Publications

2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005

2024

  • C. DeSmet and D. Cook HydraGAN: A cooperative agent model for multi-objective data generation. ACM Transactions on Intelligent Systems and Technology, to appear.
  • C. Luna, D. Cook, and M. Schmitter-Edgecombe. But will they use it? Predictors of adoption of an electronic memory aid in individuals with amnestic mild cognitive impairment. Neuropsychology, to appear.
  • M. Schmitter-Edgecombe, C. Luna, S. Dai, and D. Cook. Predicting daily cognition and lifestyle behaviors for older adults using smart home data and Ecological Momentary Assessment. The Clinical Neuropsychologist, to appear.
  • S. Pimento, H. Agarwal, B. Minor, S. Karia, D. Cook, M. Schmitter-Edgecombe, S. Farias, R. Lorabi, and A. Weakley. Interactive-Wear: An intelligent watch application to aid memory for intentions and everyday functioning in older adults with cognitive impairments. IEEE International Conference on AI for Medicine, Health, and Care, 2024.
  • J. Nie, M. Schmitter-Edgecombe, and D. Cook. Speech analysis in older adults for neuropsychological status prediction. International Neuropsychological Society, 2024.

2023

  • G. Wilson, J. Doppa, and D. Cook. CALDA: Improving multi-source time series domain adaptation with contrastive adversarial learning. IEEE Transactions on Pattern Analysis and Machine Learning, 45(12):14208-14221, 2023.
  • T. Wang, T. Fischer, and D. Cook. The indoor predictability of human mobility. IEEE Transactions on Emerging Topics in Computing, 11(1):182-193, 2023.
  • K. Wuestney, B. Lin, D. Cook, and R. Fritz. Modeling human frailty with a smart home-based approximation of entropy. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 2023.
  • C. Luna, S. Dai, S. Farias, D. Cook, and M. Schmitter-Edgecombe. Ecological momentary assessment of the fluctuations in cognitive performance and contextual states of commuity-dwelling older adults. Journal of the International Neuropsychological Society, 29(s1):483-484, 2023.
  • D. Cook, L. Wiese, and M. Schmitter-Edgecombe. Testing the feasibility of tracking behavior and physiology patterns using wearable technology to detect potential cognitive risk among rural, multicultural older adults. AAIC, 2023.
  • L. Wiese, I. Williams, J. Holt, C. Magzamen, L. Besser, J. Park, D. Mitsova, and D. Cook. Cane, muck, and community connections: Soil and air matters. Southern Gerontological Society Annual Scientific Conference, 2023.
  • P. Seegmiller, J. Gatto, M. Basak, D. Cook, H. Ghasemzadeh, J. Stankovic, and S. Preum. The scope of in-context learning for the extraction of medical temporal constraints. International Workshop on Health Natural Language Processing, 2023.

2022

  • T. Wang and D. Cook. Multi-person activity recognition in continuously monitored smart homes. IEEE Transactions on Emerging Topics in Computing, 10(2):1130-1141, 2022.
  • M. Wilson, S. Fritz, M. Finlay, and D. Cook. Piloting smart home sensors to detect overnight respiratory and withdrawal symptoms in adults prescribed opioids. Pain Management Nursing, 12(11), 2022.
  • B. Thomas, L. Holder, and D. Cook. Automated cognitive health assessment using partially-complete time series sensor data. Methods of Information in Medicine, 61(3/4):99-110, 2022.
  • G. Sprint, M. Schmitter-Edgecombe, L. Holder, and D. Cook. Multimodal fusion of smart home and text-based behavior markers for clinical assessment prediction. ACM Transactions on Computing for Healthcare, 3(4):1-25, 2022.
  • A. Ghods and D. Cook. PIP: Pictorial Interpretable Prototype learning for time series classification. IEEE Computational Intelligence, 2:34-45, 2022.
  • S. Mirzadeh, A. Arefeen, J. Ardo, R. Fallahzadeh, B. Minor, J. Lee, J. Hildebrand, D. Cook, H. Ghasemzadeh, and L. Evangelista. Use of machine learning to predict medication adherence in individuals at risk for atherosclerotic cardiovascular disease. Smart Health, 2022.
  • D. Cook, M. Strickland, and M. Schmitter-Edgecombe. Detecting smartwatch-based behavior change in response to a multi-domain brain health intervention. ACM Transactions on Computing for Healthcare, 3(3):1-18, 2022.
  • S. Fritz, K. Wuestney, G. Dermody, and D. Cook. Nurse-in-the-loop smart home detection of health events associated with diagnosed chronic conditions: A case-event series. International Journal of Nursing Studies Advances, 4:100081, 2022.
  • E. Ashari, N. Chaytor, D. Cook, and H. Ghasemzadeh. Memory-aware active learning in mobile sensing systems. IEEE Transactions on Mobile Computing, 21(1):181-195, 2022.
  • M. Schmitter-Edgecombe and D. Cook. Partnering a compensatory application with activity-aware prompting to improve use in individuals with amnestic mild cognitive impairment: A randomized controlled pilot clinical trial. Journal of Alzheimer's Disease, 85(1):73-90, 2022.
  • G. Wilson, J. Doppa, and D. Cook. Domain adaptation under behavioral and temporal shifts for natural time series mobile activity recognition. SIGKDD Workshop on Mining and Learning from Time Series, 2022.
  • J. Briscoe, A. Gebremedhin, L. Holder, and D. Cook. Adversarial creation of a smart home testbed for novelty detection. AAAI Spring Symposium on Designing AI for Open Worlds, 2022.
  • K. Wuestney, J. Ramirez, D. Cook, and R. Fritz. Smart home data visualization for proactive health monitoring of community dwelling older adults. Gerontological Society of America 2022 Annual Scientific Meeting, 2022.

2021

2020

2019

2018

  • D. Cook, M. Schmitter-Edgecombe, L. Jonsson, and A. Morant. Technology-enabled assessment of functional health. IEEE Reviews on Biomedical Engineering, 12:319-332, 2018.
  • D. Weeks, G. Sprint. J. Dahmen, A. La Fleur, and D. Cook. Implementing wearable sensors for continuous assessment of daytime heart rate response in inpatient rehabilitation. Telemedicine and e-Health, 24:1014-1020, 2018.
  • A. Alberdi, A. Weakley, A. Goenaga, M. Schmitter-Edgecombe, and D. Cook. Automatic assessment of functional health decline in older adults based on smart home data. Journal of Biomedical Informatics, 18:119-130, 2018.
  • D. Cook, G. Sprint, R. Fritz, and G. Duncan. Using smart city technology to make healthcare smarter. Proceedings of the IEEE, 106(4):708-722, 2018.
  • A. Alberdi, A. Weakley, M. Schmitter-Edgecombe, D. Cook, A. Aztiria, A. Basarab, and M. Barrenechea. Smart home-based prediction of multi-domain symptoms related to Alzheimer's disease. Journal of Biomedical and Health Informatics, 22(6):1720-1731, 2018.
  • J. Dahmen, B. Minor, D. Cook, T. Vo, and M. Schmitter-Edgecombe. Design of a smart home-driven digital memory notebook to support self-management of activities for older adults. Gerontechnology, 17(2):113-123, 2018.
  • A. Mokhtari, S. Aminikhanghahi, Q. Zhang, and D. Cook. Fall detection in smart home sensors using UWB sensors and unsupervised change detection. Journal of Reliable Intelligent Environments, 4(3):131-139, 2018.
  • W. M. Kirk, M. Fuchs, Y. Huangfu, N. Lima, P. O'Keeffe, B. Lin, T. Jobson, S. Pressley, V. Walden, D. Cook, and B. Lamb. Indoor air quality and wildfire smoke impacts in the Pacific Northwest. Science and Technology for the Built Environment, 24(2), 2018.
  • A. Musser, B. Lin, D. Cook, B. Jobson, M. Kirk, N. Lima, P. O'Keeffe, S. Pressley, V. Walden, Y. Huangfu, and B. Lamb. Indoor air toxic gases levels in a net-zero energy house under multiple venilation system settings. Conference of the International Society of Indoor Air Quality and Climate, 2018.
  • A. Musser, B. Lin, D. Cook, B. Jobson, M. Kirk, N. Lima, P. O'Keeffe, S. Pressley, V. Walden, Y. Huangfu, and B. Lamb. Simulations of indoor air quality based on future climate conditions. Conference of the International Society of Indoor Air Quality and Climate, 2018.
  • A. Musser, B. Lin, D. Cook, B. Jobson, M. Kirk, N. Lima, P. O'Keeffe, S. Pressley, V. Walden, Y. Huangfu, and B. Lamb. The major role of temperature on indoor concentrations of air toxic VOCs in 9 houses based on in-situ high time resolution measurements. Conference of the International Society of Indoor Air Quality and Climate, 2018.

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

  • D. Cook. Health monitoring and assistance to support aging in place.
    Journal of Universal Computer Science, 12(1), pages 15-29, 2006.
  • C.-C Tseng and D. Cook. Mining from time series human movement data. Proceedings of the Conference on Systems, Man, and
    Cybernetics, 2006.
  • V. Jakkula, M. Youngblood, and D. Cook. Identification of lifestyle behavior patterns with prediction of the happiness of an inhabitant in a smart home. Proceedings of the AAAI Workshop on Computational Aesthetics, 2006.
  • G. Jain, D. Cook, and V. Jakkula.
    Monitoring health by detecting drifts and outliers for a smart environment inhabitant. Proceedings of the International Conference On Smart Homes and Health Telematics, 2006.
  • S. Das and D. Cook. Designing and modeling smart environments.
    Proceedings of the Workshop on Autonomic Computing and Communications, 2006.
  • D. Brezeale and D. Cook. Using closed caption and visual features to classify movies by genre. Proceedings of the KDD/MDM Workshop, 2006.
  • D. Cook, G. M. Youngblood, and G. Jain.
    Algorithms for smart spaces. Technology for Aging,
    Disability and Independence: Computer and Engineering for Design and
    Applications, Wiley, 2006.
  • D. Cook, G. M. Youngblood, and S. K. Das.
    A multi-agent approach to controlling a smart environment. AI and Smart Homes, pages 165-182, Springer Verlag, 2006.
  • S. K. Das and D. Cook. Smart Home Environments: A paradigm based on learning and prediction. Wireless Mobile and Sensor Networks: Technology, Applications and Future Directions.
    (R. Shorey, A. Ananda, M. C. Chan, and W. T. Ooi, eds.),
    pages 337-356, Wiley, 2006.

2005

  • M. Youngblood, D. Cook, and L. Holder. Managing adaptive versatile environments. Journal of Pervasive and Mobile Computing, 2005.
  • M. Youngblood, D. Cook, and L. Holder. Managing adaptive versatile environments. Proceedings of the IEEE International Conference on
    Pervasive Computing and Communications, 2005.
  • S. K. Das and D. Cook.
    Designing smart environments: A paradigm based on learning and prediction. Proceedings of First International Conference on Pattern
    Recognition and Machine Intelligence (PReMI’05), Kolkata, India, Dec 18-22, 2005.
  • M. Youngblood, D. Cook, L. Holder and E. Heierman.
    Automation intelligence for the smart environment.
    Proceedings of the International Joint Conference on Artificial Intelligence, 2005.
  • M. Youngblood, L. Holder, and D. Cook.
    A learning architecture for automating the intelligent environment. Proceedings of the Conference on Innovative Applications of Artificial Intelligence, 2005.
  • S. K. Das and D. Cook. Smart home environments: A paradigm based on learning and prediction, Wireless Mobile and Sensor Networks, Wiley, 2005.