Zachary Beattie, Ph.D.

  • Assistant Professor of Neurology, School of Medicine
  • ORCATECH, School of Medicine

Biography

While a graduate student at OHSU, Dr. Beattie developed a new technology with the ability to detect sleep apnea using non-contact sensors. After completing his Ph.D. in Biomedical Engineering, Dr. Beattie accepted a Research Scientist position at Fitbit where he innovated new features for Fitbit wearables, working as project lead for several Fitbit research projects including the recently released Fitbit Sleep Stages feature, which has been used to collect over 6 billion nights of sleep data.  In 2017, Dr. Beattie returned to OHSU to join the team at the Oregon Center for Aging and Technology.

In his free time, Dr. Beattie enjoys spending time with his three boys and exploring the outdoors through camping, hiking, and running.

Research

Currently as lead data scientist at ORCATECH (Oregon Center for Aging and Technology), Dr. Beattie is focused on data validity, provenance and integrity for the ORCATECH platform.  The ORCATECH platform consists of digital sensors placed in the homes of elderly individuals that are used to collect a variety of data (e.g. walking speed, activity levels) about the individuals with the goal of developing digital biomarkers that can be used to facilitate studies of aging and in clinical trials. Dr. Beattie is particularly focused on overseeing data architecture and algorithm development for the NIA and VA funded national CART (Collaborative Aging Research using Technology) Initiative by building out the ORCATECH platform to enable research for multiple investigators ultimately engaging thousands of homes across the U.S.

Publications

1.   Beattie ZT. Algorithm for automatic beat detection of cardiovascular pressure signals.  Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008.  2594-2597. 2.   Beattie ZT, Hagen CC, Pavel M, Hayes TL. Classification of breathing events using load cells under the bed. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009.  3921-3924. 3.    Adami AM, Adami AG, Schwarz G, Beattie ZT, Hayes TL. A subject state detection approach to determine rest-activity patterns using load cells. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2010.  204-207. 4.   Beattie ZT, Hagen CC, Hayes TL. Classification of lying position using load cells under the bed. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011.  474-477. Adami AM, Adami AG, Hayes TL, Pavel M, Beattie ZT. A Gaussian model for movement detection during sleep. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012.  2263-2266. Austin D,Beattie ZT, Riley T, Adami AM, Hagen CC, Hayes TL. Unobtrusive classification of sleep and wakefulness using load cells under the bed. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012.  5254-5257. Beattie ZT, Hayes TL, Guilleminault C, Hagen CC. Accurate scoring of the apnea–hypopnea index using a simple non-contact breathing sensor. Journal of Sleep Research, 2013, 22: 356–362. Adami AM, Adami AG, Hayes TL, Beattie ZT. (2013). A system for assessment of limb movements in sleep. Proceedings of the IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013), p. 397-401. Adami AM, Adami AG, Hayes TL, Beattie ZT. (2013). Unobtrusive movement detection during sleep based on load cell dynamics. In: XIII Workshop de Informática Médica (WIM 2013), Proceedings of the XXXIII Congresso Brasileiro da Sociedade Brasileira de Computação. Adami AM, Adami AG, Hayes TL, Beattie ZT. (2014). Using load cells under the bed as a non-contact method for detecting periodic leg movements. IRBM, 35: 334-340. Beattie ZT, Oyang Y, Statan A, Ghoreyshi A, Pantelopoulos A, Russell A, Heneghan C. (2017). Estimation of sleep stages in a healthy adult population from optical plethysmography and accelerometer signals. Physiological Measurement, 38: 1968-1979. Kaye J, Reynolds C, Bowman M, Sharma N, Riley T, Golonka O, Lee J, Quinn C, Beattie ZT, Austin J, Seelye A, Wild K, Mattek N. (2018). Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data. J. Vis. Exp.(137).

Education

  • Ph.D., 2013, Oregon Health & Science University

Publications

Publications

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