Reverse recognition of body postures using on-body radio channel characteristics

The problem of posture detection is of considerable significance for assisted living (AL). In most cases, radio channel models for wireless body area network (WBANs) are fixed when a specific body posture is considered. To the best of the authors' knowledge, little work has been done on the reverse body posture information extraction using WBAN radio channel characteristics. This study aims to classify human postures from on-body narrowband wireless channel information. It is demonstrated that by applying the random forest (RF) classification technique, the action of the human body can be detected. The classification error is perfectly acceptable for RF algorithm. Two propagation environments were compared and the results indicate that the classification error is less in the anechoic chamber (21.39%). In summary, this study provides a novel approach to detect human body postures by using body-centric wireless channel information, and will be beneficial for AL.

[1]  Mengyuan Li,et al.  Using the Kinect to detect potentially harmful hand postures in pianists , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  Yang Hao,et al.  Antennas and Radio Propagation for Low-power Cooperative Body Centric Wireless Networks , 2011 .

[3]  Matjaz Gams,et al.  Accelerometer Placement for Posture Recognition and Fall Detection , 2011, 2011 Seventh International Conference on Intelligent Environments.

[4]  David H. Wolpert,et al.  An Efficient Method To Estimate Bagging's Generalization Error , 1999, Machine Learning.

[5]  Soraia Raupp Musse,et al.  Automatic Detection of 2D Human Postures Based on Single Images , 2011, 2011 24th SIBGRAPI Conference on Graphics, Patterns and Images.

[6]  Chokri Ben Amar,et al.  A novel approach for drowsy driver detection using head posture estimation and eyes recognition system based on wavelet network , 2014, IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications.

[7]  N Gamage,et al.  Towards real-time sign language analysis via markerless gesture tracking , 2009, 2009 IEEE Instrumentation and Measurement Technology Conference.

[8]  Rini Akmeliawati,et al.  Vision-based hand posture detection and recognition for Sign Language — A study , 2011, 2011 4th International Conference on Mechatronics (ICOM).

[9]  Octavian M. S. Dogarescu,et al.  Abnormal posture detection device with audible feedback , 2011, 2011 7TH INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING (ATEE).

[10]  Rohit Verma,et al.  Vision based hand gesture recognition using finite state machines and fuzzy logic , 2009, 2009 International Conference on Ultra Modern Telecommunications & Workshops.

[11]  T. Limpiti,et al.  Wireless intelligent fall detection and movement classification using fuzzy logic , 2012, The 5th 2012 Biomedical Engineering International Conference.

[12]  Baharak Shakeri Aski,et al.  Intelligent video surveillance for monitoring fall detection of elderly in home environments , 2008, 2008 11th International Conference on Computer and Information Technology.

[13]  G. Rozinaj,et al.  Gesture identification for system navigation in 3D scene , 2012, Proceedings ELMAR-2012.

[14]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[15]  Robert Tibshirani,et al.  Bias, Variance and Prediction Error for Classification Rules , 1996 .

[16]  D. R. Sanchez,et al.  Design of a EMG wireless surface EMG 6 channels , 2013, 2013 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC).

[17]  Soraia Raupp Musse,et al.  Making Them Alive , 2011, 2011 Brazilian Symposium on Games and Digital Entertainment.

[18]  Alex Mihailidis,et al.  A Survey on Ambient-Assisted Living Tools for Older Adults , 2013, IEEE Journal of Biomedical and Health Informatics.

[19]  Ahmed Manasrah,et al.  An Investigation Towards Worms Detection Approaches over Network , 2011, 2011 UkSim 13th International Conference on Computer Modelling and Simulation.

[20]  A. Hussain,et al.  Shock Posture for Shape Matching , 2006, 2006 2nd International Conference on Information & Communication Technologies.

[21]  Rini Akmeliawati,et al.  A hybrid method using haar-like and skin-color algorithm for hand posture detection, recognition and tracking , 2010, 2010 IEEE International Conference on Mechatronics and Automation.

[22]  Madhat Alsoos,et al.  Posture independent model for hand detection and tracking , 2013, 2013 6th International Conference on Human System Interactions (HSI).

[23]  L. Breiman.  OUT-OF-BAG ESTIMATION , 1996 .

[24]  A. Uribe-Quevedo,et al.  Seated Tracking for Correcting Computer Work Postures , 2013, 2013 29th Southern Biomedical Engineering Conference.