About Giovanni Bellusci, Ph.D.
Giovanni Bellusci joined Xsens in 2010, where he is currently responsible for the technology developments for the overall products portfolio and for IP generation. He has over a decade of experience in the field of signal processing, sensor fusion, motion tracking algorithms and corresponding applications, and has authored several technical papers and patents in the field. Giovanni holds a M.Sc. Degree in Electrical Engineering from the University of Pisa, Italy, and a Ph.D. Degree in Digital Communications and Signal Processing from the Delft University of Technology, The Netherlands.
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About Sanjay Bhandari, Ph.D.
Dr. Bhandari is CTO & Senior Vice President at mCube and is responsible for planning, execution and growth of mCube’s Technology & product roadmap. mCube, founded in 2009, has developed single chip CMOS+MEMS inertial sensors with disruptive technology to create world’s smallest inertial sensors for mobile & IoT market. At mCube, Dr. Bhandari has managed global teams working on MEMS, ASIC and systems design for over 7 years and has driven mCube’s product development from concept to high volume production. Dr. Bhandari was instrumental in mCube’s acquisition of Xsens in September 2017 which expands the product portfolio of combined mCube-Xsens entity from unique sensor components to 10DoF industrial sensor modules and complete human motion monitoring solutions.
Dr. Bhandari has more than 25 years of experience in all areas of electronic product design, development and commercialization and has worked for aggressive start-up companies as well as billion-dollar global leaders. Dr. Bhandari previously served as Vice President of Engineering at GTronix Inc. which was acquired by National Semiconductor in 2010. Prior to GTronix, Dr. Bhandari served as Senior Director at Ikanos Communications and contributed to the successful IPO of Ikanos in 2005. He has also held senior engineering and management positions at ST Micro and Philips Semiconductors (NXP).
Dr. Bhandari received his BSEE from the College of Engineering, Pune, his MSEE from Indian Institute of Technology, Delhi, and his Ph.D. from the Indian Institute of Technology, Bombay. He attended the Executive management program at Stanford University in 2008. Dr. Bhandari has given technical presentations & invited talks at many International conferences and leading universities. He has published numerous technical papers and holds 16 US patents in area of Sensors, circuits and system design.
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Abstract
Human motion is a rich source of information that can be used to understand behaviors and skills, prevent injuries and incorrect habits, and monitor and improve physical performance. Possible application areas include sports and fitness, ergonomics, gaming, or health and rehabilitation. In this presentation, wearable solutions for 3D full body human motion capture based on inertial and magnetic field sensing, will be introduced. It will be shown how latest advances in statistical state estimation and numerical optimization algorithms, in combination with use of background calibration routines, complex biomechanical models, and innovative sensor fusion and signal processing frameworks, can provide solutions to typical limitations of current technologies. We will present how highly accurate and consistent full body human motion tracking is possible in any environment using consumer-grade, low-power, inexpensive, accelerometer and gyroscope sensors, which currently are used only for simple step counting and coarse activity classification. These advancements represent a major step towards a truly seamless and pervasive use of wearable inertial sensing technology, empowering the user with a “sixth sense”: rich, quantitative, real-time information of motion available at any time. Monolithic CMOS plus MEMS 3D integration technology has produced miniaturization of sensors to the size of grain of sand and offer potential for embedding inertial sensors in clothing and accessories. This miniaturization together with ultra-low power and sensor fusion algorithms, are expected to provide solutions for next generation wearable technologies that will help consumers with advanced kinesiological information with ease of use to enhance their daily lives, health and productivity.
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