Publications (2)1.52 Total impact
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Article: From Modeling to Implementation of Virtual Sensors in Body Sensor Networks
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ABSTRACT: Body Sensor Networks (BSNs) represent an emerging technology which has received much attention recently due to its enormous potential to enable remote, real-time, continuous and non-invasive monitoring of people in health-care, entertainment, fitness, sport, social interaction. Signal processing for BSNs usually comprises of multiple levels of data abstraction, from raw sensor data to data calculated from processing steps such as feature extraction and classification. This paper presents a multi-layer task model based on the concept of Virtual Sensors to improve architecture modularity and design reusability. Virtual Sensors are abstractions of components of BSN systems that include sensor sampling and processing tasks and provide data upon external requests. The Virtual Sensor model implementation relies on SPINE2, an open source domain-specific framework that is designed to support distributed sensing operations and signal processing for wireless sensor networks and enables code reusability, efficiency, and application interoperability. The proposed model is applied in the context of gait analysis through wearable sensors. A gait analysis system is developed according to a SPINE2-based Virtual Sensor architecture and experimentally evaluated. Obtained results confirm that great effectiveness can be achieved in designing and implementing BSN applications through the Virtual Sensor approach while maintaining high efficiency and accuracy.IEEE Sensors Journal 04/2012; · 1.52 Impact Factor -
Conference Proceeding: Implementation of virtual sensors in body sensor networks with the SPINE framework
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ABSTRACT: Signal processing for body sensor networks usually comprises multiple levels of data abstraction, from raw sensor data to data calculated from processing steps such as feature extraction and classification. This paper presents a multi-layer task model based on the concept of virtual sensors (VS) to improve architecture modularity and design reusability. In our pilot application of gait parameter extraction, VS are abstractions of components of BSN classification systems that include sensor sampling and processing tasks and provide data upon external requests analogous to the function of physical sensors. The paper presents an extension of the SPINE framework including a new buffer management scheme that facilitates the VS implementation.Industrial Embedded Systems, 2009. SIES '09. IEEE International Symposium on; 08/2009
