Cooperative Sensors: A Disruptive Approach for Wearable Medical Devices
Great America Ballroom K
10:10 - 10:35
Compared to state-of-the-art medical monitoring systems, cooperative sensors allow comprehensive measurements of physiological signals during daily activities, including sleep, and are ideal for outpatients suffering from lung and heart diseases. Cooperative sensors are excellent to manage comorbidities, because the same sensors can simultaneously measure biopotential, impedance, skin temperature, SpO2, blood pressure and human kinetics.
Speaker Biography (Jens Arnulf Krauss)
Jens Krauss received his Master in Engineering Sciences in 1991 at the Swiss Federal Institute of Technology (ETHZ), followed by a two-year research stage at the Politecnico di Milano, Italy. Back to ETHZ, Mr Krauss lead the biomechanical software team of ESA's human spaceflight Mission TVD. Mr Krauss joined CSEM in 1996 and is heading today the Systems Division with a 100+ scientist and engineers in its strategic Medical Device Technology and Scientific Instrumentation research activity. His expertise in the field of human vital signs monitoring and mobile patient health has led to a series of key patents, successful technology transfers and start-ups.
Company Profile (CSEM Centre Suisse d'Electronique et de Microtechnique SA)
CSEM is a private non-profit Swiss research organization and acts as a technology provider for the industrial sector. As a recognized RTO, CSEM develops innovative technology platforms and offers services from contract R&D to development of solutions for applications including medical, transport, energy, security, life sciences, and telecom. CSEM has been active in the wearable technology domain for 20+ years and its medical device technology is certified ISO 13485. It has long-term and widespread competencies in the development of low-power wireless sensors for human-monitoring applications comprising sensor electronics, signal processing and advanced feature extraction at the sensor level or in the cloud, big data analysis, and machine learning.