EmpkinS

Motivation

The German Research Foundation (DFG) is funding a joint project called “Empatho-Kinaesthetic Sensor Technology – Sensor Techniques and Data Analysis Methods for Empatho-Kinaesthetic Modeling and Condition Monitoring,” or EmpkinS for short. It is an interdisciplinary project with the aim of advancing patient-centered digital diagnosis and therapy options in medicine and psychology. This goal is achieved through the non-invasive recording of high-resolution human motion parameters using wave- and radio-based sensor technologies and the algorithmic reconstruction of physiological and behavioral states based on the recorded motion data using body function models.

In medicine and psychology, accurate analysis of physiological and behavioral states and body functions is often necessary for efficient diagnosis and therapy of patients. This requires information about muscle activity as well as its precise localization. State-of-the-art systems for analyzing human movements and radio-based sensor localization systems suffer from numerous compromises in development, such as measurement accuracy and limited functionality due to space constraints, energy efficiency for longer battery life, biocompatibility, and form factor for biomedical telemetry applications, to name a few.

Goals and Procedure

This project aims to develop a 61 GHz mm-wave transceiver chip in a 22 nm FDSOI (Fully Depleted Silicon-On-Insulator) -CMOS (Complementary Metal Oxide Semiconductor) process for an extremely energy-efficient and localizable, non-invasive biomedical wireless electromyography (EMG) transponder. This enables a novel approach to capturing surface EMG data in real time while simultaneously localizing the source muscle with high precision in the sub-mm range. The research task focuses primarily on the investigation, design, verification, and characterization of energy-efficient mixed-signal mm-wave front-end and baseband circuits for the transmitter in order to meet the transponder's requirements for low power consumption and carrier stability. The transmitter chip is to be integrated into an EMG sensor platform, which is to be developed in a miniaturized, flexible, and energy-efficient manner and equipped with multiple EMG channels. The sensor platform will then be evaluated in test series on test subjects, e.g., on the face or legs, to analyze facial expressions and gait.

Currently, there is a discrete version of the EMG sensor system with a discretely constructed 24 GHz transmitter unit and an initial version of a 61 GHz transmitter chip, which will be integrated into the EMG sensor system and evaluated. The next steps include integrating the EMG sensor technology onto a flexible substrate using the FlexIC process, expanding the transmitter chip into a transceiver chip, and heterogeneously integrating the EMG sensor technology and transceiver chip onto a flexible substrate.