Tommi Karkkainen

Professor

University of Jyväskylä

Finland

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About

Professor Tommi Karkkainen is a faculty member at the University of Jyväskylä in Finland. His research interests include EEG-based seizure prediction, the role of virtual reality and video technology in education, and the integration of serious games in science and mathematics education. He has recently published articles addressing various innovative strategies in educational technology and epilepsy research.

Articles (14)

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2025

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2022

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2021

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2021

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2020

Collaborators (9)

Mihaly Szerovay

Professor of Practice, Research & Development in Football

University of Jyväskylä

FINLAND

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Mirka Saarela

Assistant Professor (Tenure Track)

University of Jyväskylä

FINLAND

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Päivikki Jääskelä

Adjunct professor

University of Jyväskylä

FINLAND

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Raija Hämäläinen

Professor

University of Jyväskylä

FINLAND

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Ari Tuhkala

University lecturer

University of Jyväskylä

FINLAND

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Paavo Nieminen

Senior Lecturer

University of Jyväskylä

FINLAND

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Sami Äyrämö

University of Jyväskylä

FINLAND

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Joni Lämsä

Postdoctoral Researcher

University of Oulu

FINLAND

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Emilia Lampi

University of Jyväskylä

FINLAND

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Tommi Karkkainen

Research Interests

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About

Articles (14)

EEG-Based Seizure Onset Detection of Frontal and Temporal Lobe Epilepsies Using 1DCNN

The Role of VR in Education: A Two-Phase Review of Umbrella Reviews and Recent Primary Studies

The Role of Video Technology in Football Coaching: An Integrative Review

The interconnection between evaluated and self-assessed performance in full flight simulator training

Serious games in Science and Mathematics Education: a scoping umbrella review

Combination of Channel Reordering Strategy and Dual CNN-LSTM for Epileptic Seizure Prediction Using Three iEEG Datasets

The Finnish Version of the Affinity for Technology Interaction (ATI) Scale: Psychometric Properties and an Examination of Gender Differences

Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators

Measuring self‐regulated learning in a junior high school mathematics classroom: Combining aptitude and event measures in digital learning materials

Channel Increment Strategy-Based 1D Convolutional Neural Networks for Seizure Prediction Using Intracranial EEG

Toolbox for Distance Estimation and Cluster Validation on Data With Missing Values

Explainable Student Agency Analytics

Detection of developmental dyslexia with machine learning using eye movement data

Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?

Collaborators (9)

Mihaly Szerovay

Mirka Saarela

Päivikki Jääskelä

Raija Hämäläinen

Ari Tuhkala

Paavo Nieminen

Sami Äyrämö

Joni Lämsä

Emilia Lampi

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