P. Kidmose

Publications
Influence

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

D. Liu, M. Abu-Khalaf, +57 authors D. Xu
Computer Science
2015

We propose a directional deep embedding and appearance learning (DDEAL) method, which is free of the online fine-tuning process, for fast VOS. Expand

The In-the-Ear Recording Concept: User-Centered and Wearable Brain Monitoring

D. Looney, P. Kidmose, +4 authors D. Mandic
Engineering, Medicine
IEEE Pulse
12 December 2012

The integration of brain monitoring based on electroencephalography (EEG) into everyday life has been hindered by the limited portability and long setup time of current wearable systems as well as by… Expand

In-Ear EEG From Viscoelastic Generic Earpieces: Robust and Unobtrusive 24/7 Monitoring

V. Goverdovsky, D. Looney, P. Kidmose, D. Mandic
Engineering
IEEE Sensors Journal
2016

We introduce a novel in-ear sensor which satisfies key design requirements for wearable electroencephalography (EEG)-it is discreet, unobtrusive, and capable of capturing high-quality brain activity… Expand

A Study of Evoked Potentials From Ear-EEG

P. Kidmose, D. Looney, M. Ungstrup, M. L. Rank, D. Mandic
Psychology, Computer Science
IEEE Transactions on Biomedical Engineering
29 May 2013

A method for brain monitoring based on measuring the electroencephalogram (EEG) from electrodes placed in-the-ear (ear- EEG) was recently proposed. Expand

Velocity and Directionality of the Electrohysterographic Signal Propagation

Lasse Lange, Anders Vaeggemose, P. Kidmose, Eva Mikkelsen, N. Uldbjerg, P. Johansen
Physics, Medicine
PloS one
21 January 2014

Objective The initiation of treatment for women with threatening preterm labor requires effective distinction between true and false labor. The electrohysterogram (EHG) has shown great promise in… Expand

EEG Recorded from the Ear: Characterizing the Ear-EEG Method

K. Mikkelsen, S. L. Kappel, D. Mandic, P. Kidmose
Psychology, Medicine
Front. Neurosci.
18 November 2015

Highlights Auditory middle and late latency responses can be recorded reliably from ear-EEG. For sources close to the ear, ear-EEG has the same signal-to-noise-ratio as scalp. Ear-EEG is an excellent… Expand

Dry-Contact Electrode Ear-EEG

S. L. Kappel, M. L. Rank, H. Toft, Mikael Andersen, P. Kidmose
Computer Science, Medicine
IEEE Transactions on Biomedical Engineering
2019

Ear-EEG is a noninvasive and discreet way of recording EEG, and has the potential to be used for long-term brain monitoring in real-life environments. Expand

Ear-EEG from generic earpieces: A feasibility study

P. Kidmose, D. Looney, L. Jochumsen, D. Mandic
Engineering, Computer Science
35th Annual International Conference of the IEEE…
3 July 2013

We introduce an ear-EEG recording device based on generic earpieces which meets key patient needs (discreet, unobstrusive, user-friendly, robust) and that is low-cost and suitable for off-the-shelf use; thus promising great advantages for healthcare applications. Expand

An in-the-ear platform for recording electroencephalogram

D. Looney, C. Park, +4 authors D. Mandic
Engineering, Computer Science
Annual International Conference of the IEEE…
1 December 2011

We introduce a novel approach to brain monitoring based on electroencephalogram (EEG) recordings from within the ear canal. Expand

Automatic sleep staging using ear-EEG

K. Mikkelsen, David Bové Villadsen, M. Otto, P. Kidmose
Medicine
Biomedical engineering online
19 September 2017

This study shows that automatic sleep staging based on ear-EEG can classify sleep stages with a level of accuracy that makes it relevant for both scientific and clinical sleep assessment. Expand

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