Customized Body-attached Sensor Network for Real-Time Motion Sensory Information
The objective is to systematically elaborate a methodology to synthesize optimized biomimetic body-attached sensor networks (BASNs) for real-time capturing of basic gesture components and complex gestures. Therefore, we elaborate a valid methodology for synthesizing task-specific BASNs. We investigate a methodology to design a synthesis process for innovative sensors based on polymer carbon nanocomposites (PCN) for a BASN. We investigate approaches to design compatible and highly flexible signal pre-processing sensor nodes. We develop a hybrid methodology for a simultaneous feature selection and gesture classification. Finally, we elaborate a simulator for designing the most suitable BASNs