Reinder Haakma - researchr alias

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Viewing Publication 1 - 36 from 36

2022

t linear mixed model: model formulation, identifiability and estimationMarta Regis, Alberto Brini, Nazanin Nooraee, Reinder Haakma, Edwin R. van den Heuvel. cssc, 51(5):2318-2342, 2022. [doi]

2019

Generating time-based label refinements to discover more precise process modelsNiek Tax, Emin Alasgarov, Natalia Sidorova, Reinder Haakma, Wil M. P. van der Aalst. jaise, 11(2):165-182, 2019. [doi]

2018

LocalProcessModelDiscovery: Bringing Petri Nets to the Pattern Mining WorldNiek Tax, Natalia Sidorova, Wil M. P. van der Aalst, Reinder Haakma. apn 2018: 374-384 [doi]

Mining Local Process Models with Constraints Efficiently: Applications to the Analysis of Smart Home DataNiek Tax, Natalia Sidorova, Reinder Haakma, Wil M. P. van der Aalst. intenv 2018: 56-63 [doi]

2017

Actigraphy-based sleep/wake detection for insomniacsXi Long, Pedro Fonseca, Reinder Haakma, Ronald M. Aarts. bsn 2017: 1-4 [doi]

Detection of Nocturnal Slow Wave Sleep Based on Cardiorespiratory Activity in Healthy AdultsXi Long, Pedro Fonseca, Ronald M. Aarts, Reinder Haakma, Jerome Rolink, Steffen Leonhardt. titb, 21(1):123-133, 2017. [doi]

2016

On the Reactivity of Sleep Monitoring with DiariesM. S. Goelema, M. M. Willems, Reinder Haakma, P. Markopoulos. biostec 2016: 240-247 [doi]

On Generation of Time-based Label RefinementsNiek Tax, Emin Alasgarov, Natalia Sidorova, Reinder Haakma. csp 2016: 25-36 [doi]

Event Abstraction for Process Mining Using Supervised Learning TechniquesNiek Tax, Natalia Sidorova, Reinder Haakma, Wil M. P. van der Aalst. intellisys 2018: 251-269 [doi]

Log-based Evaluation of Label Splits for Process ModelsNiek Tax, Natalia Sidorova, Reinder Haakma, Wil M. P. van der Aalst. kes 2016: 63-72 [doi]

Heuristic approaches for generating Local Process Models through log projectionsNiek Tax, Natalia Sidorova, Wil M. P. van der Aalst, Reinder Haakma. ssci 2016: 1-8 [doi]

Mining local process modelsNiek Tax, Natalia Sidorova, Reinder Haakma, Wil M. P. van der Aalst. jides, 3(2):183-196, 2016. [doi]

2015

Improving sleep/wake detection via boundary adaptation for respiratory spectral featuresXi Long, Reinder Haakma, Jerome Rolink, Pedro Fonseca, Ronald M. Aarts. embc 2015: 374-377 [doi]

Effects of Between- and Within-Subject Variability on Autonomic Cardiorespiratory Activity during Sleep and Their Limitations on Sleep Staging: A Multilevel AnalysisXi Long, Reinder Haakma, Tim R. M. Leufkens, Pedro Fonseca, Ronald M. Aarts. cin, 2015, 2015. [doi]

2014

Does Being Monitored during Sleep Affect People on a Cognitive and a Behavioral Level?M. S. Goelema, Reinder Haakma, P. Markopoulos. biostec 2014: 27-33 [doi]

Automatic detection of overnight deep sleep based on heart rate variability: A preliminary studyXi Long, Pedro Fonseca, Reinder Haakma, Jérôme Foussier, Ronald M. Aarts. embc 2014: 50-53 [doi]

Spectral Boundary Adaptation on Heart Rate Variability for Sleep and Wake ClassificationXi Long, Pedro Fonseca, Reinder Haakma, Ronald M. Aarts, Jérôme Foussier. ijait, 23(3), 2014. [doi]

Sleep and Wake Classification With Actigraphy and Respiratory Effort Using Dynamic WarpingXi Long, Pedro Fonseca, Jérôme Foussier, Reinder Haakma, Ronald M. Aarts. titb, 18(4):1272-1284, 2014. [doi]

Analyzing respiratory effort amplitude for automated sleep stage classificationXi Long, Jérôme Foussier, Pedro Fonseca, Reinder Haakma, Ronald M. Aarts. bspc, 14:197-205, 2014. [doi]

2013

Respiration amplitude analysis for REM and NREM sleep classificationXi Long, Jérôme Foussier, Pedro Fonseca, Reinder Haakma, Ronald M. Aarts. embc 2013: 5017-5020 [doi]

2012

Time-frequency analysis of heart rate variability for sleep and wake classificationXi Long, Pedro Fonseca, Reinder Haakma, Ronald M. Aarts, Jérôme Foussier. bibe 2012: 85-90 [doi]

Using dynamic time warping for sleep and wake discriminationXi Long, Pedro Fonseca, Jérôme Foussier, Reinder Haakma, Ronald M. Aarts. bhi 2012: 886-889 [doi]

2009

The theoretical foundation and validity of a component-based usability questionnaireWillem-Paul Brinkman, Reinder Haakma, Don Bouwhuis. behaviourIT, 28(2):121-137, 2009. [doi]

2008

Component-Specific Usability TestingWillem-Paul Brinkman, Reinder Haakma, Don Bouwhuis. tsmc, 38(5):1143-1155, 2008. [doi]

2007

Towards an empirical method of efficiency testing of system parts: A methodological studyWillem-Paul Brinkman, Reinder Haakma, Don Bouwhuis. iwc, 19(3):342-356, 2007. [doi]

Relation between DSIS and DSCQS for temporal and spatial video artifacts in a wireless home environmentNele Van den Ende, Lydia M. J. Meesters, Reinder Haakma. hvei 2007: [doi]

How to Improve the Production Process for interactive TV with semi-formal MethodsMatthias Rauterberg, Michel Alders, Reinder Haakma. jvrb, 4, 2007. [doi]

2004

Usability Testing of Interaction Components: Taking the Message Exchange as a Measure of UsabilityWillem-Paul Brinkman, Reinder Haakma, Don Bouwhuis. cadui 2005: 157-168

Empirical Usability Testing in a Component-Based Environment: Improving Test Efficiency with Component-Specific Usability MeasuresWillem-Paul Brinkman, Reinder Haakma, Don Bouwhuis. ehci 2005: 20-37 [doi]

2001

Usability Evaluation of Component-Based User InterfacesWillem-Paul Brinkman, Reinder Haakma, Don Bouwhuis. INTERACT 2001: 767-768

1999

Towards explaining the behaviour of novice usersReinder Haakma. ijmms, 50(6):557-570, 1999. [doi]

1996

Layered Protocols: hands-on experienceJ. H. Eggen, Reinder Haakma, Joyce H. D. M. Westerink. ijmms, 44(1):45-72, 1996. [doi]

1994

Improved efficiency through I- and E-feedback: a trackball with contextual force feedbackFrits L. Engel, Peter Goossens, Reinder Haakma. ijmms, 41(6):949-974, 1994. [doi]

1993

Layered protocols in user interfaces for consumer equipmentJ. H. Eggen, Reinder Haakma, Joyce H. D. M. Westerink. chi 1993: 165-166 [doi]

Expectations and Feedback in User-System CommunicationFrits L. Engel, Reinder Haakma. ijmms, 39(3):427-452, 1993.

1992

Contextual motor feedback in cursor controlReinder Haakma. CHI 1992: 61 [doi]

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