Literature DB >> 28293869

An Intelligent Body Posture Analysis Model Using Multi-Sensors for Long-Term Physical Rehabilitation.

Chin-Feng Lai1, Ren-Hung Hwang2, Ying-Hsun Lai3.   

Abstract

Sensors can be installed on various body parts to provide information for computer diagnosis to identify the current body state. However, as human posture is subject to gravity, the direction of the force on each limb differs. For example, the directions of gravitational force on legs and trunk differ. In addition, each person's height and structure of limbs differs, hence, the acceleration and rotation resulted from such differences on force and length of the limbs of a person in motion would be different, and be presented by cases of different postures. Thus, how to present body postures through skeleton system equations, and achieve an long-term physical rehabilitation, according to the different limb characteristics of each person, is a challenging research issue. This paper proposes a novel scheme named as "Intelligent Body Posture Analysis Model", which uses multiple acceleration sensors and gyroscopes to detect body motion patterns. The effectiveness of the proposed scheme is proved by conducting a large number of practical experiments and tests.

Entities:  

Keywords:  Body posture analysis model; Intelligent healthcare system; Long-term physical rehabilitation

Mesh:

Year:  2017        PMID: 28293869     DOI: 10.1007/s10916-017-0708-5

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  5 in total

1.  Iterative extensions of the Sturm/Triggs algorithm: convergence and nonconvergence.

Authors:  John Oliensis; Richard Hartley
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2007-12       Impact factor: 6.226

2.  Low-rank matrix fitting based on subspace perturbation analysis with applications to structure from motion.

Authors:  Hongjun Jia; Aleix M Martinez
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2009-05       Impact factor: 6.226

3.  Make3D: learning 3D scene structure from a single still image.

Authors:  Ashutosh Saxena; Min Sun; Andrew Y Ng
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2009-05       Impact factor: 6.226

4.  Motion compensated iterative reconstruction of a region of interest in cardiac cone-beam CT.

Authors:  A A Isola; A Ziegler; D Schäfer; T Köhler; W J Niessen; M Grass
Journal:  Comput Med Imaging Graph       Date:  2009-09-15       Impact factor: 4.790

5.  An Assessment of a Low-Cost Visual Tracking System (VTS) to Detect and Compensate for Patient Motion during SPECT.

Authors:  Joseph E McNamara; Philippe Bruyant; Karen Johnson; Bing Feng; Andre Lehovich; Songxiang Gu; Michael A Gennert; Michael A King
Journal:  IEEE Trans Nucl Sci       Date:  2008-06       Impact factor: 1.679

  5 in total

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