Project Area B

Sensor signal / data processing and transfer

Project Area B researches innovative methods and solutions for efficient sensor signal processing and transfer. All parts of the processing chain such as the sampling of the high-dimensional, continuous, physical signals, the efficient source coding of the scanned sensor values, the energy-saving mobile sensor data transfer and the visualization are addressed.

Specifically, the compressive sampling of 6D radar data is being researched in sub project B03 in order to shorten the recording time of empatho-kinaesthetic radar sensors. For this purpose, the common sparseness of the location and motion data is used and the radar test signals are optimized and adapted with regard to the compressive scanning. In B01 an efficient source coding method for multimodal body shell camera data is explored, which, similar to the mp3 format for audio data, enables efficient compressed transmission and storage of the human body shell data including their motion. For this purpose, the spatial correlation of the depth information and the temporal coherence of the movement should be used in order to reduce the data volume by at least two orders of magnitude. Innovative protocols and algorithms for energy-efficient reference signal and electromyography (EMG) sensor data transmission are researched in B02. In order to meet the application-related, stringent requirements for energy efficiency, the joint design of reference and data signals as well as the integration of concepts for local energy generation are developed. Finally, B04 explores the visualization of motion sequences based on a biomechanical model. Derived states of the biomechanical model make the sensor signals easier to interpret for medical professionals, whereby visualizations should also be generated for patients that support communication. Important research aspects are the spatial registration and deformation of the multimodal sensor data and the biomechanical model as well as the integrated representation of these components.

Sub Projects

The aim of the subproject is to develop a source coding method for multimodal body envelope data that enables efficient transmission of the human body envelope including its motion. The spatial correlation of the depth signals, the temporal coherence of the human motion and the interconnection dependencies between micro-doppler aperture synthesis radar data and depth signals are to be used for the coding. Depending on the reconstruction accuracy of the biomechanical and psychomotor applications in the CRC, a reduction of the data volume by at least two orders of magnitude is expected.

 

 

Suitable analytical and data-based models for the hardware components and signal processing blocks of the EmpkinS beacons and the base stations are developed for resource allocation. Based on these models, optimization problems are formulated and resource allocation protocols and algorithms are designed based on their solutions. Subsequently, the most promising resource allocation concepts are implemented, verified and further refined in an experimental system.

 

First, a synthetic data model is created. In cooperation with the sub-projects A01, A04, D04 andD05, this model will be validated and adapted, and replaced by real measurement data as soon as they are available. Based on this, various methods for improving compressive sensing will be researched in order to reduce the measurement time of image-based radar technology in EmpkinS: distributed compressive sensing, adaptive compressive sensing and radar test signals optimized for compressive sensing.

 

 

In sub-project B04, innovative methods for the visualization of movement sequences that were recorded with various empathokinesthetic sensors and/or for which a biomechanical simulation was carried out are being researched. The focus is on visualizations and the extraction of features that support medical interpretation and diagnosis.