EarGait: Estimation of Temporal Gait Parameters from Hearing Aid Integrated Inertial Sensors

Seifer AK, Dorschky E, Küderle A, Moradi H, Hannemann R, Eskofier B (2023)

Publication Language: English

Publication Type: Journal article

Publication year: 2023


Book Volume: 23

Article Number: 6565

Journal Issue: 14

URI: https://www.mdpi.com/1424-8220/23/14/6565

DOI: 10.3390/s23146565

Open Access Link: https://www.mdpi.com/1424-8220/23/14/6565


Wearable sensors are able to monitor physical health in a home environment and detect changes in gait patterns over time. To ensure long-term user engagement, wearable sensors need to be seamlessly integrated into the user’s daily life, such as hearing aids or earbuds. Therefore, we present EarGait, an open-source Python toolbox for gait analysis using inertial sensors integrated into hearing aids. This work contributes a validation for gait event detection algorithms and the estimation of temporal parameters using ear-worn sensors. We perform a comparative analysis of two algorithms based on acceleration data and propose a modified version of one of the algorithms. We conducted a study with healthy young and elderly participants to record walking data using the hearing aid’s integrated sensors and an optical motion capture system as a reference. All algorithms were able to detect gait events (initial and terminal contacts), and the improved algorithm performed best, detecting 99.8% of initial contacts and obtaining a mean stride time error of 12 ± 32 ms. The existing algorithms faced challenges in determining the laterality of gait events. To address this limitation, we propose modifications that enhance the determination of the step laterality (ipsi- or contralateral), resulting in a 50% reduction in stride time error. Moreover, the improved version is shown to be robust to different study populations and sampling frequencies but is sensitive to walking speed. This work establishes a solid foundation for a comprehensive gait analysis system integrated into hearing aids that will facilitate continuous and long-term home monitoring.

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Seifer, A.-K., Dorschky, E., Küderle, A., Moradi, H., Hannemann, R., & Eskofier, B. (2023). EarGait: Estimation of Temporal Gait Parameters from Hearing Aid Integrated Inertial Sensors. Sensors, 23(14). https://dx.doi.org/10.3390/s23146565


Seifer, Ann-Kristin, et al. "EarGait: Estimation of Temporal Gait Parameters from Hearing Aid Integrated Inertial Sensors." Sensors 23.14 (2023).

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