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 70 条
  • [21] Dutta D, 2017, BIOCYBERN BIOMED ENG
  • [22] Fabian J, 2014, IEEE ASME T MECHATRO
  • [23] Fischer RA, 1936, ANN EUGEN
  • [24] Real-Time Estimation of Pathological Tremor Parameters from Gyroscope Data
    Gallego, Juan A.
    Rocon, Eduardo
    Roa, Javier O.
    Moreno, Juan C.
    Pons, Jose L.
    [J]. SENSORS, 2010, 10 (03) : 2129 - 2149
  • [25] Galna B, 2014, GAIT POSTURE
  • [26] Metrological comparison between Kinect I and Kinect II sensors
    Gonzalez-Jorge, H.
    Rodriguez-Gonzalvez, P.
    Martinez-Sanchez, J.
    Gonzalez-Aguilera, D.
    Arias, P.
    Gesto, M.
    Diaz-Vilarino, L.
    [J]. MEASUREMENT, 2015, 70 : 21 - 26
  • [27] Reliability and validity of a novel Kinect-based software program for measuring posture, balance and side-bending
    Grooten, Wilhelmus Johannes Andreas
    Sandberg, Lisa
    Ressman, John
    Diamantoglou, Nicolas
    Johansson, Elin
    Rasmussen-Barr, Eva
    [J]. BMC MUSCULOSKELETAL DISORDERS, 2018, 19
  • [28] Hafeez A., 2014, TRANSFORM, V2, P420
  • [29] Heinrich F, 2016, MOV DISORD
  • [30] RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
    Henry, Peter
    Krainin, Michael
    Herbst, Evan
    Ren, Xiaofeng
    Fox, Dieter
    [J]. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2012, 31 (05) : 647 - 663