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Computer Science

D-Index
55
Citations
11909
World Ranking
4323
National Ranking
2028

Research.com Recognitions

  • 2018 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

Marjorie Skubic is affiliated with the University of Missouri in the United States. Their research spans multiple disciplines, primarily focusing on Medicine and Computer Science. Within these fields, they have contributed to subfields such as Computer Vision and Pattern Recognition, Biomedical Engineering, Cardiology and Cardiovascular Medicine, Physical Therapy, Sports Therapy and Rehabilitation, and Surgery.

The scientist's work covers a variety of topics, including:

  • Context-Aware Activity Recognition Systems
  • Non-Invasive Vital Sign Monitoring
  • Balance, Gait, and Falls Prevention
  • Stroke Rehabilitation and Recovery
  • Heart Rate Variability and Autonomic Control
  • Technology Use by Older Adults
  • Time Series Analysis and Forecasting

Their frequent co-authors include Mihail Popescu, James M. Keller, Laurel Despins, Rachel Proffitt, and Mengxuan Ma.

Marjorie Skubic has published multiple papers in various venues, some of which include:

  • "Explainable Fall Risk Prediction in Older Adults Using Gait and Geriatric Assessments," 2022, Frontiers in Digital Health
  • "Non-Invasive Heart Rate Estimation From Ballistocardiograms Using Bidirectional LSTM Regression," 2021, IEEE Journal of Biomedical and Health Informatics
  • "Technology for Healthy Independent Living: Creating a Tailored In-Home Sensor System for Older Adults and Family Caregivers," 2020, Journal of Gerontological Nursing
  • "Early Detection of Health Changes in the Elderly Using In-Home Multi-Sensor Data Streams," 2021, ACM Transactions on Computing for Healthcare
  • "Using Sensor Signals in the Early Detection of Heart Failure: A Case Study," 2020, Journal of Gerontological Nursing

The scientist has a notable publication presence in venues such as Innovation in Aging, Journal of Gerontological Nursing, American Journal of Occupational Therapy, IEEE Journal of Biomedical and Health Informatics, and the 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Marjorie Skubic was recognized as a Fellow of the Indian National Academy of Engineering (INAE) in 2018.

Best Publications

  • Older adults' attitudes towards and perceptions of ‘smart home’ technologies: a pilot study

    George Demiris;Marilyn J. Rantz;Myra A. Aud;Karen D. Marek

  • Fall Detection in Homes of Older Adults Using the Microsoft Kinect

    Erik E. Stone;Marjorie Skubic

  • Senior residents' perceived need of and preferences for "smart home" sensor technologies.

    George Demiris;Brian K. Hensel;Marjorie Skubic;Marilyn Rantz

  • A smart home application to eldercare: Current status and lessons learned

    Marjorie Skubic;Gregory Alexander;Mihail Popescu;Marilyn Rantz

  • Spatial language for human-robot dialogs

    M. Skubic;D. Perzanowski;S. Blisard;A. Schultz

  • Linguistic summarization of video for fall detection using voxel person and fuzzy logic

    Derek Anderson;Robert H. Luke;James M. Keller;Marjorie Skubic

  • Doppler Radar Fall Activity Detection Using the Wavelet Transform

    Bo Yu Su;K. C. Ho;Marilyn J. Rantz;Marjorie Skubic

  • Needing smart home technologies: the perspectives of older adults in continuing care retirement communities.

    Karen L Courtney;George Demiris;Marilyn Rantz;Marjorie Skubic

  • Recognizing falls from silhouettes.

    Derek Anderson;James M. Keller;Marjorie Skubic;Xi Chen

  • Histogram of oriented normal vectors for object recognition with a depth sensor

    Shuai Tang;Xiaoyu Wang;Xutao Lv;Tony X. Han

  • Automatic fall detection based on Doppler radar motion signature

    Liang Liu;Mihail Popescu;Marjorie Skubic;Marilyn Rantz

  • Unobtrusive, Continuous, In-Home Gait Measurement Using the Microsoft Kinect

    Erik E. Stone;Marjorie Skubic

  • An acoustic fall detector system that uses sound height information to reduce the false alarm rate

    Mihail Popescu;Yun Li;Marjorie Skubic;Marilyn Rantz

  • Passive in-home measurement of stride-to-stride gait variability comparing vision and Kinect sensing

    Erik E. Stone;Marjorie Skubic

  • Evaluation of an inexpensive depth camera for in-home gait assessment

    Erik Stone;Marjorie Skubic

  • Findings from a participatory evaluation of a smart home application for older adults

    George Demiris;Debra Parker Oliver;Geraldine Dickey;Marjorie Skubic

  • A technology and nursing collaboration to help older adults age in place.

    Marilyn J. Rantz;Karen Dorman Marek;Karen Dorman Marek;Myra Aud;Harry W. Tyrer

  • Older adults' privacy considerations for vision based recognition methods of eldercare applications

    George Demiris;Debra Parker Oliver;Jarod Giger;Marjorie Skubic

  • Sensor Technology to Support Aging in Place

    Marilyn J. Rantz;Marjorie Skubic;Steven J. Miller;Colleen Galambos

  • Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment

    Marjorie Skubic;Rainer Dane Guevara;Marilyn Rantz

  • Modeling Human Activity From Voxel Person Using Fuzzy Logic

    D. Anderson;R.H. Luke;J.M. Keller;M. Skubic

  • Evaluation of an inexpensive depth camera for passive in-home fall risk assessment

    Erik E. Stone;Marjorie Skubic

Frequent Co-Authors

James M. Keller
James M. Keller University of Missouri
K. C. Ho
K. C. Ho University of Missouri
Alan C. Schultz
Alan C. Schultz United States Naval Research Laboratory
Zhihai He
Zhihai He University of Missouri
J. Gregory Trafton
J. Gregory Trafton United States Naval Research Laboratory
Julie A. Adams
Julie A. Adams Oregon State University
Diane J. Cook
Diane J. Cook Washington State University
Jeffrey Kaye
Jeffrey Kaye Oregon Health & Science University
Alex Mihailidis
Alex Mihailidis University of Toronto
Holly A. Yanco
Holly A. Yanco University of Massachusetts Lowell

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