Application of Sensors in Intelligent Clothing Design

In order to study the application of sensors in intelligent clothing design, the artificially intelligent cutting-edge technology -machine learning method was proposed to combine a variety of signals of non-contact sensors in several different positions. Higher accuracy was achieved, while maintaining the comfort brought by a non-contact sensor. The experimental results showed that the proposed strategy focused on the combination of clothing design technology and artificial intelligence technology. As a result, without changing the sensor materials, it enhances the comfort and precision of clothing, eliminates the comfort reduced by sensor close to the skin, and transforms inaccurate measurement into accurate measurement.

[1]  Chris D. Nugent,et al.  Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: a systematic review and meta-analysis , 2017, International Journal of Behavioral Nutrition and Physical Activity.

[2]  Xu Zhang,et al.  Random Forest-Based Recognition of Isolated Sign Language Subwords Using Data from Accelerometers and Surface Electromyographic Sensors , 2016, Sensors.

[3]  Paul Lukowicz,et al.  From Smart Clothing to Smart Table Cloth: Design and Implementation of a Large Scale, Textile Pressure Matrix Sensor , 2014, ARCS.

[4]  Zhen Li,et al.  An exploratory study on a chest-worn computer for evaluation of diet, physical activity and lifestyle. , 2015, Journal of healthcare engineering.

[5]  Sumit Mandal,et al.  Thermal sensors for performance evaluation of protective clothing against heat and fire: a review , 2015 .

[6]  Kaveh Pahlavan,et al.  Enlighten Wearable Physiological Monitoring Systems: On-Body RF Characteristics Based Human Motion Classification Using a Support Vector Machine , 2016, IEEE Transactions on Mobile Computing.

[7]  Roy Phitayakorn,et al.  A blinded assessment of video quality in wearable technology for telementoring in open surgery: the Google Glass experience , 2015, Surgical Endoscopy.

[8]  Jeng-Shyang Pan,et al.  Development of a Wearable Motor-Imagery-Based Brain–Computer Interface , 2016, Journal of Medical Systems.

[9]  Ilker Demirkol,et al.  Has Time Come to Switch From Duty-Cycled MAC Protocols to Wake-Up Radio for Wireless Sensor Networks? , 2016, IEEE/ACM Transactions on Networking.

[10]  Adam Witkowski,et al.  First-in-Man Computed Tomography-Guided Percutaneous Revascularization of Coronary Chronic Total Occlusion Using a Wearable Computer: Proof of Concept. , 2016, The Canadian journal of cardiology.