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  S.M.B. Robben (Saskia)

Telephone:
0621157049
Email:
s.m.b.robben@hva.nl
Work address:
Theo Thijssenhuis, Wibautstraat 2-4 1091 GM Amsterdam
Postal address:
Postbus 2728,1000 CS Amsterdam
Room number:
04A27
Personal website:
Website Kenniscentrum FDMCI
Go to Research database

Saskia Robben, MSc. is onderzoeker en projectleider bij het lectoraat Digital Life en doet onderzoek op het gebied van zorg en (nieuwe) technologie.

Onderzoek

Haar onderzoek richt zich op het ontwikkelen van analysemethoden voor het meten van gezondheid met omgevingssensoren of draagbare sensoren bij mensen thuis. Ook heeft ze zich beziggehouden met het ontwikkelen van innovatieve interfaces die sensor data tonen aan verschillende gebruikersgroepen.

Motivatie

Ze vind het belangrijk dat ze haar kennis van Kunstmatige Intelligentie in kan zetten voor een betere wereld. Ze zoekt daarom altijd projecten die te maken hebben met het verbeteren van de zorg, en daarnaast geeft ze haar kennis als docent bij HBO-ICT ook mee aan een nieuwe generatie studenten.

Huidige projecten

Saskia Robben werkt op dit moment aan verschillende onderzoeksprojecten zoals het project De Interactieve Woonkamer (Guiding Environment) in samenwerking met onder andere de Hogeschool Arnhem Nijmegen. In dat project is samen met eindgebruikers een prototype ontwikkeld van een interactieve woonkamer voor het ondersteunen van thuiswonende mensen met dementie bij hun dagstructuur. Dit prototype is onder andere geïnstalleerd in de Empathische Woning.

Huidige onderwijsactiviteiten

Als docent bij HBO-ICT was ze betrokken bij het oprichten van de minor Zorgtechnologie. De laatste jaren doceert ze voornamelijk over AI-algoritmes en tools voor data-analyse bij het semester Big Data en de minor Applied Artificial Intelligence.

Opleiding

Ze is in 2011 afgestudeerd aan de Radboud Universiteit Nijmegen in de Kunstmatige Intelligentie / Cognitiewetenschap. Haar bachelorproject was gericht op Bayesiaanse netwerken voor borstkankerscreening en haar masterproject bij TNO op de ontwikkeling van sociale robotica voor kinderen met diabetes.

Voor een overzicht van publicaties kijk op: http://digitallife.nl/team/saskia-robben

  • Towards Responsible AI Code Development: A Six-Value Process Model for Junior and Novice AI Programmers
    van Kersbergen, R., & Robben, S. (2023). Towards Responsible AI Code Development: A Six-Value Process Model for Junior and Novice AI Programmers. Paper presented at BNAIC 2023, Delft, Netherlands. https://bnaic2023.tudelft.nl/static/media/BNAICBENELEARN_2023_paper_52.078bd4485b9ebe57325b.pdf
  • A co-creation approach to implementing eHealth applications in care organizations: lessons learned from multiple cases
    Robben, S., Oey, M., Pol, M., Muiser, S., Melis, P., & Ben Allouch, S. (2022). A co-creation approach to implementing eHealth applications in care organizations: lessons learned from multiple cases. Poster session presented at 5th UK Implementation Science Research Conference, United Kingdom.
  • Developing an Intelligent Environment to Support People with Early-Stage Dementia: from User-Needs to a Real-Life Prototype
    Grave, A., Robben, S., Oey, M., Ben Allouch, S., & Mohammadi, M. (2022). Developing an Intelligent Environment to Support People with Early-Stage Dementia: from User-Needs to a Real-Life Prototype. Applied Human Informatics: Open Journal of the Academy of Human Informatics, 4(1), 1-18. https://doi.org/10.14865/ahi.4.1.1
  • Routekaart voor implementatie van eHealth toepassingen in de zorg
    Muiser, S., Melis, P. J. J. M., Oey, M. A., & Robben, S. M. B. (2022). Routekaart voor implementatie van eHealth toepassingen in de zorg.
  • Beslisondersteuning bij Oprichten Applied AI Lab
    Robben, S. M. B. (2021). Beslisondersteuning bij Oprichten Applied AI Lab: Adviesrapport kansen Applied Artificial Intelligence (AAI) in de faculteiten Gezondheid & Bewegen, Sport en Voeding.
  • Requirement elicitation and prototype development of an intelligent environment to support people with early dementia
    Grave, A., Robben, S., Oey, M., Ben Allouch, S., & Mohammadi, M. (2021). Requirement elicitation and prototype development of an intelligent environment to support people with early dementia. In 2021 17th International Conference on Intelligent Environments, IE 2021 - Proceedings Article 9486462 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IE51775.2021.9486462
  • Movement registration and analysis for fall risk assessment in the hospital: lessons from an observational pilot study
    Robben, S. M. B., Ploegmakers, K. J., de Vrijer, A., & van der Velde, N. (2018). Movement registration and analysis for fall risk assessment in the hospital: lessons from an observational pilot study. 63-63. Poster session presented at EU Falls Festival 2018, Manchester, United Kingdom.
  • Towards an accessible pre-screening tool for fall risk assessment
    de Vrijer, A., & Robben, S. (2018). Towards an accessible pre-screening tool for fall risk assessment: Automated gait analysis using a machine-learning approach. Poster session presented at EU Falls Festival 2018, Manchester, United Kingdom.
  • BRAVO Annotation Tool
    Robben, S. M. B. (2018). BRAVO Annotation Tool. Software
  • Movement registration and analysis for fall risk assessment in the hospital: observational pilot study
    Robben, S. M. B., Ploegmakers, K. J., & van der Velde, N. (2017). Movement registration and analysis for fall risk assessment in the hospital: observational pilot study. Poster session presented at 2nd Annual Meeting of the Amsterdam Public Health research institute, Amsterdam, Netherlands.
  • Ontwikkeling van geautomatiseerde valrisicoscreening met betaalbare technologie
    de Vrijer, A., & Robben, S. M. B. (2017). Ontwikkeling van geautomatiseerde valrisicoscreening met betaalbare technologie. Poster session presented at Landelijk Valsymposium 2017, Amsterdam, Netherlands.
  • Delta features from ambient sensor data are good predictors of change in functional health
    Robben, S., Englebienne, G., & Krose, B. (2016). Delta features from ambient sensor data are good predictors of change in functional health. IEEE Journal of Biomedical and Health Informatics, 21(4), 986-993. https://doi.org/10.1109/JBHI.2016.2593980
  • Expert knowledge for modeling functional health from sensor data
    Robben, S. M. B., Pol, M. C., Buurman, B. M., & Kröse, B. J. A. (2016). Expert knowledge for modeling functional health from sensor data. Methods of Information in Medicine, 55(6), 516-524. https://doi.org/10.3414/ME15-01-0072
  • Measuring Regularity in Daily Behavior for the Purpose of Detecting Alzheimer
    Robben, S., Nait Aicha, A., & Kröse, B. (2016). Measuring Regularity in Daily Behavior for the Purpose of Detecting Alzheimer. In Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare (pp. 97-100). Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering. https://dl.acm.org/citation.cfm?id=3021334
  • Modeling functional health with sensor data
    Robben, S. M. B. (2016). Modeling functional health with sensor data: from experts to data. Poster session presented at PervasiveHealth, Cancun, Mexico.
  • Managing Flexible Care With a Context Aware System for Ageing-In-Place
    Robben, S., Bosch, L., Wiggers, P., Decancq, J., & Kanis, M. (2015). Managing Flexible Care With a Context Aware System for Ageing-In-Place. EAI Endorsed Transactions on Context-aware Systems and Applications, 15(5), Article e1. https://doi.org/10.4108/icst.pervasivehealth.2015.259229
  • Care4Balance Report on final evaluation Care4Balance prototype
    Jacobs, A., Decancq, J., Coppens, P., Versteeg, L., Wüthrich, M., Andrushevich, A., Wiggers, P., Robben, S., & Nemhe, Z. (2015). Care4Balance Report on final evaluation Care4Balance prototype. iMinds.
  • How Are You Doing? Enabling Older Adults to Enrich Sensor Data with Subjective Input
    Kanis, M., Robben, S., & Kröse, B. (2015). How Are You Doing? Enabling Older Adults to Enrich Sensor Data with Subjective Input. In A. Ali Salah, B. J. A. Kröse, & D. J. Cook (Eds.), Proceedings of the 6th International Workshop on Human Behavior Understanding (pp. 39-51). (Lecture Notes in Computer Science; Vol. 9277). Springer. https://doi.org/10.1007/978-3-319-24195-1_4
  • Managing Flexible Care With a Context Aware System for Ageing-In-Place
    Robben, S., Bosch, L., Wiggers, P., Decancq, J., & Kanis, M. (2015). Managing Flexible Care With a Context Aware System for Ageing-In-Place. In B. Arnrich, C. Ersoy, A. Dey, K. Kunze, & N. Berthouze (Eds.), Proceedings of the 2015 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth): PervasiveHealth 2015 ICST. https://doi.org/10.4108/icst.pervasivehealth.2015.259229
  • Expert knowledge for modeling the relation between functional health and data from ambient assisted living sensor systems
    Robben, S. M. B., Pol, M., Kröse, B. J. A., & Buurman, B. M. (2014). Expert knowledge for modeling the relation between functional health and data from ambient assisted living sensor systems. Poster session presented at 10th Congress of the European Union of Geriatric Medicine Society (EUGMS) 2014
    , Rotterdam. https://www.thieme-connect.com/products/ejournals/abstract/10.3414/ME15-01-0072
  • Longitudinal ambient sensor monitoring for functional health assessments
    Robben, S. M. B., Pol, M., & Kröse, B. J. A. (2014). Longitudinal ambient sensor monitoring for functional health assessments: a case study. In UBICOMP '14 Adjunct proceedings (workshop: SmartHealthSys 2014) (pp. 1209-1216) https://doi.org/10.1145/2638728.2638812
  • Identifying and visualizing relevant deviations in longitudinal sensor patterns for care professionals
    Robben, S., Kanis, M., Kröse, B., & Boot, M. (2013). Identifying and visualizing relevant deviations in longitudinal sensor patterns for care professionals. In PervasiveHealth '13: Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering.
  • Longitudinal residential ambient monitoring
    Robben, S., & Kröse, B. (2013). Longitudinal residential ambient monitoring: correlating sensor data to functional health status. In PervasiveHealth '13: Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering.
  • Sensor monitoring in the home
    Kanis, M., Robben, S., Hagen, J., Bimmerman, A., Wagelaar, N., & Kröse, B. (2013). Sensor monitoring in the home: giving voice to elderly people. In M. Czerwinski , O. Mayora , P. Lukowicz, A. Campbell , & V. Osmani (Eds.), Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops: PervasiveHealth 2013: Venice, Italy May 5/8, 2013 IEEE Press. https://doi.org/10.4108/icst.pervasivehealth.2013.252060
  • Sensor monitoring to measure and support daily functioning for independently living older people a systematic review and road map for further development
    Pol, M. C., Poerbodipoero, S., Robben, S., Daams, J., van Hartingsveldt, M., de Vos, R., de Rooij, S. E., Kröse, B., & Buurman, B. M. (2013). Sensor monitoring to measure and support daily functioning for independently living older people a systematic review and road map for further development. Journal of the American Geriatrics Society, 61(12), 2219-2227. https://doi.org/10.1111/jgs.12563
  • How Is grandma doing?
    Robben, S., Englebienne, G., Pol, M., & Kröse, B. (2012). How Is grandma doing? predicting functional health status from binary ambient sensor data. In D. J. Cook, N. C. Krishnan, P. Rashidi, M. Skubic, & A. Mihailidis (Eds.), Artificial intelligence for gerontechnology: papers from the AAAI symposium (pp. 26-31). (AAAI Technical Report; No. FS-12-01). AAAI Press.
  • How is Grandma Doing? Prediction Functional Health Status from Binary Ambient Sensor Data.
    Robben, S. M. B., Englebienne, G., Pol, M., & Kröse, B. J. A. (2012). How is Grandma Doing? Prediction Functional Health Status from Binary Ambient Sensor Data. In How is Grandma Doing? Prediction Functional Health Status from Binary Ambient Sensor Data. (Vol. 2012-01). (AAAI Technical Report FS).
  • Living Labs as Educational Tool for Ambient Intelligence
    Robben, S., Kanis, M., Kröse, B. J. A., & Veenstra, M. (2012). Living Labs as Educational Tool for Ambient Intelligence. In Ambient Intelligence: Third International Joint Conference, AmI 2012 (Vol. 7683). (Lecture Notes in Computer Scienc). Springer Verlag.
  • Miniature play
    Kanis, M., Robben, S., & Kröse, B. J. A. (2012). Miniature play: Using an interactive dollhouse to demonstrate ambient interactions in the home. In DIS '12: Designing Interactive Systems Conference 2012 Association for Computing Machinery.
  • Reducing dementia related wandering behaviour with an interactive wall
    Robben, S., Bergman, K., Haitjema, S., Yannick, D. L., & Kröse, B. J. A. (2012). Reducing dementia related wandering behaviour with an interactive wall. In AmI 2012: Ambient Intelligence (Lecture Notes in Computer Science; Vol. 7683). Springer Verlag.
  • Visualizing ambient user experiences
    Kanis, M., Robben, S., Kröse, B., & Veenstra, M. (2012). Visualizing ambient user experiences: any how. Association for Computing Machinery.
  • Ambient monitoring from an elderly-centred design perspective
    Robben, S., Groen, J., Kanis, M., Bakkes, S., Alizadeh, S., Khalili, M., & Kröse, B. (2011). Ambient monitoring from an elderly-centred design perspective: what, who and how. In AmI'11: Proceedings of the Second international conference on Ambient Intelligence Hogeschool van Amsterdam.
Go to Research database
Go to Research database