CEO, Sensing Tex
Mr. Ridao founded Sensing Tex and became Chief Executive Officer in 2010. He served as the co-founder of three companies in the field of engineering and technology. Holding over seventeen years of experience in the business of textile and electronic technology, Mr. Ridao is an inventor, holds some patents, has lectured worldwide, published several articles, and has won several awards at both technology and business level. On top of Mr. Ridao’s achievement of receiving many high degrees Pre-PhD (UPC, Barcelona Spain 2006); Master Physics (UB, Barcelona Spain 2003); Master Textile Engineering (FH Reutlingen Germany 1999); (UPC, Barcelona Spain 1998), he has acquired academic training completed specifically within the field of entrepreneurship, leadership, and management. This training was done at the business schools of IESE Business School (Learning to Grow Executive Program) and La Salle Business School (Startup Catalonia Program)
Miguel has a passion for innovation in Smart Textiles, he thinks that the future of textiles is not what it will be is about what we love to build and work
- Sensing Health, Sensing Mats and Smart Textiles for Preventive Care of Bedridden and Low Mobility Patients
- The presentation will introduce Sensing Health, a continuous monitoring Product and Service across the Care continuum from home to Hospitals that provides early detection to help lower risk and improve Bedridden and Low mobility patient care while reducing costs. The Products have been developed thanks to the eTextiles technology of stretchable circuits and Sensing Mat and Sensing Wear Platforms from Sensing Tex and the latest technology to analyze the raw data based on machine learning and AI. The products are systems developed for body pressure mapping to recognize body movement, postural analysis and Bio signals in bedding, seating applications in a non invasive way. Although the platform allows to connect and integrate other sensors.The conference will describe the different sensors and how they are textile printed and built in the same manufacturing process, the architecture of the whole system and how fully printed eTextiles can be implemented in Large Area non invasive sensors. Application of machine learning to Raw data of the textile sensors will be also explored.