OpenEarable ExG: Open-Source Hardware for Ear-Based Biopotential Sensing Applications
Authors: 
Philipp Lepold, Tobias Röddiger, Tobias King, 
Kai Kunze, Christoph Maurer, 
Michael BeiglAuthors Info & Claims
Pages 916 - 920
Abstract
While traditional earphones primarily offer private audio spaces, so-called "earables" emerged to offer a variety of sensing capabilities. Pioneering platforms like OpenEarable have introduced novel sensing platforms targeted at the ears, incorporating various sensors. The proximity of the ears to the eyes, brain, and facial muscles has also sparked investigation into sensing biopotentials. However, currently there is no platform available that is targeted at the ears to sense biopotentials. To address this gap, we introduce OpenEarable ExG - an open-source hardware platform designed to measure biopotentials in and around the ears. OpenEarable ExG can be freely configured and has up to 7 sensing channels. We initially validate OpenEarable ExG in a study with a left-right in-ear dual-electrode montage setup with 3 participants. Our results demonstrate the successful detection of smooth pursuit eye movements via Electrooculography (EOG), alpha brain activity via Electroencephalography (EEG), and jaw clenching via Electromyography (EMG). OpenEarable ExG is part of the OpenEarable initiative and is fully open-source under MIT license.
References
[1]
Venkatesh Acharya. 2011. Improving common-mode rejection using the right-leg drive amplifier. Texas Instruments (2011), 1--11.
[2]
JW Ahn, Y Ku, DY Kim, J Sohn, J-H Kim, and HC Kim. 2018. Wearable in-the-ear EEG system for SSVEP-based brain-computer interface. Electronics Letters, Vol. 54, 7 (2018), 413--414.
[3]
Oliver Amft, Florian Wahl, Shoya Ishimaru, and Kai Kunze. 2015. Making Regular Eyeglasses Smart. IEEE Pervasive Computing, Vol. 14, 3 (2015), 32--43. https://doi.org/10.1109/MPRV.2015.60
[4]
Analog Devices. 2017. AD7124--4: 4-Channel, Low Noise, Low Power, 24-Bit, Sigma-Delta ADC with PGA. https://www.analog.com/media/en/technical-documentation/data-sheets/ad7124--4.pdf Accessed: 2024-06--25.
[5]
Analog Devices, Inc. 2021. MAX98357A/MAX98357B. Analog Devices, Inc. https://www.analog.com/media/en/technical-documentation/data-sheets/max98357a-max98357b.pdf Document 19--6416; Rev 4.
[6]
Shengjie Bi, Tao Wang, Ellen Davenport, Ronald Peterson, Ryan Halter, Jacob Sorber, and David Kotz. 2017. Toward a wearable sensor for eating detection. In Proceedings of the 2017 workshop on wearable systems and applications. 17--22.
[7]
Martin G Bleichner and Stefan Debener. 2017. Concealed, unobtrusive ear-centered EEG acquisition: cEEGrids for transparent EEG. Frontiers in human neuroscience, Vol. 11 (2017), 163.
[8]
Bosch Sensortec. 2015. BMX160 Small, low power inertial measurement unit. Bosch Sensortec GmbH. https://www.mouser.com/pdfdocs/BST-BMX160-DS000--11.pdf Document Number: BST-BMX160-DS000--11.
[9]
COSINE. 2024. COSINA333MRB Datasheet. https://wmsc.lcsc.com/wmsc/upload/file/pdf/v2/lcsc/2402190355_COSINE-COSINA333MRB_C17702539.pdf Accessed: 2024-07-03.
[10]
Datwyler. 2024. SoftPulse Electrodes. https://datwyler.com/company/innovation/softpulse/products Accessed: 2024-07-03.
[11]
Hao Dong, Paul M Matthews, and Yike Guo. 2016. A new soft material based in-the-ear EEG recording technique. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 5709--5712.
[12]
Ying Gu, Evy Cleeren, Jonathan Dan, Kasper Claes, Wim Van Paesschen, Sabine Van Huffel, and Borbála Hunyadi. 2017. Comparison between scalp EEG and behind-the-ear EEG for development of a wearable seizure detection system for patients with focal epilepsy. Sensors, Vol. 18, 1 (2017), 29.
[13]
L'ubovs Hládek, Bernd Porr, and W Owen Brimijoin. 2018. Real-time estimation of horizontal gaze angle by saccade integration using in-ear electrooculography. Plos one, Vol. 13, 1 (2018), e0190420.
[14]
Wiremu Hohaia, Blake W Saurels, Alan Johnston, Kielan Yarrow, and Derek H Arnold. 2022. Occipital alpha-band brain waves when the eyes are closed are shaped by ongoing visual processes. Scientific reports, Vol. 12, 1 (2022), 1194.
[15]
Fahim Kawsar, Chulhong Min, Akhil Mathur, and Alessandro Montanari. 2018. Earables for personal-scale behavior analytics. IEEE Pervasive Computing, Vol. 17, 3 (2018), 83--89.
[16]
Preben Kidmose, David Looney, Michael Ungstrup, Mike Lind Rank, and Danilo P Mandic. 2013. A study of evoked potentials from ear-EEG. IEEE Transactions on Biomedical Engineering, Vol. 60, 10 (2013), 2824--2830.
[17]
Hiroyuki Manabe, Masaaki Fukumoto, and Tohru Yagi. 2013. Conductive rubber electrodes for earphone-based eye gesture input interface. In Proceedings of the 2013 International Symposium on Wearable Computers. 33--40.
[18]
Microchip Technology Inc. 2014. MCP73831/2. Microchip Technology Inc. https://eu.mouser.com/datasheet/2/268/MCP73831_Family_Data_Sheet_DS20001984H-3441711.pdf Document DS20001984H.
[19]
Jacob L Newman, John S Phillips, and Stephen J Cox. 2021. Detecting positional vertigo using an ensemble of 2D convolutional neural networks. Biomedical Signal Processing and Control, Vol. 68 (2021), 102708.
[20]
Open Source Hardware Association. [n.,d.]. Open Source Hardware Association (OSHWA). https://www.oshwa.org/. Accessed: 2024-07-04.
[21]
OpenBCI. 2023. Cyton Biosensing Board. https://shop.openbci.com/products/cyton-biosensing-board-8-channel. Accessed: 2024-07-03.
[22]
Tobias Röddiger, Christopher Clarke, Paula Breitling, Tim Schneegans, Haibin Zhao, Hans Gellersen, and Michael Beigl. 2022. Sensing with earables: A systematic literature review and taxonomy of phenomena. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 6, 3 (2022), 1--57.
[23]
Tobias Röddiger, Tobias King, Dylan Ray Roodt, Christopher Clarke, and Michael Beigl. 2022. Openearable: Open hardware earable sensing platform. In Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers. 246--251.
[24]
M Teplan. 2002. FUNDAMENTALS OF EEG MEASUREMENT. MEASUREMENT SCIENCE REVIEW, Vol. 2 (2002).
[25]
u-blox. 2023. NINA-B3 series. u-blox AG. https://content.u-blox.com/sites/default/files/NINA-B3_DataSheet_UBX-17052099.pdf Document UBX-17052099.
[26]
Wilhelm Von Rosenberg, Theerasak Chanwimalueang, Valentin Goverdovsky, Nicholas S Peters, Christos Papavassiliou, and Danilo P Mandic. 2017. Hearables: Feasibility of recording cardiac rhythms from head and in-ear locations. Royal Society open science, Vol. 4, 11 (2017), 171214.
Index Terms
- OpenEarable ExG: Open-Source Hardware for Ear-Based Biopotential Sensing Applications
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October 2024
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Published: 05 October 2024
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- Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
- Carl-Zeiss-Stiftung (Carl-Zeiss-Foundation)
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UbiComp '24: The 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing
October 5 - 9, 2024
Melbourne VIC, Australia
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