensors such as EEG and ECG remained less mature (4–6/10) due to limited availability, validation and data quality. Across all modalities, a variety of physiological parameters can be derived from raw sensor signals. Depending on the sensor type, these parameters have been explored in research studies for a range of potential use cases.

Conclusions: Ear-level biosensors show varying levels of maturity across sensor types, with IMUs and PPG sensors being the most established, while EEG and ECG remain less mature. Although research demonstrates a wide range of potential use cases for physiological parameters derived from these sensors, commercially available devices are largely limited to basic applications, reflecting current limitations in data usability. Bridging this gap between research potential and current consumer applications could enable more advanced health monitoring.

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