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FatoXtract a suit that may be useful in rehabilitation

Published: 20 June 2018 Publication History

Abstract

Kinematic analysis of human movement is very important in several areas, such as in sports (e.g., for athletic performance analysis), health (e.g., rehabilitation of people with motor disabilities) and others. The study of the kinematics of the human body involves several methods that resort to the analysis of several parameters that come from the movement. Important parameters to take into account are the acceleration, velocity and position (linear or angular) of the various articulations of the human body, which can be measured by sensors or through the analysis of repeated images obtained by camera. In this paper will be presented a suit that acquire the different position of human joints that will be useful in rehabilitation, FatoXtract. It is through the analysis of human movement that we can analyze whether the movement in rehabilitation is adequate or not.

References

[1]
J. K. Aggarwal and Q. Cai, "Human motion analysis: A review.," Computer vision and image understanding, vol. 73, no. 3, pp. 428--440, 1999.
[2]
H. Zhou and H. Hu, "Human motion tracking for rehabilitation - A survey," Biomedical Signal Processing and Control, vol. 3, no. 1, pp. 1--18, 2008.
[3]
M. Schepers, "Ambulatory assessment of human body kinematics and kinetics," PhD Thesis, 2009.
[4]
M. S. Couceiro, D. Portugal, N. Gonçalves, R. Rocha, J. M. A. Luz, C. M. Figueiredo and G. Dias, "A Methodology for Detection and Estimation in the Analysis of the Golf Putting," Pattern Analysis and Applications, vol. 16, no. 3, pp. 459--474, 2013.
[5]
V. Macellari, "CoSTEL: a peripherical remote sensing device for 3-dimensional monitoring of human motion," Medical ans Biological Engineering and Computing, vol. 21, no. 3, pp. 311--318, 1983.
[6]
G. Ferrigno and A. Pedotti, "ELITE: a digital dedicated hardware system for movement analysis via real-time TV signal processing," IEEE Transactions in Biomedical Engineering, pp. 943--950, 1985.
[7]
T. Josefsson, E. Nordh and P.-O. Eriksson, "A flexible high-precision viedo system for digital recording of motor acts through lightweight reflex markers," Computer methods and programs in biomedicine, vol. 49, no. 2, pp. 119--129, 1996.
[8]
K. Litomisky, "Consumer RGB-D Cameras and their Applications," Rapport technique, University of California, 2012.
[9]
A. Dubois and F. Charpille, "Human Activities Recognition with RGB-Depth camera using HMM," in In Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE, 2013.
[10]
V. Ganapathi, C. Plagemann, D. Roller and S. Thrun, "Real Time Motion Capture Real Using a Single Time-Of-Flight Camera," in IEEE Conference in Computer Vision and Pattern Recognition (CVPR), 2010.
[11]
R. Lange and P. Seitz, "Solid-State Time-of-Flight Range Camera," IEEE Journal of Quantum Electronics, vol. 37, no. 3, pp. 390--397, 2001.
[12]
D. Uebersax, "Gesture Recognition with a Time-of-Flight Camera," MSc Thesis, 2010.
[13]
S. Foix, G. Alenyà and C. Torras, "Lock-in Time-of-Flight (ToF) Cameras: A Survey," IEEE Sensors Journal, vol. 11, no. 9, pp. 1917--1926, 2011.
[14]
Y. Cui, S. Schuon, D. Chan, S. Thrun and C. Theobalt, "3D Shape Scanning with a Time-of-Flight Camera," in In Computer Vision and Pattern Recognition, 2010 IEEE Conference on, 2010.
[15]
X. Chen, "Human Motion Analysis with Wearable Inertial," PhD Thesis, Knoxville, 2013.
[16]
M. Miezal, G. Bleser, N. Schmitz and D. Stricker, "A generic approach to inertial tracking of arbitrary Kinematic chains," in In Proceedings of the 8th International Conference on Body Area Networks, 2013.
[17]
R. Takeda, S. Tadano, A. Natorigawa, M. Todoh and S. Yoshinari, "Gait posture estimation using wearable acceleration and gyrosensors," Journal of Biomechanics, vol. 42, no. 15, pp. 2486--2494, 2009.
[18]
D. Roetenberg, H. Luinge and P. Slycke, "Xsens MVN: full 6DOF human motion tracking using miniature inertial sensors," Xsens Motion Technologies BV, 2009.
[19]
M. Kok, J. D. Hol and T. B. Schön, "An optimization-based approach to human body motion capture using inertial sensors," in In 19th World Congress of the International Federation of Automatic Control (IFAC), South Africa, 2014.
[20]
J. P. Vital, D. R. Faria, G. Dias, M. S. Couceiro, F. Coutinho and N. M. Ferreira, "Combining Discriminative Spatio-Temporal Features for daily life activity recognition using wearable motion sensing suit," Pattern Analysis and Applications, vol. 20(4), pp. 1179--1194,2017.

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  • (2019)A new approach of developing games for motor rehabilitation using Microsoft Kinect2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH)10.1109/SeGAH.2019.8882457(1-6)Online publication date: Aug-2019

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    cover image ACM Other conferences
    DSAI '18: Proceedings of the 8th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion
    June 2018
    365 pages
    ISBN:9781450364676
    DOI:10.1145/3218585
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 20 June 2018

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    • (2019)A new approach of developing games for motor rehabilitation using Microsoft Kinect2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH)10.1109/SeGAH.2019.8882457(1-6)Online publication date: Aug-2019

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