Literature DB >> 23366301

Full body gait analysis with Kinect.

Moshe Gabel1, Ran Gilad-Bachrach, Erin Renshaw, Assaf Schuster.   

Abstract

Human gait is an important indicator of health, with applications ranging from diagnosis, monitoring, and rehabilitation. In practice, the use of gait analysis has been limited. Existing gait analysis systems are either expensive, intrusive, or require well-controlled environments such as a clinic or a laboratory. We present an accurate gait analysis system that is economical and non-intrusive. Our system is based on the Kinect sensor and thus can extract comprehensive gait information from all parts of the body. Beyond standard stride information, we also measure arm kinematics, demonstrating the wide range of parameters that can be extracted. We further improve over existing work by using information from the entire body to more accurately measure stride intervals. Our system requires no markers or battery-powered sensors, and instead relies on a single, inexpensive commodity 3D sensor with a large preexisting install base. We suggest that the proposed technique can be used for continuous gait tracking at home.

Entities:  

Mesh:

Year:  2012        PMID: 23366301     DOI: 10.1109/EMBC.2012.6346340

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  27 in total

1.  Portable Motion-Analysis Device for Upper-Limb Research, Assessment, and Rehabilitation in Non-Laboratory Settings.

Authors:  Won Joon Sohn; Rifat Sipahi; Terence D Sanger; Dagmar Sternad
Journal:  IEEE J Transl Eng Health Med       Date:  2019-11-13       Impact factor: 3.316

2.  Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors.

Authors:  Conrad S Tucker; Ishan Behoora; Harriet Black Nembhard; Mechelle Lewis; Nicholas W Sterling; Xuemei Huang
Journal:  Comput Biol Med       Date:  2015-09-08       Impact factor: 4.589

3.  MotionTalk: Personalized home rehabilitation system for assisting patients with impaired mobility.

Authors:  Janani Venugopalan; Chih-Wen Cheng; May D Wang
Journal:  ACM BCB       Date:  2014

4.  Automating the Clinical Assessment of Independent Wheelchair Sitting Pivot Transfer Techniques.

Authors:  Lin Wei; Cheng-Shiu Chung; Alicia M Koontz
Journal:  Top Spinal Cord Inj Rehabil       Date:  2021-08-13

5.  Development of a Smart Hallway for Marker-Less Human Foot Tracking and Stride Analysis.

Authors:  Vinod Gutta; Pascal Fallavollita; Natalie Baddour; Edward D Lemaire
Journal:  IEEE J Transl Eng Health Med       Date:  2021-03-29       Impact factor: 3.316

6.  Walking speed measurement technology: A review.

Authors:  Yohanna MejiaCruz; Jean Franco; Garret Hainline; Stacy Fritz; Zhaoshuo Jiang; Juan M Caicedo; Benjamin Davis; Victor Hirth
Journal:  Curr Geriatr Rep       Date:  2021-01-20

7.  A 2D Markerless Gait Analysis Methodology: Validation on Healthy Subjects.

Authors:  Andrea Castelli; Gabriele Paolini; Andrea Cereatti; Ugo Della Croce
Journal:  Comput Math Methods Med       Date:  2015-04-30       Impact factor: 2.238

8.  Automation of workplace lifting hazard assessment for musculoskeletal injury prevention.

Authors:  June T Spector; Max Lieblich; Stephen Bao; Kevin McQuade; Margaret Hughes
Journal:  Ann Occup Environ Med       Date:  2014-06-24

9.  Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications.

Authors:  Alvaro Muro-de-la-Herran; Begonya Garcia-Zapirain; Amaia Mendez-Zorrilla
Journal:  Sensors (Basel)       Date:  2014-02-19       Impact factor: 3.576

10.  Using perceptive computing in multiple sclerosis - the Short Maximum Speed Walk test.

Authors:  Janina Behrens; Caspar Pfüller; Sebastian Mansow-Model; Karen Otte; Friedemann Paul; Alexander U Brandt
Journal:  J Neuroeng Rehabil       Date:  2014-05-27       Impact factor: 4.262

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