{{Infobox diagnostic | name = Ear-EEG | image = Ear-EEG2.jpg | alt = | caption = Examples of in-ear EEG mounts. On the left is seen a single earplug (right ear), on the right is seen a right earplug in ear | pronounce = | purpose =measure dynamics of brain activity | test of = | based on = | synonyms = | reference_range = }} '''Ear-EEG''' is a method for measuring dynamics of brain activity through the minute voltage changes observable on the skin, typically by placing electrodes on the scalp. In ear-EEG, the electrodes are exclusively placed in or around the outer ear, resulting in both a much greater invisibility and wearer mobility compared to full scalp electroencephalography (EEG), but also significantly reduced signal amplitude, as well as reduction in the number of brain regions in which activity can be measured. It may broadly be partitioned into two groups: those using electrode positions exclusively within the concha and ear canal, and those also placing electrodes close to the ear, usually hidden behind the ear lobe. Generally speaking, the first type will be the most invisible, but also offer the most challenging (noisy) signal. Ear-EEG is a good candidate for inclusion in a hearable device, however, due to the high complexity of ear-EEG sensors, this has not yet been done.
== History == Ear-EEG was first described in a patent application,<ref>{{cite patent|country=US|number=2007112277|pubdate=2007-05-17|title=Apparatus and method for the measurement and monitoring of bioelectric signal patterns|inventor1-last=Fischer|inventor1-first=Russell|inventor2-last=Ferraro|inventor2-first=Joseph|inventor3-last=Lal|inventor3-first=Prince|inventor4-last=Lusted|inventor4-first=Hugh |status=application}}, since abandoned.</ref> and subsequently in other publications.<ref>{{cite patent|country=EP|number=2448477|pubdate=2012-05-09|title=An ear plug with surface electrodes|assign1=Widex A/S|inventor1-last=Kidmose|inventor1-first=Preben |inventor2-last=Ungstrup|inventor2-first=Michael|inventor3-last=Rank|inventor3-first=Mike L.}}</ref><ref>{{cite conference |chapter=Auditory evoked responses from Ear-EEG recordings|last1= Kidmose|first1=Preben |title= 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society|year= 2012|pages= 586–589|location=San Diego, Cal |conference= EMBC 2012|doi=10.1109/EMBC.2012.6345999|isbn= 978-1-4577-1787-1}}</ref> Since then, it has grown to be an endeavor spread across multiple research groups<ref>{{cite journal |last=Bleichner |first=Martin|date=6 April 2015 |title=Exploring miniaturized EEG electrodes for brain-computer interfaces. An EEG you do not see? |pmc=4425967 |journal=Physiol Rep |volume=3 | issue= 4|article-number=e12362|pmid=25847919 |doi=10.14814/phy2.12362}}</ref> and collaborations, as well as private companies.<ref name=unitedSciences>{{cite web |url=http://www.unitedsciences.com/the-aware-kickstart-the-hearable-revolution |title=The Aware |work=United Sciences | Precision 3D Hole Scanning |date=20 April 2016 |publisher=United Sciences |access-date=25 August 2016}}</ref><ref>{{cite conference |title= Ear-EEG Allows Extraction of Neural Responses in Challenging Listening Scenarios – A Future Technology for Hearing Aids? |last1= Fiedler|first1=Lorenz |location=Orlando, Fl |conference= EMBC 2016}}</ref> Notable incarnations of the technology are the cEEGrid <ref name=ceegrid>{{cite journal |last=Debener|first=Stefan|date=17 November 2015 |title=Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear|pmc=4648079 |journal=Scientific Reports|volume=5 | article-number=16743 |doi=10.1038/srep16743 |pmid=26572314|bibcode=2015NatSR...516743D}}</ref><ref>{{Cite web|url=http://www.ceegrid.com|title=cEEGrid –|website=www.ceegrid.com|access-date=2016-11-14}}</ref> (see picture to the right) and the custom 3D-printed ear plugs from NeuroTechnology Lab (see picture above). Attempts at creating in-ear generic earpieces are also known to be under way.<ref>{{Cite book|last1=Kidmose|first1=P.|last2=Looney|first2=D.|last3=Jochumsen|first3=L.|last4=Mandic|first4=D. P.|title=2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |chapter=Ear-EEG from generic earpieces: A feasibility study |date=July 2013|publisher=IEEE|volume=2013|pages=543–546|doi=10.1109/embc.2013.6609557|pmid=24109744|isbn=978-1-4577-0216-7|s2cid=10278053}}</ref><ref>{{cite conference |title= A New Soft Material based In-The-Ear EEG Recording Technique |last1= Dong|first1=Hao |location=Orlando, Fl |conference= EMBC 2016}}</ref><ref>{{cite conference |title= Generic Viscoelastic In-Ear EEG Monitor |last1= Goverdovsky |first1=Valentin |location=Orlando, Fl |conference= EMBC 2016}}</ref><ref>{{cite journal |last=Goverdovsky |first=Valentin |date=1 January 2016 |title=In-Ear EEG From Viscoelastic Generic Earpieces: Robust and Unobtrusive 24/7 Monitoring |journal=IEEE Sensors Journal |publisher=IEEE |volume=16 |issue= 1|pages=271–277 |doi=10.1109/JSEN.2015.2471183 |bibcode=2016ISenJ..16..271G |hdl=10044/1/43182 |s2cid=44224053 |hdl-access=free }}</ref><ref>{{cite journal |last=Norton|first=James|date=31 March 2015 |title=Soft, curved electrode systems capable of integration on the auricle as a persistent brain–computer interface|pmc=4386388 |journal=PNAS |volume=112|issue= 13 |doi=10.1073/pnas.1424875112 |pmid=25775550 |pages=3920–3925|bibcode=2015PNAS..112.3920N|doi-access=free}}</ref> thumb|Demonstration of multiple cEEGrids on dummy heads|315x315px
== Uses in research == It is possible to think of multiple research areas in which an unobtrusive and invisible EEG system would be beneficial.<ref>{{cite journal |last=Casson|first=Alexander|date=10 May 2010 |title=Wearable electroencephalography. What is it, why is it needed, and what does it entail?|journal= IEEE Engineering in Medicine and Biology Magazine|volume=29|issue= 3|doi=10.1109/MEMB.2010.936545 |pmid=20659857|pages=44–56|hdl=10044/1/5910|s2cid=1891995|url=http://spiral.imperial.ac.uk/bitstream/10044/1/5910/1/final_paper.pdf}} </ref> Good examples are in studies of group dynamics or didactics, in which cases it would be very valuable to be able to monitor the effect of various events on individuals, while still letting them experience said events unfettered. And in this context, it is very important to perform detailed comparisons between ear-EEG and regular scalp EEG, as results need to be comparable across platforms. This has been done in multiple papers.<ref name="ceegrid" /><ref>{{cite journal |last=Mikkelsen|first=Kaare|date=18 November 2015 |title=EEG Recorded from the Ear: Characterizing the Ear-EEG Method|journal= Frontiers in Neuroscience|volume=9|page=438|doi=10.3389/fnins.2015.00438 |pmid=26635514|pmc=4649040|doi-access=free}}</ref><ref>{{cite journal |last=Bleichner|first=Martin|date=5 October 2016 |title=Identifying auditory attention with ear-EEG: cEEGrid versus high-density cap-EEG comparison|journal= Journal of Neural Engineering|volume=13|number=6|doi=10.1088/1741-2560/13/6/066004 |pmid=27705963|article-number=066004|bibcode=2016JNEng..13f6004B|doi-access=free}}</ref><ref name="Dong">{{cite book |last=Dong|first=Hao|date=18 October 2016 |doi=10.1109/EMBC.2016.7592023|pmid=28269551|isbn=978-1-4577-0220-4|hdl=10044/1/44965|chapter=A new soft material based in-the-ear EEG recording technique|title=2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |volume=2016|pages=5709–5712|s2cid=27566415}}</ref> In these it has been found that ear-EEG measurements are comparable to scalp EEG in the frequency domain; however, the time domain activity recorded by the two systems are notably different. Several papers have presented models (i.e. ear-EEG forward models) of how the electric field from electrical sources in the brain maps to potentials in the ear.<ref name=":4" /><ref>{{Cite journal|last1=Goverdovsky|first1=Valentin|last2=von Rosenberg|first2=Wilhelm|last3=Nakamura|first3=Takashi|last4=Looney|first4=David|last5=Sharp|first5=David J.|last6=Papavassiliou|first6=Christos|last7=Morrell|first7=Mary J.|last8=Mandic|first8=Danilo P.|date=December 2017|title=Hearables: Multimodal physiological in-ear sensing|journal=Scientific Reports|volume=7|issue=1|page=6948|doi=10.1038/s41598-017-06925-2|issn=2045-2322|pmc=5537365|pmid=28761162|bibcode=2017NatSR...7.6948G|arxiv=1609.03330}}</ref><ref>{{Cite journal|last1=Kidmose|first1=Preben|last2=Looney|first2=David|last3=Ungstrup|first3=Michael|last4=Rank|first4=Mike Lind|last5=Mandic|first5=Danilo P.|date=October 2013|title=A Study of Evoked Potentials From Ear-EEG|journal=IEEE Transactions on Biomedical Engineering|volume=60|issue=10|pages=2824–2830|doi=10.1109/TBME.2013.2264956|pmid=23722447|s2cid=12550407|issn=0018-9294}}</ref> The ear-EEG forward models enable prediction of the potentials in the ear for a specific neural phenomenon, and can be used to improve the understanding of which neural sources that can be measured with ear-EEG<ref name=":4" /> thumb|581x581px|Example of a scalp topography (middle) with corresponding ear-topographies (left and right). The topographies show the potential on the scalp and in the ears for a single dipolar brain source and were calculated using an individualized ear-EEG forward model as described by Kappel et al.<ref name=":4">{{Cite journal|last1=Kappel|first1=Simon L.|last2=Makeig|first2=Scott|last3=Kidmose|first3=Preben|date=2019-09-10|title=Ear-EEG Forward Models: Improved Head-Models for Ear-EEG|journal=Frontiers in Neuroscience|volume=13|page=943|doi=10.3389/fnins.2019.00943|issn=1662-453X|pmc=6747017|pmid=31551697|doi-access=free}}</ref>
== Dry-contact electrode ear-EEG == Dry-contact electrode ear-EEG is a method in which no gel is applied between the electrode and the skin.<ref name=":2" /><ref name=":3" /><ref>{{Cite book|last1=Xiong Zhou|last2=Qiang Li|last3=Kilsgaard|first3=Soren|last4=Moradi|first4=Farshad|last5=Kappel|first5=Simon L.|last6=Kidmose|first6=Preben|date=June 2016 |doi=10.1109/VLSIC.2016.7573559|isbn=978-1-5090-0635-9|chapter=A wearable ear-EEG recording system based on dry-contact active electrodes|title=2016 IEEE Symposium on VLSI Circuits (VLSI-Circuits)|pages=1–2|s2cid=37530730}}</ref> This method generally improves the comfort and user-friendliness for long-term and real-life recordings. Because no gel is applied to the electrodes, the user can potentially mount the ear-EEG device without assistance. alt=High-density ear-EEG.|thumb|Example of high-density ear-EEG. On the left is seen a high-density ear-EEG earpiece mounted in the ear. On the right is a picture of a high-density ear-EEG soft-earpiece with dry-contact electrodes.<ref name=":1" /><ref name=":0">{{Cite journal|last1=Kappel|first1=Simon L.|last2=Rank|first2=Mike Lind|last3=Toft|first3=Hans Olaf|last4=Andersen|first4=Mikael|last5=Kidmose|first5=Preben|date=2018|title=Dry-Contact Electrode Ear-EEG|journal=IEEE Transactions on Biomedical Engineering|volume=66|issue=1|pages=150–158|doi=10.1109/tbme.2018.2835778|pmid=29993415|s2cid=51614629|issn=0018-9294|doi-access=free}}</ref>|337x337px Dry-contact electrode ear-EEG have been used to perform high-density ear-EEG recordings, which enable mapping of the brain response on a topographic 3D map of the ear (Ear-topographies).<ref name=":1">{{Cite book|last1=Kappel|first1=Simon L.|last2=Kidmose|first2=Preben|date=July 2017 |doi=10.1109/embc.2017.8037338|pmid=29060380|isbn=978-1-5090-2809-2|chapter=High-density ear-EEG|title=2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |volume=2017|pages=2394–2397|s2cid=8902094}}</ref>
When using dry-contact electrodes, the interface between the skin and the electrodes are mainly defined by the electrochemical properties of the electrode material, the mechanical design of the electrode, the surface properties of the electrode, and how the electrode is retained against the skin.<ref>{{Cite journal|last1=Chi|first1=Yu Mike|last2=Jung|first2=Tzyy-Ping|last3=Cauwenberghs|first3=Gert|date=2010|title=Dry-Contact and Noncontact Biopotential Electrodes: Methodological Review|journal=IEEE Reviews in Biomedical Engineering|volume=3|pages=106–119|doi=10.1109/RBME.2010.2084078|pmid=22275204|s2cid=2705602|issn=1937-3333|citeseerx=10.1.1.227.2124}}</ref> To improve these aspects for ear-EEG, nanostructured electrodes and soft earpieces have been proposed.<ref name=":0" /> The electronic instrumentation must also be carefully designed to accommodate dry-contact electrodes.<ref>{{Cite book|last1=Kappel|first1=Simon L.|last2=Kidmose|first2=Preben|date=August 2015 |doi=10.1109/embc.2015.7319063|pmid=26736963|isbn=978-1-4244-9271-8|chapter=Study of impedance spectra for dry and wet EarEEG electrodes|title=2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |volume=2015|pages=3161–3164|s2cid=450962}}</ref><ref>{{Cite book|last1=Xiong Zhou|last2=Qiang Li|last3=Kilsgaard|first3=Søren|last4=Moradi|first4=Farshad|last5=Kappel|first5=Simon L.|last6=Kidmose|first6=Preben|date=June 2016 |doi=10.1109/vlsic.2016.7573559|isbn=978-1-5090-0635-9|chapter=A wearable ear-EEG recording system based on dry-contact active electrodes|title=2016 IEEE Symposium on VLSI Circuits (VLSI-Circuits)|pages=1–2|s2cid=37530730}}</ref>
== Real-life monitoring == The state of the human brain is influenced by the surrounding environment, and the response from the brain is influenced by the state of the brain. Thus, restricting brain research to a laboratory represents a fundamental limitation. Real-life monitoring of ear-EEG overcome this limitation, and enable research of evoked responses and spontaneous responses related to everyday life situations.<ref>{{Cite journal|last1=Bleichner|first1=Martin G.|last2=Debener|first2=Stefan|date=2017-04-07|title=Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG|journal=Frontiers in Human Neuroscience|volume=11|page=163|doi=10.3389/fnhum.2017.00163|issn=1662-5161|pmc=5383730|pmid=28439233|doi-access=free}}</ref><ref name=":3">{{Cite book|last1=Kappel|first1=Simon L.|last2=Kidmose|first2=Preben|date=July 2018 |doi=10.1109/embc.2018.8513532|pmid=30441575|isbn=978-1-5386-3646-6|chapter=Real-Life Dry-Contact Ear-EEG|title=2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |volume=2018|pages=5470–5474|s2cid=53093217}}</ref>
The compact and discreet nature of ear-EEG devices makes it suitable for real-life EEG monitoring.<ref>{{Cite thesis|last=Kappel|first=Simon L.|title=Development and Characterization of Ear-EEG for Real-Life Brain-Monitoring|date=September 2016|degree=Ph.D.|publisher=Aarhus University|url=https://ebooks.au.dk/index.php/aul/catalog/book/260|doi=10.7146/aul.260.183|isbn=978-87-7507-420-4 }}</ref><ref>{{Cite journal|last1=Bleichner|first1=Martin G.|last2=Lundbeck|first2=Micha|last3=Selisky|first3=Matthias|last4=Minow|first4=Falk|last5=Jäger|first5=Manuela|last6=Emkes|first6=Reiner|last7=Debener|first7=Stefan|last8=De Vos|first8=Maarten|date=April 2015|title=Exploring miniaturized EEG electrodes for brain-computer interfaces. An EEG you do not see?|journal=Physiological Reports|volume=3|issue=4|article-number=e12362|doi=10.14814/phy2.12362|issn=2051-817X|pmc=4425967|pmid=25847919}}</ref><ref name=":2">{{Cite journal|last1=Hoon Lee|first1=Joong|last2=Min Lee|first2=Seung|last3=Jin Byeon|first3=Hang|last4=Sook Hong|first4=Joung|last5=Suk Park|first5=Kwang|last6=Lee|first6=Sang-Hoon|date=August 2014|title=CNT/PDMS-based canal-typed ear electrodes for inconspicuous EEG recording|journal=Journal of Neural Engineering|volume=11|issue=4|article-number=046014|doi=10.1088/1741-2560/11/4/046014|issn=1741-2552|pmid=24963747|bibcode=2014JNEng..11d6014L|s2cid=37513095 }}</ref><ref>{{Cite book|last1=Fiedler|first1=L.|last2=Obleser|first2=J.|last3=Lunner|first3=T.|last4=Graversen|first4=C.|date=August 2016 |doi=10.1109/EMBC.2016.7592020|pmid=28269548|isbn=978-1-4577-0220-4|chapter=Ear-EEG allows extraction of neural responses in challenging listening scenarios — A future technology for hearing aids?|title=2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |volume=2016|pages=5697–5700|s2cid=206635991}}</ref><ref name=":5">{{Cite book|last1=Pham|first1=Nhat|last2=Dinh|first2=Tuan|last3=Raghebi|first3=Zohreh|last4=Kim|first4=Taeho|last5=Bui|first5=Nam|last6=Nguyen|first6=Phuc|last7=Truong|first7=Hoang|last8=Banaei-Kashani|first8=Farnoush|last9=Halbower|first9=Ann|last10=Dinh|first10=Thang|last11=Vu|first11=Tam|title=Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services |chapter=WAKE |date=2020-06-15|chapter-url=https://doi.org/10.1145/3386901.3389032|series=MobiSys '20|location=Toronto, Ontario, Canada|publisher=Association for Computing Machinery|pages=404–418|doi=10.1145/3386901.3389032|isbn=978-1-4503-7954-0|s2cid=219398352}}</ref> A general problem when recordings EEG is the interference arising from noise and artifacts. In a laboratory environment, artifacts and interference can largely be avoided or controlled, in real-life this is challenging. Physiological artifacts are a category of artifacts with physiological origin, in contrast to artifacts arising from electrical interference. A study of physiological artifacts in ear-EEG found artifacts from jaw muscle contractions to be higher for ear-EEG compared to the scalp EEG, whereas eye-blinking did not influence the ear-EEG.<ref>{{Cite journal|last1=Kappel|first1=Simon L.|last2=Looney|first2=David|last3=Mandic|first3=Danilo P.|last4=Kidmose|first4=Preben|date=2017-08-11|title=Physiological artifacts in scalp EEG and ear-EEG|journal=BioMedical Engineering OnLine|volume=16|issue=1|page=103|doi=10.1186/s12938-017-0391-2|issn=1475-925X|pmc=5553928|pmid=28800744 |doi-access=free }}</ref><ref>{{Cite book|last1=Kappel|first1=Simon L.|last2=Looney|first2=David|last3=Mandic|first3=Danilo P.|last4=Kidmose|first4=Preben|date=August 2014 |doi=10.1109/embc.2014.6943931|pmid=25570299|isbn=978-1-4244-7929-0|chapter=A method for quantitative assessment of artifacts in EEG, and an empirical study of artifacts|title=2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |volume=2014|pages=1686–1690|s2cid=12524339}}</ref>
== Sleep monitoring == A promising use case is in long-term sleep monitoring, where there is presently a need for a more user friendly (and cheaper) alternative to the gold standard polysomnography.<ref>{{Cite journal|last1=Looney|first1=David|last2=Goverdovsky|first2=Valentin|last3=Rosenzweig|first3=Ivana|last4=Morrell|first4=Mary J.|last5=Mandic|first5=Danilo P.|date=December 2016|title=Wearable In-Ear Encephalography Sensor for Monitoring Sleep. Preliminary Observations from Nap Studies|journal=Annals of the American Thoracic Society|volume=13|issue=12|pages=2229–2233|doi=10.1513/AnnalsATS.201605-342BC|issn=2329-6933|pmc=5291497|pmid=27684316}}</ref><ref>{{cite conference|last1=Stochholm|first1=Andreas|title=Automatic Sleep Stage Classification using Ear-EEG|conference=EMBC 2016|location=Orlando, Fl}}</ref><ref>{{cite journal|last1=Mikkelsen|first1=Kaare|title=Automatic sleep staging using ear-EEG|journal= BioMedical Engineering OnLine|volume=16|number=1|doi=10.1186/s12938-017-0400-5 |pmid=28927417|pmc=5606130|article-number=111|year=2017 |doi-access=free }}</ref><ref>{{Cite book|last1=Nguyen|first1=Anh|last2=Alqurashi|first2=Raghda|last3=Raghebi|first3=Zohreh|last4=Banaei-kashani|first4=Farnoush|last5=Halbower|first5=Ann C.|last6=Vu|first6=Tam|title=Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM |chapter=A Lightweight and Inexpensive In-ear Sensing System for Automatic Whole-night Sleep Stage Monitoring |date=2016|chapter-url=http://dl.acm.org/citation.cfm?doid=2994551.2994562|location=Stanford, CA, USA|publisher=ACM Press|pages=230–244|doi=10.1145/2994551.2994562|isbn=978-1-4503-4263-6|series=SenSys '16|s2cid=11709648}}</ref> Innovation Fund Denmark recently funded a large project on using ear-EEG for sleep monitoring, in a collaboration between industry and Aarhus University in Denmark ,<ref>{{cite web |url=https://innovationsfonden.dk/en/node/1637/ |title=Øreprop skal aflæse søvnløses hjerneaktivitet |publisher=Innovation Fund Denmark|access-date=4 January 2018}}</ref> however, development of an ear-EEG based sleep monitor is a global endeavor, with other prominent examples taking place at the University of Colorado ,<ref>{{cite conference|last1=Nguyen|first1=Anh|title=A Lightweight and Inexpensive In-ear Sensing System For Automatic Whole-night Sleep Stage Monitoring|conference=14th ACM Conference on Embedded Network Sensor System|location=Stanford, USA}}</ref> Imperial College London <ref>{{cite book |last=Moss |first=James |date=2017 | chapter=The Efficacy of In-Ear Electroencephalography (EEG) to Monitor Sleep Latency and the Impact of Sleep Deprivation |title=A80-C. NOVEL DIAGNOSTIC APPROACHES TO SDB|article-number=A7596 | chapter-url=http://www.atsjournals.org/doi/abs/10.1164/ajrccm-conference.2017.195.1_MeetingAbstracts.A7596|doi=10.1164/ajrccm-conference.2017.195.1_MeetingAbstracts.A7596 |publisher=American Thoracic Society |series=American Thoracic Society International Conference Abstracts |doi-broken-date=12 July 2025 }}</ref><ref name="Dong" /> as well as the University of Oxford.<ref name=":5" />
== Possible commercial uses == Despite the lack of ear-EEG products on the market, several companies have revealed investments in ear-EEG technology. Foremost of these are the hearing aid producers Oticon <ref>{{cite conference |title= Around-the-Ear EEG Reflects the Attended Speaker in Multi-Speaker Scenario |last1= Fiedler|first1=Lorenz |location=Orlando, Fl |conference= EMBC 2016}}</ref> and Widex and its sister company T&W Engineering,<ref>{{cite web |url=http://eng.au.dk/en/research-in-engineering/research-projects/electrical-and-computer-engineering-research-projects/ear-eeg-based-hypoglycaemia-alarm/ |title=Ear EEG-based Hypoglycaemia Alarm |publisher=Aarhus University |access-date=31 August 2016}}</ref> who are looking into hearing-aid applications, the feasibility of which there appears to be some support for,<ref>{{cite journal |last=Mirkovic|first=Bojana|date=27 July 2016 |title=Target Speaker Detection with Concealed EEG Around the Ear|journal= Frontiers in Neuroscience|volume=9|page=438|doi=10.3389/fnins.2015.00438 |pmid=26635514|pmc=4649040|doi-access=free}}</ref><ref>{{cite conference |title= Ear-EEG Allows Extraction of Neural Responses in Challenging Listening Scenarios – A Future Technology for Hearing Aids? |last1= Mirkovic|first1=Bojana |location=Orlando, Fl |conference= EMBC 2016}}</ref> and a hypoglycemia alarm.
Other potential use cases which are known to have been explored are driver drowsiness detection,<ref>{{cite conference |title= Driver Drowsiness Detection using the In-Ear EEG |last1= Hwang |first1=Taeho|location=Orlando, Fl |conference= EMBC 2016}}</ref> BCI<ref>{{cite conference |title= Feasibility of using Ear EEG for Developing a Practical Brain-Computer Interface System: A Preliminary Study |last1= Choi|first1=Soo-In |location=Orlando, Fl |conference= EMBC 2016}}</ref><ref>{{Cite book|last1=Yu-Te Wang|last2=Nakanishi|first2=Masaki|last3=Kappel|first3=Simon Lind|last4=Kidmose|first4=Preben|last5=Mandic|first5=Danilo P.|last6=Yijun Wang|last7=Chung-Kuan Cheng|last8=Tzyy-Ping Jung|date=August 2015 |doi=10.1109/embc.2015.7318845|pmid=26736745|isbn=978-1-4244-9271-8|chapter=Developing an online steady-state visual evoked potential-based brain-computer interface system using EarEEG|title=2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |volume=2015|pages=2271–2274|s2cid=5996098}}</ref> and biometric identification.<ref>{{cite conference |title= Passthoughts Authentication with Low Cost EarEEG |last1= Yang|first1=Jong-Kai|location=Orlando, Fl |conference= EMBC 2016}}</ref>
==References== {{Reflist|30em}}
Category:Electroencephalography Category:Electrophysiology Category:Neurophysiology Category:Neurotechnology Category:Brain–computer interface Category:Electrodiagnosis