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. 2016 Oct 18;16(10):1724.
doi: 10.3390/s16101724.

A Vision-Based Approach for Building Telecare and Telerehabilitation Services

Angela Barriga  1 , José M Conejero  2 , Juan Hernández  3 , Elena Jurado  4 , Enrique Moguel  5 , Fernando Sánchez-Figueroa  6
Affiliations

A Vision-Based Approach for Building Telecare and Telerehabilitation Services

Angela Barriga et al. Sensors (Basel). .

Abstract

In the last few years, telerehabilitation and telecare have become important topics in healthcare since they enable people to remain independent in their own homes by providing person-centered technologies to support the individual. These technologies allows elderly people to be assisted in their home, instead of traveling to a clinic, providing them wellbeing and personalized health care. The literature shows a great number of interesting proposals to address telerehabilitation and telecare scenarios, which may be mainly categorized into two broad groups, namely wearable devices and context-aware systems. However, we believe that these apparently different scenarios may be addressed by a single context-aware approach, concretely a vision-based system that can operate automatically in a non-intrusive way for the elderly, and this is the goal of this paper. We present a general approach based on 3D cameras and neural network algorithms that offers an efficient solution for two different scenarios of telerehabilitation and telecare for elderly people. Our empirical analysis reveals the effectiveness and accuracy of the algorithms presented in our approach and provides more than promising results when the neural network parameters are properly adjusted.

Keywords: 3D-cameras; fall detection; healthcare; neural network; telerehabilitation.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure A1
Figure A1
Sitting posture detection.
Figure A2
Figure A2
Standing posture detection.
Figure A3
Figure A3
Arm outstretched detection.
Figure A4
Figure A4
Left arm raised detection.
Figure B1
Figure B1
Normal situation detection.
Figure B2
Figure B2
Abnormal situation detection.
Figure B3
Figure B3
Urgent situation detection.
Figure B4
Figure B4
Urgent situation detection.
Figure 1
Figure 1
Body joint positions.
Figure 2
Figure 2
Example of artificial neurons grouped into layers.
Figure 3
Figure 3
Standing vs. sitting postures.
Figure 4
Figure 4
System architecture.
See this image and copyright information in PMC

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