FatoXtract a suit that may be useful in rehabilitation

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.

[1]  Krystof Litomisky Consumer RGB-D Cameras and their Applications , 2012 .

[2]  Thomas B. Schön,et al.  An optimization-based approach to human body motion capture using inertial sensors , 2014 .

[3]  Xi Chen Human Motion Analysis with Wearable Inertial Sensors , 2013 .

[4]  Sebastian Thrun,et al.  3D shape scanning with a time-of-flight camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  D. Roetenberg,et al.  Xsens MVN: Full 6DOF Human Motion Tracking Using Miniature Inertial Sensors , 2009 .

[6]  Sebastian Thrun,et al.  Real time motion capture using a single time-of-flight camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Micael S. Couceiro,et al.  A methodology for detection and estimation in the analysis of golf putting , 2012, Pattern Analysis and Applications.

[8]  S. Foix,et al.  Lock-in Time-of-Flight (ToF) Cameras: A Survey , 2011, IEEE Sensors Journal.

[9]  T Josefsson,et al.  A flexible high-precision video system for digital recording of motor acts through lightweight reflex markers. , 1996, Computer methods and programs in biomedicine.

[10]  Joachim Hornegger,et al.  Gesture recognition with a Time-Of-Flight camera , 2008, Int. J. Intell. Syst. Technol. Appl..

[11]  V. Macellari,et al.  CoSTEL: a computer peripheral remote sensing device for 3-dimensional monitoring of human motion , 1983, Medical and Biological Engineering and Computing.

[12]  Norbert Schmitz,et al.  A generic approach to inertial tracking of arbitrary kinematic chains , 2013, BODYNETS.

[13]  Jake K. Aggarwal,et al.  Human Motion Analysis: A Review , 1999, Comput. Vis. Image Underst..

[14]  Nuno M. Fonseca Ferreira,et al.  Combining discriminative spatiotemporal features for daily life activity recognition using wearable motion sensing suit , 2017, Pattern Analysis and Applications.

[15]  Huosheng Hu,et al.  Human motion tracking for rehabilitation - A survey , 2008, Biomed. Signal Process. Control..

[16]  Giancarlo Ferrigno,et al.  Elite: A Digital Dedicated Hardware System for Movement Analysis Via Real-Time TV Signal Processing , 1985, IEEE Transactions on Biomedical Engineering.

[17]  H. M. Schepers,et al.  Ambulatory assessment of human body kinematics and kinetics , 2009 .

[18]  R. Lange,et al.  Solid-state time-of-flight range camera , 2001 .

[19]  François Charpillet,et al.  Human activities recognition with RGB-Depth camera using HMM , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[20]  Masahiro Todoh,et al.  Gait posture estimation using wearable acceleration and gyro sensors. , 2009, Journal of biomechanics.