{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T04:10:42Z","timestamp":1790741442806,"version":"4.1.0"},"reference-count":47,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T00:00:00Z","timestamp":1726531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Movement intentions of motor impaired individuals can be detected in laboratory settings via electroencephalography Brain\u2013Computer Interfaces (EEG-BCIs) and used for motor rehabilitation and external system control. The real-world BCI use is limited by the costly, time-consuming, obtrusive, and uncomfortable setup of scalp EEG. Ear-EEG offers a faster, more convenient, and more aesthetic setup for recording EEG, but previous work using expensive amplifiers detected motor intentions at chance level. This study investigates the feasibility of a low-cost ear-EEG BCI for the detection of tongue and hand movements for rehabilitation and control purposes. In this study, ten able-bodied participants performed 100 right wrist extensions and 100 tongue-palate movements while three channels of EEG were recorded around the left ear. Offline movement vs. idle activity classification of ear-EEG was performed using temporal and spectral features classified with Random Forest, Support Vector Machine, K-Nearest Neighbours, and Linear Discriminant Analysis in three scenarios: Hand (rehabilitation purpose), hand (control purpose), and tongue (control purpose). The classification accuracies reached 70%, 73%, and 83%, respectively, which was significantly higher than chance level. These results suggest that a low-cost ear-EEG BCI can detect movement intentions for rehabilitation and control purposes. Future studies should include online BCI use with the intended user group in real-life settings.<\/jats:p>","DOI":"10.3390\/s24186004","type":"journal-article","created":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T01:16:10Z","timestamp":1726622170000},"page":"6004","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Detection of Movement-Related Brain Activity Associated with Hand and Tongue Movements from Single-Trial Around-Ear EEG"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1455-0905","authenticated-orcid":false,"given":"D\u00e1vid","family":"Guly\u00e1s","sequence":"first","affiliation":[{"name":"Department of Health Science and Technology, Aalborg University, 9260 Gistrup, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7729-4359","authenticated-orcid":false,"given":"Mads","family":"Jochumsen","sequence":"additional","affiliation":[{"name":"Department of Health Science and Technology, Aalborg University, 9260 Gistrup, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1111\/j.1365-2702.2010.03509.x","article-title":"Quality of life, anxiety and depression in ALS patients and their next of kin","volume":"20","author":"Strang","year":"2011","journal-title":"J. Clin. Nurs."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"19","DOI":"10.5114\/hm.2020.89910","article-title":"Functionality and quality of life in patients with amyotrophic lateral sclerosis: A cross-sectional study","volume":"21","author":"Oliveira","year":"2020","journal-title":"Hum. Mov."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2351","DOI":"10.1113\/JP278775","article-title":"Neuropsychological and neurophysiological aspects of brain-computer-interface (BCI) control in paralysis","volume":"599","author":"Chaudhary","year":"2021","journal-title":"J. Physiol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1016\/S1388-2457(02)00057-3","article-title":"Brain\u2013computer interfaces for communication and control","volume":"113","author":"Wolpaw","year":"2002","journal-title":"Clin. Neurophysiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"046085","DOI":"10.1088\/1741-2552\/ac0488","article-title":"Online control of an assistive active glove by slow cortical signals in patients with amyotrophic lateral sclerosis","volume":"18","author":"Aliakbaryhosseinabadi","year":"2021","journal-title":"J. Neural Eng."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ofner, P., Schwarz, A., Pereira, J., Wyss, D., Wildburger, R., and M\u00fcller-Putz, G.R. (2019). Attempted Arm and Hand Movements can be Decoded from Low-Frequency EEG from Persons with Spinal Cord Injury. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-43594-9"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/86.847812","article-title":"The thought translation device (TTD) for completely paralyzed patients","volume":"8","author":"Birbaumer","year":"2000","journal-title":"IEEE Trans. Rehabil. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5","DOI":"10.2340\/16501977-0020","article-title":"Motor imagery and stroke rehabilitation: A critical discussion","volume":"39","author":"Mulder","year":"2007","journal-title":"J. Rehabil. Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2421","DOI":"10.1038\/s41467-018-04673-z","article-title":"Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke","volume":"9","author":"Biasiucci","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"041001","DOI":"10.1088\/1741-2552\/aba162","article-title":"BCI for stroke rehabilitation: Motor and beyond","volume":"17","author":"Mane","year":"2020","journal-title":"J. Neural Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1002\/acn3.51551","article-title":"Associative cued asynchronous BCI induces cortical plasticity in stroke patients","volume":"9","author":"Niazi","year":"2022","journal-title":"Ann. Clin. Transl. Neurol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1109\/TNSRE.2012.2194309","article-title":"Peripheral Electrical Stimulation Triggered by Self-Paced Detection of Motor Intention Enhances Motor Evoked Potentials","volume":"20","author":"Niazi","year":"2012","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2092","DOI":"10.1109\/TBME.2014.2313867","article-title":"A Closed-Loop Brain-Computer Interface Triggering an Active Ankle-Foot Orthosis for Inducing Cortical Neural Plasticity","volume":"61","author":"Xu","year":"2014","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Jochumsen, M., Cremoux, S., Robinault, L., Lauber, J., Arceo, J.C., Navid, M.S., Nedergaard, R.W., Rashid, U., Haavik, H., and Niazi, I.K. (2018). Investigation of Optimal Afferent Feedback Modality for Inducing Neural Plasticity with A Self-Paced Brain-Computer Interface. Sensors, 18.","DOI":"10.3390\/s18113761"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Jochumsen, M., Navid, M.S., Nedergaard, R.W., Signal, N., Rashid, U., Hassan, A., Haavik, H., Taylor, D., and Niazi, I.K. (2019). Self-Paced Online vs. Cue-Based Offline Brain\u2013Computer Interfaces for Inducing Neural Plasticity. Brain Sci., 9.","DOI":"10.3390\/brainsci9060127"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.artmed.2013.08.001","article-title":"Brain\u2013computer interface controlled gaming: Evaluation of usability by severely motor restricted end-users","volume":"59","author":"Holz","year":"2013","journal-title":"Artif. Intell. Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.artmed.2013.08.004","article-title":"Transferring brain\u2013computer interfaces beyond the laboratory: Successful application control for motor-disabled users","volume":"59","author":"Leeb","year":"2013","journal-title":"Artif. Intell. Med."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/B978-0-444-63934-9.00026-3","article-title":"Hearing the needs of clinical users","volume":"Volume 168","author":"Nijboer","year":"2020","journal-title":"Handbook of Clinical Neurology"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Jochumsen, M., Knoche, H., Kidmose, P., Kj\u00e6r, T.W., and Dinesen, B.I. (2020). Evaluation of EEG Headset Mounting for Brain-Computer Interface-Based Stroke Rehabilitation by Patients, Therapists, and Relatives. Front. Hum. Neurosci., 14.","DOI":"10.3389\/fnhum.2020.00013"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1002\/pmrj.12525","article-title":"Interprofessional Practitioners\u2019 Opinions on Features and Services for an Augmentative and Alternative Communication Brain-Computer Interface Device","volume":"13","author":"Hill","year":"2021","journal-title":"PM&R"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1007\/s11571-022-09808-z","article-title":"Human factors engineering of BCI: An evaluation for satisfaction of BCI based on motor imagery","volume":"17","author":"Lyu","year":"2023","journal-title":"Cognit. Neurodyn."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"108918","DOI":"10.1016\/j.jneumeth.2020.108918","article-title":"A comprehensive assessment of Brain Computer Interfaces: Recent trends and challenges","volume":"346","author":"Yadav","year":"2020","journal-title":"J. Neurosci. Methods"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"051002","DOI":"10.1088\/1741-2552\/acfcda","article-title":"The future of wearable EEG: A review of ear-EEG technology and its applications","volume":"20","author":"Kaongoen","year":"2023","journal-title":"J. Neural Eng."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Schalk, G., Shao, S., Xiao, K., and Wu, Z. (2023). Detection of common EEG phenomena using individual electrodes placed outside the hair. Biomed. Phys. Eng. Exp., 10.","DOI":"10.1088\/2057-1976\/ad12f9"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Jochumsen, M., Knoche, H., Kjaer, T.W., Dinesen, B., and Kidmose, P. (2020). EEG Headset Evaluation for Detection of Single-Trial Movement Intention for Brain-Computer Interfaces. Sensors, 20.","DOI":"10.3390\/s20102804"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"066010","DOI":"10.1088\/1741-2552\/abc1b6","article-title":"An investigation of in-ear sensing for motor task classification","volume":"17","author":"Wu","year":"2020","journal-title":"J. Neural Eng."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kim, Y.J., Kwak, N.S., and Lee, S.W. (2018, January 15\u201317). Classification of motor imagery for Ear-EEG based Brain-Computer Interface. Proceedings of the 2018 6th International Conference on Brain-Computer Interface (BCI), High1 Resort, Gangwon, Republic of Korea.","DOI":"10.1109\/IWW-BCI.2018.8311517"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1109\/TNSRE.2022.3157959","article-title":"Feature and Classification Analysis for Detection and Classification of Tongue Movements from Single-Trial Pre-Movement EEG","volume":"30","author":"Johansson","year":"2022","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.1038\/s41593-023-01346-z","article-title":"A motor association area in the depths of the central sulcus","volume":"26","author":"Jensen","year":"2023","journal-title":"Nat. Neurosci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1109\/TNSRE.2006.875642","article-title":"The BCI competition III: Validating alternative approaches to actual BCI problems","volume":"14","author":"Blankertz","year":"2006","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"046036","DOI":"10.1088\/1741-2552\/ad6189","article-title":"Single-trial movement intention detection estimation in patients with Parkinson\u2019s disease: A movement-related cortical potential study","volume":"21","author":"Jochumsen","year":"2024","journal-title":"J. Neural Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"056015","DOI":"10.1088\/1741-2560\/10\/5\/056015","article-title":"Detection and classification of movement-related cortical potentials associated with task force and speed","volume":"10","author":"Jochumsen","year":"2013","journal-title":"J. Neural Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1669","DOI":"10.1113\/jphysiol.2011.222851","article-title":"Precise temporal association between cortical potentials evoked by motor imagination and afference induces cortical plasticity","volume":"590","author":"Kristensen","year":"2012","journal-title":"J. Physiol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"025004","DOI":"10.1088\/1741-2560\/8\/2\/025004","article-title":"Using brain\u2014Computer interfaces to induce neural plasticity and restore function","volume":"8","author":"Mattia","year":"2011","journal-title":"J. Neural Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"031005","DOI":"10.1088\/1741-2552\/aab2f2","article-title":"A review of classification algorithms for EEG-based brain\u2013computer interfaces: A 10 year update","volume":"15","author":"Lotte","year":"2018","journal-title":"J. Neural Eng."},{"key":"ref_36","first-page":"52","article-title":"Better than random? A closer look on BCI results","volume":"10","author":"Scherer","year":"2008","journal-title":"Int. J. Bioelectromagn."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Pacharra, M., Debener, S., and Wascher, E. (2017). Concealed Around-the-Ear EEG Captures Cognitive Processing in a Visual Simon Task. Front. Hum. Neurosci., 11.","DOI":"10.3389\/fnhum.2017.00290"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Xing, X., Wang, Y., Pei, W., Guo, X., Liu, Z., Wang, F., Ming, G., Zhao, H., Gui, Q., and Chen, H. (2018). A High-Speed SSVEP-Based BCI Using Dry EEG Electrodes. Sci. Rep., 8.","DOI":"10.1038\/s41598-018-32283-8"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Borr\u00e0s, M., Romero, S., Rojas-Mart\u00ednez, M., Serna, L.Y., and Ma\u00f1anas, M.A. (2023, January 24\u201327). Spinal Cord Injury Patients Exhibit Changes in Motor-Related Activity and Topographic Distribution. Proceedings of the 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Sydney, Australia. ISSN 2694-0604.","DOI":"10.1109\/EMBC40787.2023.10340794"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"035011","DOI":"10.1088\/1741-2560\/11\/3\/035011","article-title":"Motor imagery-induced EEG patterns in individuals with spinal cord injury and their impact on brain\u2014Computer interface accuracy","volume":"11","author":"Daly","year":"2014","journal-title":"J. Neural Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.neulet.2010.10.072","article-title":"Event-related desynchronization of sensorimotor EEG rhythms in hemiparetic patients with acute stroke","volume":"488","author":"Conradi","year":"2011","journal-title":"Neurosci. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"056001","DOI":"10.1088\/1741-2552\/ab20e5","article-title":"Continuous 2D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch","volume":"16","author":"Xu","year":"2019","journal-title":"J. Neural Eng."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"056003","DOI":"10.1088\/1741-2560\/12\/5\/056003","article-title":"Comparison of spatial filters and features for the detection and classification of movement-related cortical potentials in healthy individuals and stroke patients","volume":"12","author":"Jochumsen","year":"2015","journal-title":"J. Neural Eng."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"056013","DOI":"10.1088\/1741-2560\/12\/5\/056013","article-title":"Detecting and classifying movement-related cortical potentials associated with hand movements in healthy subjects and stroke patients from single-electrode, single-trial EEG","volume":"12","author":"Jochumsen","year":"2015","journal-title":"J. Neural Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"15295","DOI":"10.1109\/ACCESS.2021.3052656","article-title":"EEGNet with Ensemble Learning to Improve the Cross-Session Classification of SSVEP Based BCI From Ear-EEG","volume":"9","author":"Zhu","year":"2021","journal-title":"IEEE Access"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.jneumeth.2012.06.022","article-title":"A hybrid ERD\/SSVEP BCI for continuous simultaneous two dimensional cursor control","volume":"209","author":"Allison","year":"2012","journal-title":"J. Neurosci. Methods"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Karimi, F., Kofman, J., Mrachacz-Kersting, N., Farina, D., and Jiang, N. (2017). Detection of Movement Related Cortical Potentials from EEG Using Constrained ICA for Brain-Computer Interface Applications. Front. Neurosci., 11.","DOI":"10.3389\/fnins.2017.00356"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/18\/6004\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:57:40Z","timestamp":1760111860000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/18\/6004"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,17]]},"references-count":47,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2024,9]]}},"alternative-id":["s24186004"],"URL":"https:\/\/doi.org\/10.3390\/s24186004","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,17]]}}}