Intelligent clothing for automated recognition of human physical activities in free-living environment

This paper presents an intelligent clothing framework for human daily activity recognition using a single waist-worn tri-axial accelerometer sensor coupled with a robust pattern recognition system. The activity recognition algorithm is realized to distinguish six different physical activities through three major steps: acceleration signal collection/pre-processing, wavelet-based principle component analysis, and a support vector machine classifier. The proposed activity recognition method has been experimentally validated through two batches of trials with an overall mean classification accuracy of 95.25 and 94.87%, respectively. These results suggest that the intelligent clothing is not only able to learn the activity patterns but also capable of generalizing new data from both known and unknown subjects. This enables the proposed intelligent clothing to be applied in a comfortable and in situ assessment of human physical activities, which would open up new market segments to the textile industry.

[1]  Toni Giorgino,et al.  Sensor Evaluation for Wearable Strain Gauges in Neurological Rehabilitation , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[2]  Zedong Nie,et al.  A Wireless Biomedical Signal Interface System-on-Chip for Body Sensor Networks , 2010, IEEE Transactions on Biomedical Circuits and Systems.

[3]  Chin-Feng Lai,et al.  Detection of Cognitive Injured Body Region Using Multiple Triaxial Accelerometers for Elderly Falling , 2011, IEEE Sensors Journal.

[4]  Marcos Duarte,et al.  Support vector machines for detecting age-related changes in running kinematics. , 2011, Journal of biomechanics.

[5]  N. Malmurugan,et al.  Neural classification of lung sounds using wavelet coefficients , 2004, Comput. Biol. Medicine.

[6]  Jungchae Kim,et al.  Review of Daily Physical Activity Monitoring System Based on Single Triaxial Accelerometer and Portable Data Measurement Unit , 2010 .

[7]  Li Li,et al.  Design of Intelligent Garment with Transcutaneous Electrical Nerve Stimulation Function Based on the Intarsia Knitting Technique , 2010 .

[8]  Masatoshi Ishikawa,et al.  Human gait estimation using a wearable camera , 2011, 2011 IEEE Workshop on Applications of Computer Vision (WACV).

[9]  D. De Rossi,et al.  Development of a novel algorithm for human fall detection using wearable sensors , 2008, 2008 IEEE Sensors.

[10]  Luca Benini,et al.  Accelerometer-based fall detection using optimized ZigBee data streaming , 2010, Microelectron. J..

[11]  L. Klingbeil,et al.  Detecting walking activity in cardiac rehabilitation by using accelerometer , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[12]  Hailong Zhu,et al.  Support vector machine for classification of walking conditions using miniature kinematic sensors , 2008, Medical & Biological Engineering & Computing.

[13]  B. G. Celler,et al.  Classification of basic daily movements using a triaxial accelerometer , 2004, Medical and Biological Engineering and Computing.

[14]  Billur Barshan,et al.  Human Activity Recognition Using Inertial/Magnetic Sensor Units , 2010, HBU.

[15]  Ju Wang,et al.  PCA-based SVM for automatic recognition of gait patterns. , 2008, Journal of applied biomechanics.

[16]  Gerhard Tröster,et al.  Screen-printed Textile Transmission Lines , 2007 .

[17]  Hendrik Rogier,et al.  Influence of Relative Humidity on Textile Antenna Performance , 2010 .

[18]  Andrea Turcato,et al.  Predicting losses of balance during upright stance: evaluation of a novel approach based on wearable accelerometers , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[19]  Rosalind W. Picard,et al.  A Wearable Sensor for Unobtrusive, Long-Term Assessment of Electrodermal Activity , 2010, IEEE Transactions on Biomedical Engineering.

[20]  Maarit Kangas,et al.  Comparison of low-complexity fall detection algorithms for body attached accelerometers. , 2008, Gait & posture.

[21]  Billur Barshan,et al.  Classifying Human Leg Motions with Uniaxial Piezoelectric Gyroscopes , 2009, Sensors.

[22]  Hendrik Rogier,et al.  The Use of Textile Materials to Design Wearable Microstrip Patch Antennas , 2008 .

[23]  E K Antonsson,et al.  The frequency content of gait. , 1985, Journal of biomechanics.

[24]  S. Cerutti,et al.  Falls event detection using triaxial accelerometry and barometric pressure measurement , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[25]  David Harrison,et al.  The future design direction of Smart Clothing development , 2005 .

[26]  Shah Mostafa Khaled,et al.  Modeling Spammer Behavior: Naïve Bayes vs. Artificial Neural Networks , 2009, 2009 International Conference on Information and Multimedia Technology.

[27]  A. Goris,et al.  Detection of type, duration, and intensity of physical activity using an accelerometer. , 2009, Medicine and science in sports and exercise.

[28]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[29]  H. Rogier,et al.  Flexible textile based antennas , 2010 .

[30]  Sundaresan Jayaraman,et al.  Smart Textiles: A Platform for Sensing and Personalized Mobile Information-processing , 2003 .

[31]  Hyun-Seung Cho,et al.  Textile electrodes of jacquard woven fabrics for biosignal measurement , 2010 .

[32]  Yeh-Liang Hsu,et al.  A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring , 2010, Sensors.