SPINE: a domain‐specific framework for rapid prototyping of WBSN applications

Wireless body sensor networks (WBSNs) enable a broad range of applications for continuous and real‐time health monitoring and medical assistance. Programming WBSN applications is a complex task especially due to the limitation of resources of typical hardware platforms and to the lack of suitable software abstractions. In this paper, SPINE (signal processing in‐node environment), a domain‐specific framework for rapid prototyping of WBSN applications, which is lightweight and flexible enough to be easily customized to fit particular application‐specific needs, is presented. The architecture of SPINE has two main components: one implemented on the node coordinating the WBSN and one on the nodes with sensors. The former is based on a Java application, which allows to configure and manage the network and implements the classification functions that are too heavy to be implemented on the sensor nodes. The latter supports sensing, computing and data transmission operations through a set of libraries, protocols and utility functions that are currently implemented for TinyOS platforms. SPINE allows evaluating different architectural choices and deciding how to distribute signal processing and classification functions over the nodes of the network. Finally, this paper describes an activity monitoring application and presents the benefits of using the SPINE framework. Copyright © 2010 John Wiley & Sons, Ltd.

[1]  Matt Welsh,et al.  CodeBlue: An Ad Hoc Sensor Network Infrastructure for Emergency Medical Care , 2004 .

[2]  Allen Y. Yang,et al.  DexterNet: An Open Platform for Heterogeneous Body Sensor Networks and its Applications , 2009, 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks.

[3]  Kamiar Aminian,et al.  Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly , 2003, IEEE Transactions on Biomedical Engineering.

[4]  Roozbeh Jafari,et al.  Implementation of virtual sensors in body sensor networks with the SPINE framework , 2009, 2009 IEEE International Symposium on Industrial Embedded Systems.

[5]  Ling Bao,et al.  Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.

[6]  Danail Stoyanov,et al.  Ambient and Wearable Sensor Fusion for Activity Recognition in Healthcare Monitoring Systems , 2007, BSN.

[7]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[8]  Fabio Bellifemine,et al.  Performance analysis of an activity monitoring system using the SPINE framework , 2009, 2009 3rd International Conference on Pervasive Computing Technologies for Healthcare.

[9]  Umakishore Ramachandran,et al.  DFuse: a framework for distributed data fusion , 2003, SenSys '03.

[10]  Daniel P. Siewiorek,et al.  Activity recognition and monitoring using multiple sensors on different body positions , 2006, International Workshop on Wearable and Implantable Body Sensor Networks (BSN'06).

[11]  Josef Kittler,et al.  Floating search methods in feature selection , 1994, Pattern Recognit. Lett..

[12]  Doug Simon,et al.  The squawk virtual machine: Java™ on the bare metal , 2005, OOPSLA '05.

[13]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[14]  Amy L. Murphy,et al.  Middleware to support sensor network applications , 2004, IEEE Network.

[15]  Chenyang Lu,et al.  Mobile agent middleware for sensor networks: an application case study , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[16]  Gaetano Borriello,et al.  A Practical Approach to Recognizing Physical Activities , 2006, Pervasive.

[17]  Gerhard Tröster,et al.  Titan: A Tiny Task Network for Dynamically Reconfigurable Heterogeneous Sensor Networks , 2007, KiVS.

[18]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[19]  Paolo Bonato,et al.  Using wearable sensors to measure motor abilities following stroke , 2006, International Workshop on Wearable and Implantable Body Sensor Networks (BSN'06).

[20]  Heikki Mannila,et al.  Principles of Data Mining , 2001, Undergraduate Topics in Computer Science.

[21]  Carlos André Guimarães Ferraz,et al.  Mires: a publish/subscribe middleware for sensor networks , 2005, Personal and Ubiquitous Computing.

[22]  Daniel A. Sadilek.  Prototyping Domain-Specific Languages for Wireless Sensor Networks , 2007 .

[23]  Daniel A. Sadilek.  Domain-Specific Languages for Wireless Sensor Networks , 2008, Modellierung.