kenniscentrum faculteit Digitale Media & Creatieve Industrie
mw. S.M.B. Robben (Saskia)
Onderzoeker Zorg en nieuwe technologie (Care4Balance) en hoofddocent Learning Community 'Applied AI'Saskia Robben werkt bij het lectoraat Digital Life als onderzoeker op het gebied van zorg en (nieuwe) technologie.
Robben werkt momenteel voornamelijk voor de projecten www.health-lab.nl en www.care4balance.eu/. Haar onderzoek richt zich op het ontwikkelen van analysemethoden voor het meten van gezondheid met omgevingssensoren bij mensen thuis. Ook heeft ze zich beziggehouden met interfaces die de sensordata tonen aan verschillende gebruikersgroepen. Daarnaast was ze betrokken bij het oprichten van de minor Zorgtechnologie.
Robben rondde in Nijmegen de studie Kunstmatige Intelligentie/Cognitiewetenschap af, waar ze zich op problemen in het zorgdomein richtte. Haar bachelorproject was op het gebied van Bayesiaanse netwerken voor borstkankerscreening en haar masterproject bij TNO op het gebied van sociale robotica voor kinderen met diabetes.
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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. Poster session presented at EU Falls Festival 2018, Manchester, United Kingdom.
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Towards an accessible pre-screening tool for fall risk assessment
de Vrijer, A., & Robben, S. M. B. (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.
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BRAVO Annotation Tool
Robben, S. M. B. (Author). (2018). BRAVO Annotation Tool. Software
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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.
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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.
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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
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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
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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
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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.
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Care4Balance Report on final evaluation Care4Balance prototype
Wiggers, P., Robben, S. M. B., Coppens, P., Versteeg, L., Wüthrich, M., Andrushevich, A., Jacobs, J. D., & Nemhe , Z. (2015). Care4Balance Report on final evaluation Care4Balance prototype. iMinds.
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How are you doing? Enabling older adults to enrich sensor data with subjective input
Kanis, M., Robben, S. M. B., & Kröse, B. J. A. (2015). How are you doing? Enabling older adults to enrich sensor data with subjective input. In A. Ali Salah, B. Kröse, & D. J. Cook (Eds.), Human Behavior Understanding: 6th International Workshop (pp. 39-51). Springer. https://doi.org/10.1007/978-3-319-24195-1_4
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Managing flexible care with a context aware system for ageing-in-place
Robben, S. M. B., Bosch, L. B. J., Wiggers, P., Decancq, J., & Kanis, M. (2015). Managing flexible care with a context aware system for ageing-in-place. In B. Arnrich (Ed.), Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare
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Managing flexible care with a context aware system for ageing-In-place
Robben, S. M. B., Bosch, L. B. J., Decancq, J., Kanis, A. M., & Wiggers, P. (2015). Managing flexible care with a context aware system for ageing-In-place. EAI Endorsed Transactions on Context-aware Systems and Applications, 15(5), 338-341.
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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
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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)
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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.
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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.
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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
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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
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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.
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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).
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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.
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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.
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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.
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Visualizing ambient user experiences
Kanis, M., Robben, S., Kröse, B., & Veenstra, M. (2012). Visualizing ambient user experiences: any how. Association for Computing Machinery.
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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.