Consistency Verification of Marker-Less Gait Assessment System for Stair Walking

被引:0
|
作者
Ogawa, Ami [1 ]
Yorozu, Ayanori [1 ]
Mita, Akira [1 ]
Takahashi, Masaki [1 ]
Georgoulas, Christos [2 ]
Bock, Thomas [2 ]
机构
[1] Keio Univ, Sch Sci Open & Environm Syst, Tokyo, Japan
[2] Tech Univ Munich, Chair Bldg Realizat & Robot, Munich, Germany
关键词
Stair walking; Marker-less gait measurement; Depth data; Kinect v2; VICON; AGE-RELATED DIFFERENCES; OLDER-ADULTS; DESCENT; KNEE; ASCENT; FORCES; RISK;
D O I
10.1007/978-3-319-31744-1_57
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The number of elderly people is drastically increasing. To support them, the gait information is under the spotlight since it has the relationship between the fall risk and dementia. Among other scenarios, a relatively higher level of ability is needed for the stair walking as it requires balancing and loading. Conventionally, 3D motion capture devices have been used to acquire the parameters of stair walking. However, it is difficult to acquire daily parameters as the equipment needs complicated preparation and body-worn markers. In this study, we propose a system which can acquire daily stair walking parameters using only depth data obtained by Kinect v2 without restraining by markers. We confirmed the accuracy of our proposed system compared with a 3D motion capture system.
引用
收藏
页码:653 / 663
页数:11
相关论文
共 50 条
  • [41] Easy Extrinsic Calibration of VR System and Multi-Camera based Marker-less Motion Capture System
    Takahashi, Kosuke
    Mikami, Dan
    Isogawa, Mariko
    Sun, Siqi
    Kusachi, Yoshinori
    ADJUNCT PROCEEDINGS OF THE 2019 IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY (ISMAR-ADJUNCT 2019), 2019, : 83 - 88
  • [42] Efficient techniques for gait-analysis: comparing marker-less and IMU-based tracking systems for monitoring rehabilitation processes
    Eikerling, Heinz-Josef
    Uelschen, Michael
    Stuntebeck, Benedikt
    EMBEC & NBC 2017, 2018, 65 : 860 - 863
  • [43] Validation of joint angle measurements: comparison of a novel low-cost marker-less system with an industry standard marker-based system
    Bahadori S.
    Davenport P.
    Immins T.
    Wainwright T.W.
    Journal of Medical Engineering and Technology, 2019, 43 (01): : 19 - 24
  • [44] Hybrid System Mixed Reality and Marker-Less Motion Tracking for Sports Rehabilitation of Martial Arts Athletes
    Franzo, Michela
    Pica, Andrada
    Pascucci, Simona
    Marinozzi, Franco
    Bini, Fabiano
    APPLIED SCIENCES-BASEL, 2023, 13 (04):
  • [45] Objective evaluation of bradykinesia in Parkinson's disease using an inexpensive marker-less motion tracking system
    Lee, Wee Lih
    Sinclair, Nicholas C.
    Jones, Mary
    Tan, Joy L.
    Proud, Elizabeth L.
    Peppard, Richard
    McDermott, Hugh J.
    Perera, Thushara
    PHYSIOLOGICAL MEASUREMENT, 2019, 40 (01)
  • [46] A New Marker-Less 3D Kinect-Based System for Facial Anthropometric Measurements
    Loconsole, Claudio
    Barbosa, Nuno
    Frisoli, Antonio
    Orvalho, Veronica Costa
    ARTICULATED MOTION AND DEFORMABLE OBJECTS, 2012, 7378 : 124 - 133
  • [47] Comparison of Patient-Reported Outcomes and Functional Assessment Using a Marker-Less Image Capture System in End-Stage Knee Arthritis
    Ekanayake, Cameron D.
    DeMik, David E.
    Glass, Natalie A.
    Kotseos, Chandler
    Callaghan, John J.
    Ratigan, Brian L.
    JOURNAL OF ARTHROPLASTY, 2022, 37 (11): : 2158 - 2163
  • [48] Onboard Marker-Less Detection and Localization of Non-Cooperating Drones for Their Safe Interception by an Autonomous Aerial System
    Vrba, Matous
    Hert, Daniel
    Saska, Martin
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2019, 4 (04) : 3402 - 3409
  • [49] A marker-less human motion analysis system for motion-based biomarker identification and quantification in knee disorders
    Armstrong, Kai
    Zhang, Lei
    Wen, Yan
    Willmott, Alexander P.
    Lee, Paul
    Ye, Xujiong
    FRONTIERS IN DIGITAL HEALTH, 2024, 6
  • [50] Towards Automated and Marker-less Parkinson Disease Assessment: Predicting UPDRS Scores using Sit-stand videos
    Mehta, Deval
    Asif, Umar
    Hao, Tian
    Bilal, Erhan
    von Cavallar, Stefan
    Harrer, Stefan
    Rogers, Jeffrey
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 3836 - 3844