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One important application of Body Sensor Networks is action recognition. Action recognition often implicitly requires partitioning the sensor data into intervals, then labeling the partitions according to the actions each represents or as a non-action. The temporal partitioning stage is called segmentation and the labeling is called classification. While many effective methods exist for classification,...
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...
Recent years have witnessed a large influx of applications in the field of cyber–physical systems. An important class of these systems is body sensor networks (BSNs) where lightweight embedded processors and communication systems are tightly coupled with the human body. BSNs can provide researchers, care providers and clinicians access to tremendously valuable information extracted from data that...
Body Sensor Networks (BSN) provide a way to gather continuous observations of human movements, which has a potential of improving medical care quality, and enabling continuous remote patient monitoring. Despite their potential, BSNs face serious werability constraints. Energy optimization is essential since werability is most affected by the battery size of the device. In this paper, we introduce...
Wearable sensor nodes are highly constrained in terms of size, and, as a result, battery size and capacity. During a real time data collection, sensor nodes can communicate data continuously, however, this may reduce the system lifetime. Hence, we suggest an intelligent data collection algorithm that screens the sensor data and transmits only the segments of sensor data that might be of interest....
Employment of BSN-based technologies in real world scenarios requires a flexible infrastructure at both hardware and software level. In this paper, we emphasize how the use of SPINE (Signal Processing In-Node Environment), a software framework for BSN, supports the development of heterogeneous health-care applications based on reusable subsystems. One of the main goal of SPINE is to provide a flexible...
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