Authors: Amelie Hintermaier1; Iko Pieper1; Tamas Harczos1*
1audifon GmbH & Co. KG
Background Hearing aid technology is constantly evolving, resulting in ever more sophisticated algorithms and increasingly powerful hardware. The latter means multiple computing cores and often a multitude of coprocessors and accelerators. For the longest possible runtime, the power consumption must nevertheless be kept to a minimum, which makes hand-optimized firmware development inevitable to date. However, this, together with the complex hardware, renders the development of new algorithms rather difficult.
Method The goal of the work was to create a behind-the-ear (BTE) wearable platform that would facilitate the development and testing (under realistic conditions) of new algorithms. The system should consist of commercial off-the-shelf components, have a simple architecture and, despite easy programmability, approximately the performance and capabilities of a hearing aid. An electrical schematic, a PCB and an enclosure design as well as a firmware framework were developed from scratch.
Results An electrical circuit based on a low-cost single-core microcontroller (nRF52840/ISP1807) has emerged. The hardware further includes a power management unit, a rechargeable Li-Ion coin cell, two microphones, an amplified audio output, a µSD card interface, two push buttons as well as acceleration and temperature sensors along with interfaces for future peripherals. The implementation finds place on a 4-layer PCB, for which also a simple enclosure was designed and 3D-printed using FDM. The complete BTE system weighs about 10g. The audio path has 16 bit resolution, the sound pressure level at the output was limited to 96 dB in hardware to ensure safe development. The typical operating current is <8 mA.
Conclusion A promising platform was implemented, characterized and calibrated. With the help of this tool, first algorithms were implemented and tested. We conclude that general purpose microcontrollers of today are capable of handling complex audio signal processing tasks.