Literature DB >> 25751867

Fast Determination of the Planar Body Segment Inertial Parameters Using Affordable Sensors.

Vincent Bonnet, Gentiane Venture.   

Abstract

This study aimed at developing and evaluating a new method for the fast and reliable identification of body segment inertial parameters with a planar model using affordable sensors. A Kinect sensor, with a new marker-based tracking system, and a Wii balance board were used as an affordable and portable motion capture system. A set of optimal exciting motions was used in a biofeedback interface to identify the body segment parameters. The method was validated with 12 subjects performing various standardized motions. The same dynamometric quantities estimated both with the proposed system and, as a reference, with a laboratory grade force-plate were compared. The results showed that the proposed method could successfully estimate the resultant moment and the vertical ground reaction force (rms errors less than 8 Nm and 12 N, respectively). Finally, when local segment values were artificially varied, the proposed method was able to detect and estimate the additional masses accurately and with an error of less than 0.5 Kg, contrary to values generated with commonly used anthropometric tables.

Mesh:

Year:  2015        PMID: 25751867     DOI: 10.1109/TNSRE.2015.2405087

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  3 in total

1.  Classification of K-Pop Dance Movements Based on Skeleton Information Obtained by a Kinect Sensor.

Authors:  Dohyung Kim; Dong-Hyeon Kim; Keun-Chang Kwak
Journal:  Sensors (Basel)       Date:  2017-06-01       Impact factor: 3.576

2.  Center of pressure based segment inertial parameters validation.

Authors:  Clint Hansen; Nasser Rezzoug; Philippe Gorce; Brice Isableu; Gentiane Venture
Journal:  PLoS One       Date:  2017-06-29       Impact factor: 3.240

3.  An Online Method to Detect and Locate an External Load on the Human Body with Applications in Ergonomics Assessment.

Authors:  Marta Lorenzini; Wansoo Kim; Elena De Momi; Arash Ajoudani
Journal:  Sensors (Basel)       Date:  2020-08-10       Impact factor: 3.576

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.