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1.
J Clin Med ; 13(12)2024 Jun 17.
Article in English | MEDLINE | ID: mdl-38930077

ABSTRACT

(1) Background: The aim of this study was to investigate the circadian rhythms of tongue features according to the effects of physiological phases over a 24 h period. (2) Methods: Fifteen healthy participants aged 20 to 69 years were recruited. The participants did not have current chronic diseases or past diseases and had to meet the inclusion and exclusion criteria. The participants stayed at the Gil Hospital for a duration of 2 nights and 3 days. On the first day, at 18:00, they consumed their allocated portions of food and water and then completed a questionnaire. At approximately 21:00, their tongue images were acquired using a computerized tongue image acquisition system, following which they slept for 8 h, commencing at 23:00. Measurements were taken from 07:00 through 21:00 on the second day, and the final acquisition was taken at 07:00 on the following morning, resulting in a total of eight images. The circadian rhythm was authenticated and quantified utilizing the single cosinor analysis, a technique for periodic regression analysis for fitting a 24 h cosine curve. (3) Results: Cosinor analysis revealed that all tongue features were significantly related to circadian rhythm. (4) Conclusions: The results of this study may be important for considering the time of day at which the tongue is observed and tongue status is evaluated.

2.
IEEE Trans Biomed Eng ; 65(10): 2168-2177, 2018 10.
Article in English | MEDLINE | ID: mdl-29989953

ABSTRACT

OBJECTIVE: In this study, electroencephalography data of imagined words were classified using four different feature extraction approaches. Eight subjects were recruited for the recording of imagination with five different words, namely; 'go', 'back', 'left', 'right', and 'stop'.


Subject(s)
Electroencephalography/methods , Imagination/classification , Imagination/physiology , Signal Processing, Computer-Assisted , Speech/physiology , Adult , Algorithms , Broca Area/physiology , Female , Humans , Image Processing, Computer-Assisted , Male , Wernicke Area/physiology , Young Adult
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