Power capacity from earcanal dynamic motion

In-ear devices, such as a hearing aids, electronic earplugs, and wearables, need electrical power to operate. Batteries are the current solution, but unfortunately they also create other problems. For example, several hundred million users, mostly elderly, must change their hearing aid batteries on a weekly basis, which represents not only significant financial costs but a negative environmental impact. A promising alternative involves harvesting energy by converting the dynamic jaw movements into electrical energy via the earcanal. The extent that jaw movements distort the earcanal is still unknown, making it difficult to design the appropriate energy harvesting system for the earplug. Moreover, the finite element methods are barely capable to model the behavior of the earcanal distortion because of the complexity of mechanisms that deform the earcanal. However, this paper presents an alternative method, based on analytical considerations, to understand in-ear mechanical quasi-static deformations using earcanal point clouds. This model quantifies the bending and compressive movements of the earcanal. It can therefore be used to select an appropriate deformation mode for harvesting energy from the earcanal’s dynamic motion. The value of this approach was illustrated by calculating the obtainable mechanical energy from 12 human subjects. On average, the bending energy in a human earcanal was found to be three times greater than the radial compression energy. This key finding will need to be considered in the design of future in-ear energy harvesting devices. Such an energy harvesting device has the potential to revolutionize the market for in-ear wearable devices and hearing aids by complementing or replacing battery technology

Custom-Fitted In- and Around-the-Ear Sensors for Unobtrusive and On-the-Go EEG Acquisitions: Development and Validation

Objectives: This paper aims to validate the performance and physical design of a wearable, unobtrusive ear-centered electroencephalography (EEG) device, dubbed “EARtrodes”, using early and late auditory evoked responses. Results would also offer a proof-of-concept for the device to be used as a concealed brain–computer interface (BCI). Design: The device is composed of a custom-fitted earpiece and an ergonomic behind-the-ear piece with embedded electrodes made of a soft and flexible combination of silicone rubber and carbon fibers. The location of the conductive silicone electrodes inside the ear canal and the optimal geometry of the behind-the-ear piece were obtained through morphological and geometrical analysis of the human ear canal and the region around-the-ear. An entirely conductive generic earpiece was also developed to assess the potential of a universal, more affordable solution. Results: Early latency results illustrate the conductive silicone electrodes’ capability to record quality EEG signals, comparable to those obtained with traditional gold-plated electrodes. Additionally, late latency results demonstrate EARtrodes’ capacity to reliably detect decision-making processes from the ear. Conclusions: EEG results validate the performance of EARtrodes as a circum-aural and intra-aural EEG recording system adapted for a wide range of applications in audiology, neuroscience, clinical research, and as an unobtrusive BCI