Philipp Schonle

TL;DR: This paper implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption.

TL;DR: VivoSoC is a system-on-chip realized in 130-nm CMOS for miniaturized medical instrumentation as used in mobile health devices or implantable telemetry systems for animal experiments and exemplarily demonstrated on preliminary work on implantable PPG-based vital signs monitoring.

TL;DR: A reconfigurable successive approximation register (SAR) ADC implemented in 130 nm CMOS that resolves 5-14 bit with a maximum achievable effective number of bits (ENOB) of 13.5 using non-subtractive dither is presented.

TL;DR: Results reveal a link between nociceptors and immune cells, which might have implications for the treatment of inflammation and an optogenetic study shows that activation of pain-triggering sensory neurons induces an immune response.

TL;DR: The performance of the proposed Electromyography pattern recognition system matches state-of-the-art high-end active sensors, opening the way to the development of affordable and accurate wearable devices.