2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005
- C. DeSmet, C. Greeley, and D. Cook. Hydra-TS: Enhancing human activity recognition with multi-objective synthetic time series data generation. IEEE Sensors, to appear.
- C. DeSmet and D. Cook HydraGAN: A cooperative agent model for multi-objective data generation. ACM Transactions on Intelligent Systems and Technology, 15(3):1-21, 2024.
- L. Besser, L. Wiese, D. Cook, J. Holt, S. Magzamen, B. Minor, D. Mitsova, J. Park, O. Sablan, M. Tourelle, and C. Williams. Rural Roads to Cognitive Resilience (RRR): A prospective cohort study protocol. IEEE Access, 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.
- 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.
- 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, 37(8):955-965, 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.
- 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.
- D. Cook and M. Schmitter-Edgecombe. Fusing ambient and mobile sensor features into a behaviorome for predicting clinical health scores. IEEE Access, 2:65033-65043, 2021. code
- J. Dahmen and D. Cook. Indirectly-supervised anomaly detection of clinically-meaningful health events from smart home data. ACM Transactions on Intelligent Systems and Technology, 12(2):1-18, 2021.
- C. DeSmet and D. Cook. Recent developments in privacy-preserving mining of clinical data. ACM/IMS Transactions on Data Science, 2:65033-65043, 2021.
- E. Ashari, N. Chaytor, D. Cook, and H. Ghasemzadeh. Memory-aware active learning in mobile sensing systems. IEEE Transactions on Mobile Computing, to appear.
- T. Wang and D. Cook. sMRT: Multi-resident tracking in smart homes with sensor vectorization. IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear.
- N. Raghunath, M. Schmitter-Edgecombe, and D. Cook. Learning-enabled robotic assistive support for persons with memory impairment: Comparing older and younger adults' perceptions of the system. Gerontechnology, to appear.
- Y. Zhang, A. Srivastava, and D. Cook. Machine learning algorithm for activity-aware demand response considering energy savings and comfort requirements. IET Smart Grid, to appear.
- G. Sprint, D. Cook, and R. Fritz. Behavioral differences between subject groups identified using smart homes and change point detection. IEEE Journal of Biomedical and Health Informatics, 25(2), 2021.
- A. Ghods and D. Cook. A survey of deep network techniques all classifiers can adopt. Data Mining and Knowledge Discovery, 35:46-87, 2021.
- G. Wilson, J. Doppa, and D. Cook. Multi-source deep domain adaptation with weak supervision for time-series sensor data. SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020.
- A. Fellger, D. Weeks, E. Crooks, G. Sprint, and D. Cook. Wearable device-independent next day activity and next night sleep prediction for rehabilitation populations. IEEE Journal of Translational Engineering in Health and Medicine, 8:1-9, 2020.
- G. Wilson and D. Cook. A survey of unsupervised deep domain adaptation. ACM Transactions on Intelligent Systems and Technology, 11(5):51, 2020.
- V. Tseng, J. Ying, S. Wong, D. Cook, and J. Liu. Computational intelligence techniques for combating COVID-19: A survey. IEEE Computational Intelligence Magazine, 15(4):10-22, 2020.
- N. Raghunath, J. Dahmen, K. Brown, M. Schmitter-Edgecombe, and D. Cook. Creating a digital memory notebook application for individuals with mild cognitive impairment to support everyday functioning. Disability and Rehabilitation: Assistive Technology, 4:421-431, 2020.
- S. Aminikhanghahi, M. Schmitter-Edgecombe, and D. Cook. Context-aware delivery of ecological momentary assessment. IEEE Journal of Biomedical and Health Informatics, 4(4):1206-1214, 2020.
- A. Ghods, A. Shahrokni, H. Ghasemzadeh, and D. Cook. The remote monitoring of gastrointestinal cancer patients' performance status and burden of symptoms via a consumer-based activity tracker. Journal of Medical Internet Research, 2020.
- M. Schmitter-Edgecombe, C. Sumida, and D. Cook. Bridging the gap between performance-based assessment and self-reported everyday functioning: An ecological momentary assessment aproach. The Clinical Neuropsychologist, 34(4):678-699, 2020.
- B. Lin and D. Cook. Using continuous sensor data to formalize a model of in-home activity patterns. Journal of Ambient Intelligence and Smart Environments, 12(3):183-201, 2020.
- C. Culman, S. Aminikhanghahi, and D. Cook Easing power consumption of wearable activity monitoring with change point detection. Sensors, 20(1):310, 2020.
- R. L. Fritz, M. Wilson, G. Dermody, M. Schmitter-Edgecombe, and D. Cook. Automated smart home assessment to support pain management. Journal of Medical Internet Research, 22(11):e23943, 2020.
- A. Akbari, P. Alinia, H. Ghasemzadeh, D. Cook, and R. Jafari. Transfer learning for wearable computers. Wearable Sensors, pages 435-459, 2020.
- Y. Wang and D. Cook. BraIN: A bidirectional generative adversarial network for image captions. MLNLP, 2020
- S. Aminikhanghahi, T. Wang, and D. Cook. Real-time change point detection with application to smart home time series data. IEEE Transactions on Knowledge and Data Engineering, 31(5):1010-1023, 2019.
- A. Ghods, K. Caffrey, B. Lin, K. Fraga, R. Fritz, M. Schmitter-Edgecombe, C. Hundhausen, and D. Cook. Iterative design of visual analytics for a clinician-in-the-loop smart home. IEEE Journal of Biomedical and Health Informatics, to appear.
- S. Aminikhanghahi, T. Wang, and D. Cook. Real-time change point detection with application to smart home time series data. IEEE Transactions on Knowledge and Data Engineering, to appear.
- S. Aminikhanghahi and D. Cook. Enhancing activity recognition using CPD-based activity segmentation. Pervasive and Mobile Computing, 53:75-89, 2019.
- G. Wilson, C. Pereyda, N. Raghunath, G. de la Cruz, S. Goel, S. Nesaei, B. Minor, M. Schmitter-Edgecombe, M. Taylor, and D. Cook. Robot-enabled support of daily activities in smart home environments. Cognitive Systems Research, 54:258-272, 2019.
- J. Dahmen and D. Cook. SynSys: A synthetic data generation system for healthcare applications. Sensors, 19(4):1181, 2019.
- S. Mirzadeh, J. Ardo, R. Fallahzadeh, B. Minor, L. Evangelista, D. Cook, and H. Ghasemzadeh. LabelMerger: Learning activities in uncontrolled environments. International Conference on Transdisciplinary AI, 2019.
- 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.
- B. Minor, J. Doppa, and D. Cook. Learning activity predictors from sensor data: Algorithms, evaluation, and applications. IEEE Transactions on Knowledge and Data Engineering, 29(12):2744-2757, 2017.
- G. Sprint, D. Cook, D. Weeks, J. Dahmen, and A. La Fleur. Analyzing sensor-based time series data to track changes in physical activity during inpatient rehabilitation. Sensors, 17:2219-2238, 2017.
- B. Lin and D. Cook, Analyzing sensor-based individual and population behavior patterns via inverse reinforcement learning., Sensors, 20(18):5207, 2020.
- P. Alinia, C. Cain, R. Fallahzadeh, A. Shahrokni, and H. Ghasemzadeh. How accurate is your activity tracker? A comparative study of step counts in low-intensity physical activities. Journal of Medical Internet Research, 5(8):e106, 2017.
- K. Feuz and D. Cook. Collegial activity learning between heterogeneous sensors. Knowledge and Information Systems, 53(2):337-364, 2017.
- J. Dahmen, D. Cook, X. Wang, and W. Honglei. Smart secure homes: A survey of smart home technologies that sense, assess, and respond to security threats. Journal of Reliable Intelligent Environments, 2017.
- B. Minor and D. Cook. Forecasting occurrences of activities. Pervasive and Mobile Computing, 38(1):77-91, 2017.
- B. Lin, Y. Huangfu, N. Lima, T. Jobson, M. Kirk, P. O'Keeffe, S. Pressley, V. Walden, B. Lamb, and D. Cook. Analyzing the relationship between human behavior and indoor air quality. Journal of Sensor and Actuator Networks. 6(13), 2017.
- K. Feuz, and D. Cook. Modeling skewed class distributions by reshaping the concept space. AAAI Conference on Artificial Intelligence, 2017.
- J. Dahmen, D. Cook, X. Wang, and W. Honglei. Smart secure homes: A survey of smart home technologies that sense, assess, and respond to security threats. Journal of Reliable Intelligent Environments, to appear.
- S. Aminikhanghahi and D. Cook. A survey of methods for time series change point detection. Knowledge and Information Systems, 51(2):339-367, 2017.
- J. Williams and D. Cook. Forecasting behavior in smart homes based on past sleep and wake patterns. Technology and Health Care, 25:89-110, 2017.
- J. Dahmen, R. Fellows, D. Cook, and M. Schmitter-Edgecombe. An analysis of a digital variant of the Trail Making Test using machine learning techniques. Technology and Health Care, 25(2):251-264, 2017.
- J. Dahmen, B. Thomas, D. Cook, and X. Wang. Activity learning as a foundation for security monitoring in smart homes. Sensors, 17:737, 2017.
- R. Fellows, J. Dahmen, D. Cook, and M. Schmitter-Edgecombe. Multicomponent analysis of a digital trail making test. The Clinical Neuropsychologist, 31(1):154-167, 2017.
- S. Aminikhanghahi, R. Fallahzadeh, D. Cook, and L. Holder. Thyme: Improving smartphone prompt timing through activity awareness. IEEE International Conference on Machine Learning and Applications, 2017.
- G. Sprint, A. La Fleur, J. Dahmen, V. Stilwill, A. Meisen-Vehrs, D. Weeks, and D. Cook. Continuous assessment of daytime heart rate response during inpatient rehabilitation. American Congress of Rehabilitation Medicine Annual Conference, 2017.
- S. Fritz and D. Cook. Identifying varying health states in smart home sensor data: An expert-guided approach. World Multiconference on Systems, Cybernetics and Informatics, 2017.
- R. Fallahzadeh, B. Minor, L. Evangelista, D. Cook, and H. Ghasemzadeh. Mobile sensing to improve medication adherence. ACM/IEEE International Conference on Information Processing in Sensor Networks, 2017.
- J. Dahmen, A. LaFleur, G. Sprint, D. Cook, and D. Weeks. Using wrist-worn sensors to measure and compare physical activity changes for patients undergoing rehabilitation. Workshop on Sensing Systems and Applications Using Wrist Worn Smart Devices, 2017.
- G. Sprint, V. Borisov, D. Cook, and D. Weeks. Measuring changes in gait and vehicle transfer ability during inpatient rehabilitation with wearable inertial sensors. Workshop on Pervasive Health Technologies, 2017.
- S. Aminikhanghahi and D. Cook. Using change point detection to automate daily activity segmentation. Workshop on Context and Activity Modeling and Recognition, 2017.
- G. Sprint, D. Cook, R. Fritz, and M. Schmitter-Edgecombe. Using smart homes to detect and analyze health events. Computer, 49(11):29-37, 2016.
- B. Thomas and D. Cook. Activity-aware energy-efficient automation of smart buildings. Energies, 9(8):624, 2016.
- G. Sprint, D. Cook, and M. Schmitter-Edgecombe. Unsupervised detection and analysis of changes in everyday physical activity data. Journal of Biomedical Informatics, 63:54-65, 2016.
- E. Van Etten, A. Weakley, M. Schmitter-Edgecombe, and D. Cook. Subjective cognitive complaints and objective memory performance influence prompt preference for instrumental activities of daily living. Gerontechnology, 14(3):169-176, 2016.
- Y. Hu, D. Tilke, T. Adams, A. Crandall, D. Cook, and M. Schmitter-Edgecombe. Smart home in a box: Usability study for a large scale self-installation of smart home technologies. Journal of Reliable Intelligent Environments, 2:93-106, 2016.
- R. Fritz, C. Corbett, R. Vandermause, and D. Cook. The influence of culture on older adults' adoption of smart home monitoring. Gerontechnology, 14(3):146-156, 2016.
- B. Das, D. Cook, N. Krishnan, and M. Schmitter-Edgecombe. One-class classification-based real-time activity error detection in smart homes. IEEE Journal of Selected Topics in Signal Processing, 10(5):914-923, 2016.
- P. Dawadi, D. Cook, and M. Schmitter-Edgecombe. Modeling patterns of activities using activity curves. Pervasive and Mobile Computing, 28(C):51-68, 2016.
- P. Dawadi, D. Cook, and M. Schmitter-Edgecombe. Automated clinical assessment from smart home-based behavior data. IEEE Journal of Biomedical and Health Informatics, 20(4):1188-1194, 2016.
- B. Thomas, A. Crandall, and D. Cook. A genetic algorithm approach to motion sensor placement in smart environments. Journal of Reliable Intelligent Environments, 2(1):3-16, 2016.
- A. Crandall and D. Cook. Current state of the art of smart environments and labs from an AAL point of view. In F. Florez-Revuelta and A. Chaaraoui (Eds.), Ambient Assisted Living: Technologies and Applications, IET, 2016.
- S. Aminikhanghahi and D. Cook. Activity transition detection by relative density ratio estimation. Florida Artificial Intelligence Research Symposium, 2016.
- G. Sprint and D. Cook. Designing wearable sensor-based analytics for quantitative mobility assessment. IEEE International Conference on Smart Computing, 2016.
- G. Sprint, D. Cook, R. Fritz, and M. Schmitter-Edgecombe. Detecting health and behavior change by analyzing smart home sensor data. IEEE International Conference on Smart Computing, 2016.
- K. Bouchard, L. Holder, and D. Cook. Extracting generalizable spatial features from smart phone datasets. AAAI Workshop on Artificial Intelligence Applied to Assistive Technologies and Smart Environments, 2016.
- G. Sprint and D. Cook. Quantitative assessment of lower limb and cane movement with wearable inertial sensors. The Engineering in Medicine and Biology Conference, 2016.
- G. Sprint, D. Cook, and D. Weeks. Patient similarity and joint features for rehabilitation outcome prediction. IJCAI Workshop on Knowledge Discovery in Healthcare Data, 2016.
- R. Fallahzadeh, S. Aminikhanghahi, A. Gibson, and D. Cook. Toward personalized and context-aware prompting for smartphone-based intervention. International Conference of the IEEE Engineering in Medicine and Biology Society, 2016.
- D. Cook, P. Dawadi, and M. Schmitter-Edgecombe. Analyzing activity behavior and movement in a naturalistic environment using smart home techniques. IEEE Journal of Biomedical and Health Informatics, 19(6):1882-1892, 2015.
- G. Sprint, D. Cook, D. Weeks, and V. Borisov. Predicting functional independence measure scores during rehabilitation with wearable inertial sensors. IEEE Access, 3:1350-1366, 2015.
- A. Weakley, J. Williams, M. Schmitter-Edgecombe, and D. Cook. Neuropsychological test selection for cognitive impairment classification: A machine learning approach. Journal of Clinical and Experimental Neuropsychology, 37(9):899-916, 2015.
- K. Robertson, C. Rosasco, K. Feuz, M. Schmitter-Edgecombe, and D. Cook. Prompting technologies: A comparison of time-based and context-aware transition-based prompting. Technology and Health Care, 23:745-746, 2015.
- B. Minor, D. Cook, and J. Doppa. Data-driven activity prediction: Algorithms, evaluation methodology, and applications. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2015.
- G. Sprint, D. Cook, and D. Weeks. Towards automating clinical assessments: A survey of the Timed Up and Go (TUG). IEEE Transactions on Reviews in Biomedical Engineering, 8:64-77, 2015.
- K. Feuz, D. Cook, C. Rasasco, K. Robertson, and M. Schmitter-Edgecombe. Automated detection of activity transitions for prompting. IEEE Transactions on Human Machine Systems, 6(1):3, 2015.
- K. Feuz and D. Cook. Transfer learning across feature-rich heterogeneous feature spaces via feature-space remapping. ACM Transactions on Intelligent Systems and Technology, 6(1):3, 2015.
- D. Cook and N. Krishnan. Activity Learning from Sensor Data. Wiley, 2015.
- E. Nazerfard and D. Cook. CRAFFT: An activity prediction model based on Bayesian networks. Journal of Ambient Intelligence and Humanized Computing, 6:193-205, 2015.
- B. Das, N. Krishnan, and D. Cook. RACOG and wRACOG: Two probabilistic oversampling methods. IEEE Transactions on Knowledge and Data Engineering, 27(1):222-234, 2015.
- D. Cook and N. Krishnan. Mining the home environment. Journal of Intelligent Information Systems, 43(3):503-519, 2014.
- N. Krishnan and D. Cook. Activity recognition on streaming sensor data. Pervasive and Mobile Computing, 20:138-154, 2014.
- K. Robertson, C. Rosasco, K. Feuz, D. Cook, and M. Schmitter-Edgecome. Prompting technologies: Is prompting during activity transition more effective than time-based prompting? Archives of Clinical Neuropsychology, 29(6):598, 2014.
- B. Das, N. Krishnan, and D. Cook. Handling imbalanced and overlapping classes in a smart environments prompting dataset. Data Mining for Service, pages 199-219, Springer, 2014.
- P. Dawadi, M. Schmitter-Edgecombe, and D. Cook. Smart home-based longitudinal functional assessment. ACM UbiComp Workshop on Smart Health Systems and Applications, 2014.
- G. Sprint, V. Borisov, D. Cook, and D. Weeks. Wearable sensors in ecological rehabilitation environments. ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2014.
- B. Thomas and D. Cook. CARL: Activity-aware automation for energy efficiency. ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2014.
- B. Minor and D. Cook. Regression tree classification for activity prediction in smart homes. ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2014.
- G. Acampora, D. Cook, P. Rashidi, and A. Vasilakos. A survey on ambient intelligence in health care. Proceedings of the IEEE, 101(12):2470-2494, 2013.
- D. Cook, N. Krishnan and Z. Wemlinger. Learning a taxonomy of predefined and discovered activity patterns. Journal of Ambient Intelligence and Smart Environments, 5(6):621-637, 2013.
- P. Dawadi, D. Cook, and M. Schmitter-Edgecombe. Automated cognitive health assessment using smart home smart monitoring of complex tasks. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 43(6):1302-1313, 2013.
- D. Cook, N. Krishnan, and P. Rashidi. Activity discovery and activity recognition: A new partnership. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 43(3):820-828, 2013.
- D. Cook, K. Feuz, and N. Krishnan. Transfer learning for activity recognition: A survey. Knowledge and Information Systems, 36:537-556, 2013.
- A. Seelye, M. Schmitter-Edgecombe, D. Cook, and A. Crandall. Naturalistic assessment of everyday activities and prompting technologies in mild cognitive impairment. Journal of the International Neuropsychological Society, 43(3):820-828, 2013.
- D. Cook and L. Holder. Automated activity-aware prompting for activity initiation. Gerontechnology, 11(4):1-11, 2013.
- D. Cook, A. Crandall, B. Thomas, and N. Krishnan. CASAS: A smart home in a box. IEEE Computer, 46(6):26-33, 2013.
- C. Chen, D. Cook, and A. Crandall. The user side of sustainability: Modeling behavior and energy usage in the home. Pervasive and Mobile Computing, 9(1):161-175, 2013.
- K. Feuz and D. Cook. Real-time annotation tool (RAT). Proceedings of the AAAI Workshop on Activity Context-Aware System Architectures, 2013.
- J. Williams, A. Weakley, D. Cook, and M. Schmitter-Edgecombe. Machine learning techniques for diagnostic differentiation of mild cognitive impairment and dementia. Proceedings of the AAAI Workshop on Expanding the Boundaries of Health Informatics Using AI, 2013.
- E. Nazerfard and D. Cook. Using Bayesian networks for daily activity prediction. Proceedings of the AAAI Workshop on Plan, Activity and Intent Recognition Workshop, 2013.
- N. Roy, A. Misra, and D. Cook. Infrastructure-assisted smartphone-based ADL recognition in multi-inhabitant smart environments. Proceedings of the IEEE International Conference on Pervasive Computing and Communication, 2013.
- D. De, W.Z. Song, S. Tang, D. Cook, and S. Das. Activity-aware sensor network in smart environments. Pervasive and Mobile Computing, 8(5):730-750, 2012.
- B. Das, D. Cook, M. Schmitter-Edgecombe, and A. Seelye.
PUCK: An automated prompting system for smart environments. Personal and Ubiquitous Computing, 16(7):859-873,
2012. - A. Seelye, M. Schmitter-Edgecombe, B. Das, and D. Cook.
Application of cognitive rehabilitation theory to the development of smart prompting technologies.
Reviews in Biomedical Engineering, 5:29-44, 2012. - A. Aztiria, J. Augusto, and D. Cook.
Discovering frequent user-environment interactions in intelligent environments.
Personal and Ubiquitous Computing, 16(1):91-103, 2012. - D. De, W. Song, S. Tang, D. Cook, and S. Das. Activity-aware sensor network in smart environments. Journal of Pervasive and Mobile Computing, 8(5):730-750, 2012.
- D. Cook. How smart is your home? Science, 335:1579-1581, 2012. (Summary)
- D. Cook. Learning setting-generalized activity models for smart spaces. IEEE Intelligent Systems, 27(1):32-38, 2012.
- D. Cook and S. Das.
Pervasive computing at scale: Transforming the state of the art.
Journal of Pervasive and Mobile Computing, 8(1):22-35, 2012. - B. Das, N. Krishnan, and D. Cook.
Automated activity interventions to asist with activities of daily living.
Agents and Ambient Intelligence, IOS Press, 2012. - D. De, W. Song, and D. Cook.
FindingHuMo: Real-time tracking of motion trajectories from anonymous binary sensing in smart environments.
Proceedings of the International Conference on Distributed Computing Systems, 2012. - L. Zulas, A. Crandall, M. Schmitter-Edgecombe, and D. Cook.
Caregiver needs from elder care assistive smart homes: Nursing assessment. Proceedings of the International Conference of the Human Factors and Ergonomics Society, 2012. - A. Crandall, L. Zulas, N. Krishnan, K. Feuz, and D. Cook.
Visualizing your ward: Bringing smart home data to caregivers. Proceedings of the CHI Workshop on Emerging Technologies for Healthcare and Aging, 2012. - B. Das, A. Seelye, B. Thomas, D. Cook, L. Holder, and M. Schmitter-Edgecombe.
Using smart phones for context-aware prompting in smart environments.
Proceedings of the CCNC CeHPSA Workshop, 2012. - A. Crandall and D. Cook.
Smart home in a box: A large scale smart home deployment.
Proceedings of the Workshop on Large Scale Intelligent Environments, 2012. - E. Nazerfard and D. Cook. Bayesian network structure learning for activity prediction in smart homes. Proceedings of the International Conference on Intelligent Environments, 2012.
- S. Dernbach, B. Das, N. Krishnan, B. Thomas, and D. Cook.
Simple and complex activity recognition through smart phones.
Proceedings of the International Conference on Intelligent Environments, 2012. - C. Chen and D. Cook.
Behavior-based home energy prediction. Proceedings of the International Conference on Intelligent Environments, 2012.
- M. Schmitter-Edgecombe, C. Parsey, and D. Cook.
Cognitive correlates of functional performance in older adults: Comparison of self-report, direct observation and performance-based measures. Journal of the International Neuropsychological Society, 17(5):853-864, 2011. - D. Cook, M. Schmitter-Edgecombe, and L. Holder.
Gerontechnology education: Beyond the barriers.
IEEE Pervasive Computing, 2011. - D. Cook and L. Holder.
Sensor selection to support practical use of health-monitoring smart environments.
Data Mining and Knowledge Discovery, 10:1-13, 2011. - P. Rashidi, D. Cook, L. Holder, and M. Schmitter-Edgecombe.
Discovering activities to recognize and track in a smart environment.
IEEE Transactions on Knowledge and Data Engineering, 23(4):527-539, 2011. - P. Rashidi and D. Cook.
Activity knowledge transfer in smart environments. Journal of Pervasive and
Mobile Computing, special issue on activity recognition, 7(3):331-343, 2011. - P. Rashidi and D. Cook.
Ask me better questions: Active learning queries based on rule induction.
Proceedings of the International Conference on Knowledge Discovery and Data Mining, 2011. - P. Dawadi, D. Cook, C. Parsey, M. Schmitter-Edgecombe, and M. Schneider.
Ask me better questions: An approach to cognitive assessment in smart home. KDD Workshop on Medicine and Healthcare, 2011. - C. Chen and D. Cook.
Energy outlier detection in smart environments.
Proceedings of the AAAI Workshop on Artificial Intelligence and Smarter Living: The Conquest of Complexity, 2011. - V. Jakkula and D. Cook.
Detecting anomalous sensor events in smart home data for enhancing the living experience.
Proceedings of the AAAI Workshop on Artificial Intelligence and Smarter Living: The Conquest of Complexity, 2011. - B. Das and D. Cook.
Data mining challenges in automated prompting systems.
Workshop on Interaction with Smart Objects, 2011. - P. Rashidi and D. Cook.
Domain selection and adaptation in smart homes.
Proceedings of the International Conference on Smart Homes and Health Telematics, 2011. - B. Das and D. Cook.
An automated prompting system for smart environments.
Proceedings of the International Conference on Smart Homes and Health Telematics, 2011. - E. Nazerfard, P. Rashidi, and D. Cook.
Using association rule mining to discover temporal relations of daily activities.
Proceedings of the International Conference on Smart Homes and Health Telematics, 2011. - B. Thomas and A. Crandall.
A demonstration of PyViz, a flexible smart home visualization tool.
Proceedings of the IEEE Conference on Pervasive Computing and Communication, 2011. - Y. Sahaf, N. Krishnan, and D. Cook.
Defining the complexity of an activity.
Proceedings of the AAAI Workshop on Activity Context Representation: Techniques and Languages, 2011. - C. Chen and P. Dawadi
CASASViz: Web-based visualization of behavior patterns in smart environments.
Proceedings of the IEEE Conference on Pervasive Computing and Communication, 2011.
- D. Cook, A. Crandall, G. Singla, and B. Thomas.
Detection of social interaction in smart spaces. Journal of Cybernetics and Systems, special issue on social awareness in smart spaces, 41(2):90-104, 2010. - S. Deleawe, J. Kusznir, B. Lamb, and D. Cook.
Predicting air quality in smart environments. Journal of Ambient Intelligence and Smart Environments, 2(2):145-154, 2010. - E. Kim, S. Helal, and D. Cook.
Human activity recognition and pattern discovery. IEEE Pervasive Computing, 9(1):48-53, 2010. - G. Singla, D. Cook, and M. Schmitter-Edgecombe,
Recognizing independent and joint activities among multiple residents in smart environments.
Ambient Intelligence and Humanized Computing Journal, 1(1):57-63, 2010. - A. Crandall and D. Cook. Tracking systems for multiple smart home residents. Human Behavior Recognition Technologies, IGI Global, 2010.
- C. Chen and D. Cook. Novelty detection in human behavior through analysis of energy utilization. Human Behavior Recognition Technologies, IGI Global, 2010.
- P. Rashidi and D. Cook.
Mining sensor streams for discovering human activity patterns over time. Proceedings of the IEEE International Conference on Data Mining, 2010. - P. Rashidi and D. Cook.
Mining and monitoring patterns of daily routines for assisted living in real world settings.
Proceedings of the ACM International Health Informatics Symposium, 2010. - E. Nazerfard, L. Holder, and D. Cook.
Conditional random fields for activity recognition in smart environments.
Proceedings of the ACM International Health Informatics Symposium, 2010. - P. Rashidi and D. Cook.
Multi home transfer learning for resident activity discovery and recognition. Proceedings of the International
workshop on Knowledge Discovery from Sensor Data, 2010. - C. Chen, B. Das, and D. Cook.
Energy prediction based on resident’s activity.
Proceedings of the International workshop on Knowledge Discovery from Sensor Data, 2010. - R. Srinivasan, C. Chen, and D. Cook.
Activity recognition using actigraph sensor. Proceedings of the International workshop on Knowledge Discovery from Sensor Data, 2010. - P. Rashidi and D. Cook.
An adaptive sensor mining framework for pervasive computing applications.
Lecture Notes in Computer Science, 5840:154-174, 2010. - P. Rashidi and D. Cook.
Home to home transfer learning. Proceedings of the AAAI Plan, Activity, and Intent
Recognition Workshop, 2010. - J. Kusznir and D. Cook.
Designing lightweight software architectures for smart environments. Proceedings of the International Conference on
Intelligent Environments, 2010. - C. Chen, B. Das, and D. Cook.
A data mining framework for activity recognition in
smart environments. Proceedings of the International Conference
on Intelligent Environments, 2010. - A. Crandall and D. Cook.
Using a hidden Markov model for resident identification. Proceedings of the International Conference on Intelligent Environments, 2010. - A. Aztiria and D. Cook. Automatic modeling of frequent user behaviours in intelligent environments. Proceedings of the International Conference on Intelligent Environments, 2010.
- V. Jakkula and D. Cook.
Outlier detection in smart environment structured power datasets. Proceedings of the International Conference on Intelligent Environments, 2010. - A. Elfaham, H. Hagras, S. Helal, H. Shantonu, J. Lee, and D. Cook.
A fuzzy based verification agent for the PerSim human activity simulator in ambient intelligence environments. Proceedings of the IEEE International Conference on Fuzzy Systems, 2010.
- P. Rashidi and D. Cook.
Keeping the resident in the loop: Adapting the smart home to the user.
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 39(5):949-959, 2009. - D. Cook, H. Hagras, V. Callaghan, and A. Helal,
Making our environments intelligent.
Journal of Pervasive and Mobile Computing, 5:556-557, 2009. - A. Crandall and D. Cook.
Coping with multiple residents in a smart environment. Journal of Ambient Intelligence and Smart Environments,
1(4):323-334, 2009. - S. Szewcyzk, K. Dwan, B. Minor, B. Swedlove, and D. Cook,
Annotating smart environment sensor data for activity learning.
Technology and Health Care, special issue on Smart Environments: Technology to support health care, 2009. - G. Singla, D. Cook, and M. Schmitter-Edgecombe,
Tracking activities in complex settings using smart environment technologies. International Journal of BioSciences, Psychiatry and Technology, 1(1):25-35, 2009. - D. Cook. J. Augusto, and V. Jakkula.
Ambient intelligence: Technologies, applications, and opportunities.
Journal of Pervasive and Mobile Computing, 5(4):277-298, 2009. - D. Cook and M. Schmitter-Edgecombe.
Assessing the quality of activities in a smart environment. Methods of Information in Medicine, 2009. - D. Cook and W. Song.
Ambient intelligence and wearable computing: Sensors on the body, in the home, and beyond. Journal of Ambient Intelligence and Smart Environments, 3:1-4, 2009. - D. Cook, Multi-agent smart environments. Journal of Ambient Intelligence and Smart Environments, 1:47-51, 2009.
- D. Brezeale and D. Cook,
Learning video preferences using visual features and closed captions.
IEEE Multimedia, 16(3):39-47, 2009. - D. Cook and A. Crandall,
Learning activity models for multiple agents in a smart space.
Handbook of Ambient Intelligence and Smart Environments, Elsevier, 2009. - A. Mendez-Vazquez, S. Helal, and D. Cook.
Simulating events to generate synthetic data for pervasive spaces.
Proceedings of the CHI Workshop on Developing Shared Home Behavior Datasets to Advance HCI and Ubiquitous Computing Research, 2009. - D. Cook, M. Schmitter-Edgecombe, A. Crandall, C. Sanders, and B. Thomas.
Collecting and disseminating smart home sensor data in the CASAS project.
Proceedings of the CHI Workshop on Developing Shared Home Behavior Datasets to Advance HCI and Ubiquitous Computing Research, 2009. - G. Singla and D. Cook.
Interleaved activity recognition for smart environments. Proceedings of the
International Conference on Intelligent Environments, 2009. - P. Rashidi and D. Cook.
Transferring learned activities in smart environments. Proceedings of the International Conference on Intelligent Environments, 2009.
- A. Helal, M. Schmalz, and D. Cook.
Smart home-based health platform for behavioral monitoring and alteration of diabetes patients.
Journal of Diabetes Science and Technology, 3(1):1-8, 2008. - V. Jakkula and D. Cook.
Anomaly detection using temporal data mining in a smart home environment. Methods of Information in Medicine, 2008. - D. Brezeale and D. Cook.
Automatic video classification: A survey of the literature. IEEE Transactions on
Systems, Man, and Cybernetics, Part C, 2008. - V. Jakkula and D. J. Cook.
Enhancing smart home algorithms using temporal relations. Technology and Aging, IOS Press, 2008. - V. Jakkula, A. Crandall, and D. J. Cook.
Enhancing anomaly detection using temporal pattern discovery.
Advanced Intelligent Environments, Springer, 2008. - P. Rashidi and D. Cook.
An adaptive sensor mining model for pervasive computing applications.
Proceedings of the KDD Workshop on Knowledge Discovery from Sensor Data, 2008. - A. Aztiria, J. Augusto, A. Izaguirre, and D. Cook.
Learning accurate temporal relations from user actions in intelligent environments.
Proceedings of the Symposium of Ubiquitous Computing and Ambient Intelligence, 2008. - P. Rashidi and D. Cook.
Adapting to resident preferences in smart environments. Proceedings of
the AAAI Workshop on Advances in Preference Handling, pages 78-84, 2008. - G.Singla, D. Cook, and M. Schmitter-Edgecombe.
Incorporating temporal reasoning into activity recognition for smart home residents. Proceedings of the AAAI
Workshop on Spatial and Temporal Reasoning, pages 53-61, 2008. - S. Lockwood and D. Cook.
Computer, light on!.
Proceedings of the International Conference on Intelligent Environments, 2008. - A. Crandall and D. Cook.
Attributing events to individuals in multi-inhabitant environments.
Proceedings of the International Conference on Intelligent Environments, 2008. - P. Rashidi and D. Cook.
Keeping the intelligent environment resident in the loop.
- D. Cook, L. Holder, and G. M. Youngblood.
Graph-based analysis of human transfer learning using a game testbed.
IEEE Transactions on Knowledge and Data Engineering, 19(11):1-14, 2007. - K. Gopalratnam and D. Cook.
Online sequential prediction via incremental parsing: The Active LeZi algorithm. IEEE Intelligent Systems, 22(1), 2007. - G. M. Youngblood and D. Cook.
Data mining for hierarchical model creation. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 37(4):561-572, 2007. - D. Cook and S. K. Das.
How smart are our environments? An updated look at the state of the art.
Journal of Pervasive and Mobile Computing, 2007. - D. Cook. Making sense of sensor data.
IEEE Pervasive Computing, 2007. - V. Jakkula and D. Cook.
Prediction models for a smart home based health care system. Proceedings of the First International Workshop on Smart Homes for Tele-Health, 2007. - V. Jakkula, A. Crandall, and D. Cook.
Knowledge discovery in entity based smart environment resident data using temporal relations based data mining.
Proceedings of the ICDM Workshop on Spatial and Spatio-Temporal Data Mining, 2007. - V. Jakkula and D. Cook.
Mining sensor data in smart environments for temporal activity prediction.
Proceedings of the First International Workshop on Knowledge Discovery from Sensor Data, 2007. - V. Jakkula and D. Cook.
Temporal pattern discovery for anomaly detection in smart homes. Proceedings of the International
Conference on Intelligent Environments, 2007. - V. Jakkula and D. Cook.
Using temporal relations in smart home data for activity prediction.
Proceedings of the ICML Workshop on the Induction of Process Models, 2007. - V. Jakkula and D. Cook.
Learning temporal relations in smart home data.
Proceedings of the Second International Conference on Technology and Aging, 2007. - V. Jakkula and D. Cook.
Prediction models for a smart home based health care system. Proceedings of the First International
Workshop on Smart Homes for Tele-Health, 2007. - P. Rashidi, G. M. Youngblood, D. Cook, and S. Das.
Inhabitant guidance of smart environments. Proceedings of the
International Conference on Human-Computer Interaction, 2007. - D. J. Cook, G. M. Youngblood, and G. Jain.
Algorithms for smart spaces.
The Engineering Handbook on Smart Technology for Aging, Disability and Independence, A. Helal, M. Mokhtari and B. Abdulrazak, Editors, John Wiley and Sons, 2007.
- 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.
- 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.