PP606 - Preliminary Evaluation of Ear-Level Gait and Postural Stability Monitoring Technology

Abstract: Hearing aids are among the few wearable devices that can be worn, comfortably and unobtrusively, for extended periods of time. We postulate that the embedded motion sensors of these ear-level devices may also be suitable for monitoring the wearer’s gait and postural stability during structured and unstructured activities. The present study will provide preliminary findings regarding the technological feasibility of using hearing aids with embedded motion sensors to monitor a wearer’s gait and postural stability as means to assess future risk for falls.

Summary:

Hearing aids are among the few wearable devices that can be worn, comfortably and unobtrusively, for extended periods of time. Recently, motion sensors have been embedded into hearing aids for the purposes of tracking the wearer’s daily physical activity and to automatically send notifications to caregivers when a wearer’s fall is detected (Burwinkel et al., 2020).

We postulate that the embedded motion sensors of these ear-level devices may also be suitable for monitoring the wearer’s gait and postural stability during structured and unstructured activities. For example, wearable motion sensor data, obtained during instrumented falls risk screening tasks, has previously been used to detect significant differences between fallers and non-fallers (Howcroft, 2016; Zakaria et al., 2015). Evidence also suggests that daily physical activity level and the experience of near falls are significantly associated with the incidence of future falls (Inouye et al., 2007; Nagai et al., 2017).

The present authors will present preliminary findings regarding the technological feasibility of using hearing aids with embedded motion sensors to monitor a wearer’s gait and postural stability to assess future risk for falls.

References:

 Burwinkel, J. R., Xu, B., & Crukley, J. (2020). Preliminary Examination of the Accuracy of a Fall Detection Device Embedded into Hearing Instruments. Journal of the American Academy of Audiology, 31(06), 393–403. https://doi.org/10.3766/jaaa.19056

Howcroft, J. (2016). Evaluation of Wearable Sensors as an Older Adult Fall Risk Assessment Tool. https://uwspace.uwaterloo.ca/handle/10012/10587

Inouye, S. K., Studenski, S., Tinetti, M. E., & Kuchel, G. A. (2007). Geriatric Syndromes: Clinical, Research, and Policy Implications of a Core Geriatric Concept: (See Editorial Comments by Dr. William Hazzard on pp 794–796). Journal of the American Geriatrics Society, 55(5), 780–791. https://doi.org/10.1111/j.1532-5415.2007.01156.x

Nagai, K., Yamada, M., Komatsu, M., Tamaki, A., Kanai, M., Miyamoto, T., Tsukagoshi, R., & Tsuboyama, T. (2017). Near falls predict substantial falls in older adults: A prospective cohort study: Near falls predict substantial falls. Geriatrics & Gerontology International, 17(10), 1477–1480. https://doi.org/10.1111/ggi.12898

Zakaria, N. A., Kuwae, Y., Tamura, T., Minato, K., & Kanaya, S. (2015). Quantitative analysis of fall risk using TUG test. Computer Methods in Biomechanics and Biomedical Engineering, 18(4), 426–437. https://doi.org/10.1080/10255842.2013.805211