Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Link layer behavior of body area networks at 2.4 GHz
Proceedings of the 15th annual international conference on Mobile computing and networking
Common sense based joint training of human activity recognizers
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Mercury: a wearable sensor network platform for high-fidelity motion analysis
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Context-aware middleware for pervasive elderly homecare
IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
Object relevance weight pattern mining for activity recognition and segmentation
Pervasive and Mobile Computing
A distributed hierarchical structure for object networks supporting human activity recognition
MMNS'06 Proceedings of the 9th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services
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With the rapid advances of wearable sensors and wireless networks. There is a growing research interest in building Body Area Sensor Network (BSN) systems to support applications such as human activity recognition and daily health monitoring. The main challenges of building a BSN system include: First, the wearable sensor nodes are highly constrained in resources; Second, the sensor nodes are prong to failures; Third, the applications requires the sensors to work with high sampling rate which results in the heavy load on each sensor node. Beside the technical challenges, the usability of the system is also a critical issue when deployed into the the real-world environment. We present in this paper the lessons we learnt while building a real-world BSN system which aims at supporting real-time human activity recognition. We analyzed the challenges and problems in depth and proposed possible solutions. The conclusions we made in this paper can serve as the guidelines for building a BSN system in the future.