Low-complexity energy proportional posture/gesture recognition based on WBSN

Alexis Aulery 1 Jean-Philippe Diguet 1 Olivier Sentieys 2 Christian Roland 3
1 Lab-STICC_UBS_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
2 CAIRN - Energy Efficient Computing ArchItectures with Embedded Reconfigurable Resources
Inria Rennes – Bretagne Atlantique , IRISA-D3 - ARCHITECTURE
3 Lab-STICC_UBS_CACS_IAS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : This paper addresses the issue of low-power posture and gesture recognition in indoor or outdoor environments without any additional equipment. For applications based on predefined postures such as environment control and physical rehabilitation, we show that low cost and fully distributed solutions, that minimize radio communications, can be efficiently implemented. Considering that radio links provide distance infor- mation, we also demonstrate that the matrix of estimated inter-node distances offers complementary information that allows for the reduction of communication load. Our results are based on a simulator that can handle various measured input data, different algorithms and various noise models. Simulation results are useful and used for the development of real-life prototype.
Document type :
Conference papers
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https://hal.archives-ouvertes.fr/hal-01163581
Contributor : Jean-Philippe Diguet <>
Submitted on : Monday, June 15, 2015 - 9:17:13 AM
Last modification on : Monday, February 25, 2019 - 3:14:15 PM

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  • HAL Id : hal-01163581, version 1

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Alexis Aulery, Jean-Philippe Diguet, Olivier Sentieys, Christian Roland. Low-complexity energy proportional posture/gesture recognition based on WBSN. 12th IEEE Int. Conference on Wearable and Implantable Body Sensor Networks (BSN), Jun 2015, MIT, Cambridge, United States. ⟨hal-01163581⟩

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