The Deutsche Forschungsgemeinschaft (DFG) funded Collaborative Research Centre (CRC) project titled “Empathy-Kinaesthetic Sensor Technology – Sensor Techniques and Data Analysis Methods for Empathy-Kinaesthetic Modeling and Condition monitoring,” a.k.a. EmpkinS is an interdisciplinary project that aims to push towards patient-centric digital diagnostics and therapeutic options in medicine and psychology. This goal is achieved by remote capturing the high-resolution human motion parameters non-invasively using wave/radio-based sensor technologies and performing algorithmic reconstruction of the physiological and behavioral states based on the captured motion data using body function models.

In the field of medicine and psychology, accurate analysis of physiological, behavioral states and body functions is often required for efficient patient diagnosis and therapy. This requires both the muscle activity information and its precise location source. State-of-the-art human motion analysis systems and radio based sensor localization systems suffer from multiple levels of design trade-offs such as measurement accuracy & limited functionality due to areal constraints, power efficiency for extended battery lifetime, bio-compatibility & form-factor required for biomedical telemetry applications, to name a few. In this project, a 61 GHz mm-wave transmitter chip is to be designed in 22nm FDSOI (Fully Depleted Silicon-On-Insulator) CMOS (Complementary Metal Oxide Semiconductor) process for extremely energy-efficient & localizable, non-invasive biomedical wireless EMG transponder. This facilitates a novel approach towards acquiring real-time surface EMG data while simultaneously achieving high-precision sub-mm accurate localization of the source muscle. The research task focuses primarily on the investigation, design, verification & characterization of mixed-signal energy-efficient mm-wave front end and base-band circuits for the transmitter to meet the low-power and carrier stability requirements of the transponder. The transmitter chip is to be integrated into an EMG sensor platform, which will be evaluated in test series on probands, e.g., in the face or on legs, to analyze facial expressions and gait.