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Eco de Geus

Showing results (1-10 of 55) with videos related to

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Biological Psychology|November 27, 2025
Controlling heart rate variability for respiratory effects in ambulatory psychophysiological measurementsMelisa Saygin, Martin Gevonden, Eco de Geus
Neuroscience and Biobehavioral Reviews|December 8, 2009
Genetic influences on cardiovascular stress reactivityTing Wu, Harold Snieder, Eco de Geus
Psychophysiology|February 14, 2025
Speech Detection via Respiratory Inductance Plethysmography, Thoracic Impedance, Accelerometers, and Gyroscopes: A Machine Learning-Informed Comparative StudyMelisa Saygin, Myrte Schoenmakers, Martin Gevonden, et al.
Biological Psychology|May 20, 2008
Imaging the genetics of brain structure and functionEco de Geus, Terry Goldberg, Dorret I Boomsma, et al.
Psychosomatic Medicine|February 10, 2007
Genetics in psychosomatic medicine: research designs and statistical approachesJeanne M McCaffery, Harold Snieder, Yanbin Dong, et al.
Behavior Genetics|April 18, 2016
The Importance of the Prenatal Environment in Behavioral Genetics: Introduction to Special IssueValerie S Knopik, Jenae M Neiderhiser, Eco de Geus, et al.
Behavior Research Methods|May 13, 2025
Stress in action wearables database: A database of noninvasive wearable monitors with systematic technical, reliability, validity, and usability informationMyrte Schoenmakers, Melisa Saygin, Magdalena Sikora, et al.
International Journal of Epidemiology|March 11, 2020
Empirical comparisons of multiple Mendelian randomization approaches in the presence of assortative matingCamelia C Minică, Dorret I Boomsma, Conor V Dolan, et al.
Behavior Genetics|June 9, 2018
Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin DesignCamelia C Minică, Conor V Dolan, Dorret I Boomsma, et al.
Journal of Medical Internet Research|April 7, 2026
Electrocardiogram-Based Mental Stress Detection Amid Everyday Activities Using Machine Learning: Model Development and Validation StudyBuelent Uendes, Alex Antonides, Sjors van de Ven, et al.
Pageof 6

Showing results (1-10 of 55) with videos related to

Sort By:
Pageof 6
Biological Psychology|November 27, 2025
Controlling heart rate variability for respiratory effects in ambulatory psychophysiological measurementsMelisa Saygin, Martin Gevonden, Eco de Geus
Neuroscience and Biobehavioral Reviews|December 8, 2009
Genetic influences on cardiovascular stress reactivityTing Wu, Harold Snieder, Eco de Geus
Psychophysiology|February 14, 2025
Speech Detection via Respiratory Inductance Plethysmography, Thoracic Impedance, Accelerometers, and Gyroscopes: A Machine Learning-Informed Comparative StudyMelisa Saygin, Myrte Schoenmakers, Martin Gevonden, et al.
Biological Psychology|May 20, 2008
Imaging the genetics of brain structure and functionEco de Geus, Terry Goldberg, Dorret I Boomsma, et al.
Psychosomatic Medicine|February 10, 2007
Genetics in psychosomatic medicine: research designs and statistical approachesJeanne M McCaffery, Harold Snieder, Yanbin Dong, et al.
Behavior Genetics|April 18, 2016
The Importance of the Prenatal Environment in Behavioral Genetics: Introduction to Special IssueValerie S Knopik, Jenae M Neiderhiser, Eco de Geus, et al.
Behavior Research Methods|May 13, 2025
Stress in action wearables database: A database of noninvasive wearable monitors with systematic technical, reliability, validity, and usability informationMyrte Schoenmakers, Melisa Saygin, Magdalena Sikora, et al.
International Journal of Epidemiology|March 11, 2020
Empirical comparisons of multiple Mendelian randomization approaches in the presence of assortative matingCamelia C Minică, Dorret I Boomsma, Conor V Dolan, et al.
Behavior Genetics|June 9, 2018
Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin DesignCamelia C Minică, Conor V Dolan, Dorret I Boomsma, et al.
Journal of Medical Internet Research|April 7, 2026
Electrocardiogram-Based Mental Stress Detection Amid Everyday Activities Using Machine Learning: Model Development and Validation StudyBuelent Uendes, Alex Antonides, Sjors van de Ven, et al.
Pageof 6