S
Stella Douka
Researcher at Aristotle University of Thessaloniki
Publications - 27
Citations - 735
Stella Douka is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Dance & Athletes. The author has an hindex of 11, co-authored 27 publications receiving 623 citations.
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Journal ArticleDOI
International Ballroom Dancing Against Neurodegeneration: A Randomized Controlled Trial in Greek Community-Dwelling Elders With Mild Cognitive impairment.
Ioulietta Lazarou,Themis Parastatidis,Anthoula Tsolaki,Mara Gkioka,Anastasios Karakostas,Stella Douka,Magda Tsolaki +6 more
TL;DR: Dance may be an important nonpharmacological approach that can benefit cognitive functions in elders with amnestic mild cognitive impairment and according to the Student t test, better performance is detected in IG in contrast with CG, which had worse performance almost in all scales.
Journal ArticleDOI
Effect of a 10-week traditional dance program on static and dynamic balance control in elderly adults.
TL;DR: Findings support the use of traditional dance as an effective means of physical activity for improving static and dynamic balance control in the elderly.
Journal ArticleDOI
Testing the role of service quality on the development of brand associations and brand loyalty
TL;DR: In this article, the authors measure brand associations in the context of a fitness club, test the influence of brand associations on the development of brand loyalty, and investigate the role of service quality.
Journal ArticleDOI
Physical and psychological benefits of a 24-week traditional dance program in breast cancer survivors.
TL;DR: Aerobic exercise with Greek traditional dances and upper body training could be an alternative choice of physical activity for breast cancer survivors, thus promoting benefits in physical function, strength and psychological condition.
Proceedings Article
Dance analysis using multiple Kinect sensors
TL;DR: In this paper, a method for body motion analysis in dance using multiple Kinect sensors is presented, which applies fusion to combine the skeletal tracking data of multiple sensors in order to solve occlusion and self-occlusion tracking problems and increase the robustness of skeletal tracking.