Project Description:

In recent years, particular attention has been devoted to earable acoustic sensing due to its numerous applications. However, the lack of a common platform for accessing raw audio samples has forced researchers/developers to pay great efforts to the trifles of prototyping often irrelevant to the core sensing functions. Meanwhile, the growing popularity of active noise cancellation (ANC) has endowed common earphones with high standard acoustic capability yet to be explored by sensing. To this end, we propose EarACE to be the first acoustic sensing platform exploiting the native acoustics of commercial ANC earphones, significantly improving upon self-crafted earphone sensing devices. EarACE takes a compact design to handle hardware heterogeneity and to deliver flexible control on audio facilities. Leveraging a systematic study on in-ear acoustic signals, EarACE gains abilities to combat performance sensitivity to device wearing states and to eliminate body motion interference. We further implement three major acoustic sensing applications to showcase the efficacy and adaptability of EarACE; the results evidently demonstrate EarACE's promising future in facilitating earable acoustic sensing research. We have implemented our TDC structure in popular FPGA platforms including Intel and Xilinx FPGAs. Results demonstrate that our TDC can readily achieve a less than 0.3~LSB INL even without any calibration tricks.

Acknowledgement:

• This project is filed on December 2021 and is patented. For more information please visit our git repository

  People:

  • Dr. Chao Cai (Associate Proffessor, College of Life Science & Engineering) - Huazhong University of Science and Technology

  Related Publications:

• [1] Yetong Cao, Chao Cai, et. al. "EarACE: Empowering Versatile Acoustic Sensing via Earable Active Noise Cancellation Platform", in ACM Ubicomp,2023