At-home sleep monitoring using generic ear-EEG

Autor: Yousef R. Tabar, Kaare B. Mikkelsen, Nelly Shenton, Simon L. Kappel, Astrid R. Bertelsen, Reza Nikbakht, Hans O. Toft, Chris H. Henriksen, Martin C. Hemmsen, Mike L. Rank, Marit Otto, Preben Kidmose

Publikováno v: Frontiers in Neuroscience, Vol 17 (2023)

IntroductionA device comprising two generic earpieces with embedded dry electrodes for ear-centered electroencephalography (ear-EEG) was developed. The objective was to provide ear-EEG based sleep monitoring to a wide range of the population without

Externí odkaz: https://doaj.org/article/b6488db70fdc43f2958d790023e9a0f6

Ear-EEG Forward Models: Improved Head-Models for Ear-EEG

Autor: Simon L. Kappel, Scott Makeig, Preben Kidmose

Publikováno v: Frontiers in Neuroscience, Vol 13 (2019)

Computational models for mapping electrical sources in the brain to potentials on the scalp have been widely explored. However, current models do not describe the external ear anatomy well, and is therefore not suitable for ear-EEG recordings. Here w

Externí odkaz: https://doaj.org/article/e95892d6228c4c9e95dcf50bcf736e59

Characterization of Dry-Contact EEG Electrodes and an Empirical Comparison of Ag/AgCl and IrO

Autor: Simon L, Kappel, Preben, Kidmose

Publikováno v: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2022

Dry-contact electrodes are increasingly being used for EEG recordings in both research studies and consumer products. They are more user-friendly and better suited for long-term recordings. However, dry-contact electrodes also bring challenges with r

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::0e36ca35122ac79978bdc62bcfb352f9
https://pubmed.ncbi.nlm.nih.gov/36086317

Decoding of Hand Gestures from Electrocorticography with LSTM Based Deep Neural Network

Autor: Jathurshan Pradeepkumar, Mithunjha Anandakumar, Vinith Kugathasan, Thilina D. Lalitharatne, Anjula C. De Silva, Simon L. Kappel

Publikováno v: Pradeepkumar, J, Anandakumar, M, Kugathasan, V, Lalitharatne, T D, De Silva, A C & Kappel, S L 2021, Decoding of Hand Gestures from Electrocorticography with LSTM Based Deep Neural Network . in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 . Institute of Electrical and Electronics Engineers Inc., Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 420-423, 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021, Virtual, Online, Mexico, 01/11/2021 . https://doi.org/10.1109/EMBC46164.2021.9630958

Hand gesture decoding is a key component of controlling prosthesis in the area of Brain Computer Interface (BCI). This study is concerned with classification of hand gestures, based on Electrocorticography (ECoG) recordings. Recent studies have utili

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11517bb19b099c506635a371a4d4887c
https://pubmed.ncbi.nlm.nih.gov/34891323

Dynamic navicular motion measured using a stretch sensor is different between walking and running, and between over‐ground and treadmill conditions

Autor: Christian J Barton, Simon L Kappel, Peter Ahrendt, Ole Simonsen, Michael S Rathleff

Publikováno v: Journal of Foot and Ankle Research, Vol 8, Iss 1, Pp n/a-n/a (2015)

Abstract Background Non‐invasive evaluation of in‐shoe foot motion has traditionally been difficult. Recently a novel ‘stretch‐sensor’ was proposed as an easy and reliable method to measure dynamic foot (navicular) motion. Further validatio

Externí odkaz: https://doaj.org/article/5f2a16a46d5d4e4d8c8ad187e9b19a02