KORVEKSiS: Compensated position vectors for the characterization of seismocardiographic signals using integrated sensors

• Applicants: Professor Dr. Urs-Vito Albrecht; Dr.-Ing. Ulf Kulau
• Subject Area: Biomedical Systems Technology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 542151450

KORVEKSiS addresses the overarching research question of how seismocardiographic signals (SCG) can be uniquely characterized with resource-limited sensor technology in order to offer cost-effective portable alternatives to classical imaging methods for diagnostics and monitoring in medical care, prevention and health promotion in the future. In the current project, 3D accelerometers will be fused with 3D gyroscopes, through which compensated location vectors that are configurable in their orientation will be derived. This enables a location-based interpretation of the SCG signals based on the sensor position. In KORVEKSiS, previously neglected measurement uncertainties of the reference systems (artifacts, latencies, jitter, drift) are taken into account. Compensated location vectors provide a more stable and standardizable basis for the assignment of characteristic cardiac physiological signals of the reference systems applied in translational models. Methods for integration for resource-constrained sensing are being used as a basis for future implementations on wearable systems. The work program initially envisages the development and evaluation of a miniaturized sensor platform with fused accelerometric and gyroscopic sensor technology. Due to the lack of standards, a test infrastructure with previously validated components will be set up to allow synchronous data collection from SCG and reference systems. On this basis, baseline data will be collected in a human experiment as an exercise and test dataset for the entire project. This database is used to derive compensated SCG location vectors that are subsequently characterized using data from the reference systems of echocardiography, electrocardiography and phonocardiography. In parallel, translational models will be derived and characterization will be integrated on resource-constrained sensing systems. In summary, a portfolio of methods will be available as a scientific basis for further research aimed at enabling cost-effective wearables with a wide range of applications for outpatient diagnostics and monitoring in prevention, health promotion and diagnostics.

• DFG Programme: Research Grants