Pose and Optical Flow Fusion (POFF) for accurate tremor detection and quantification

被引:9
|
作者
Alper, Mehmet Akif [1 ]
Goudreau, John [2 ]
Daniel, Morris [1 ]
机构
[1] Michigan State Univ, Elect & Comp Engn, E Lansing, MI 48824 USA
[2] Michigan State Univ, Movement Disorders Subspecialty Clin, Neurol, E Lansing, MI 48824 USA
关键词
Limb tracking; Contactless; Tremor amplitude and frequency; Temporal alignment; Accelerometer; Kinect; 2; Marker; Parkinson's disease; KINECT; MOVEMENT;
D O I
10.1016/j.bbe.2020.01.009
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Limb tremor measurements are one factor used to characterize and quantify the severity of neurodegenerative disorders. These tremor measurements can also provide dosage-response feedback to guide medication treatments. Here, we propose a system to automatically measure limb tremors in home or clinic settings. The key feature of proposed method is that it is contactless; not requiring a user to wear or hold a device or marker. Our sensor is a Kinect 2, which measures color and depth and estimates rough limb motion. We show that its pose accuracy is poor for small limb tremors below 10 mm amplitude, and so we propose an additional level of tremor tracking that recovers limb motion at a higher precision. Our method upgrades the sensitivity to achieve detection and analysis for tremors down to 2 mm amplitude. We include empirical experiments and measurements showing improved tremor amplitude and frequency estimation using our proposed Pose and Optical Flow Fusion (POFF) algorithm. (c) 2020 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:468 / 481
页数:14
相关论文
共 50 条
  • [41] Accurate Optical Flow Sensor for Obstacle Avoidance
    Wei, Zhaoyi
    Lee, Dah-Jye
    Nelson, Brent E.
    Lillywhite, Kirt D.
    ADVANCES IN VISUAL COMPUTING, PT I, PROCEEDINGS, 2008, 5358 : 240 - 247
  • [42] An accurate and adaptive optical flow estimation algorithm
    Teng, CH
    Lai, SH
    Chen, YS
    Hsu, WH
    ICIP: 2004 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1- 5, 2004, : 1839 - 1842
  • [43] Accurate optical flow in noisy image sequences
    Spies, H
    Scharr, H
    EIGHTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOL I, PROCEEDINGS, 2001, : 587 - 592
  • [44] POINTVOTENET: ACCURATE OBJECT DETECTION AND 6 DOF POSE ESTIMATION IN POINT CLOUDS
    Hagelskjaer, Frederik
    Buch, Anders Glent
    2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2020, : 2641 - 2645
  • [45] Automated analysis of pen-on-paper spirals for tremor detection, quantification and differentiation
    Rajan, R.
    Anandapadmanabhan, R.
    Vishnu, V. Y.
    Gupta, A.
    Bhatia, R.
    Singh, M. B.
    Srivastava, A. K.
    Srivastava, M. V. P.
    MOVEMENT DISORDERS, 2021, 36 : S594 - S595
  • [46] STAR-SEQR: Accurate fusion detection and support for fusion neoantigen applications
    Jasper, Jeff
    Powers, Jason G.
    Weigman, Victor J.
    CANCER RESEARCH, 2018, 78 (13)
  • [47] Slippage Detection and Pose Recovery for Upward-Looking Camera-Based SLAM Using Optical Flow
    Chae, Heewon
    Song, Jae-Bok
    2013 13TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2013), 2013, : 1108 - 1113
  • [48] POOF: Efficient Goalie Pose Annotation using Optical Flow
    Gebotys, Brennan
    Wong, Alexander
    Clausi, David
    PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON SPORT SCIENCES RESEARCH AND TECHNOLOGY SUPPORT (ICSPORTS), 2021, : 116 - 122
  • [49] HYBRID TRACKING APPROACH USING OPTICAL FLOW AND POSE ESTIMATION
    Pressigout, Muriel
    Marchand, Eric
    Memin, Etienne
    2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5, 2008, : 2720 - 2723
  • [50] Highly sensitive fusion transcript detection and quantification in cancer
    Watson, Lisa C.
    Gross, Stephen M.
    Khrevtukova, Irina
    Pathak, Smita
    Attwooll, Claire
    Goode, Jason
    Mai, Anthony
    Schroth, Gary P.
    CANCER RESEARCH, 2015, 75