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Human++: autonomous wireless sensors for body area networks

Human++: autonomous wireless sensors for body area networks,10.1109/CICC.2005.1568597,Bert Gyselinckx,Chris Van Hoof,Julien Ryckaert,Refet Firat Yazic

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Human++: autonomous wireless sensors for body area networks   (Citations: 42)
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This paper gives an overview of the results of BMEC's Human++ research program. This program aims to achieve highly miniaturized and autonomous sensor systems that enable people to carry their personal body area network. The body area network will provide medical, lifestyle, assisted living, sports or entertainment functions. It combines expertise in wireless ultra-low power communications, packaging, D integration technologies, MEMS energy scavenging techniques and low-power design techniques.
Conference: Custom Integrated Circuits Conference - CICC , 2005
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    • ...However, energy scavenging will only deliver small amounts of energy [5, 28]...

    Benoît Latré, et al. A survey on wireless body area networks

    • ...Indeed, micro-scale network nodes may require an average power consumption of around 140W [15, 6]. Furthermore, micro-robot peak power consumption is around 100mW [19], with average power consumption around 5-10mW [33, 41], with almost all of it dedicated to motion...

    Sanjeev J. Koppal, et al. Wide-angle micro sensors for vision on a tight budget

    • ...The operational clock frequency of the sensor nodes is dependent on the application scenario ranging from a few hundreds of KHz [2] to the tens of MHz range [3]...

    Vibhu Sharma, et al. A 4.4 pJ/Access 80 MHz, 128 kbit Variability Resilient SRAM With Multi...

    • ...Ultra-wideband (UWB) has been proposed as a technique to achieve ultra-low power consumption in many emerging applications such as wireless personal area network (WPAN) [1], unobtrusive health monitoring [2], and wireless ad-hoc interconnections between electronic devices [3],[4]...
    • ...N=4 and 8. For N=2, N=4, there is only one sequence satisfying both (11) and (12), i.e.S1 = 2 [ 1; 1] and S2 = 2 [1; 1; 1; 1]. Notice that these sequences are also of the form of (13)...
    • ...N=4 and 8. For N=2, N=4, there is only one sequence satisfying both (11) and (12), i.e.S1 = 2 [ 1; 1] and S2 = 2 [1; 1; 1; 1]. Notice that these sequences are also of the form of (13)...
    • ...N=4 and 8. For N=2, N=4, there is only one sequence satisfying both (11) and (12), i.e.S1 = 2 [ 1; 1] and S2 = 2 [1; 1; 1; 1]. Notice that these sequences are also of the form of (13)...
    • ...N=4 and 8. For N=2, N=4, there is only one sequence satisfying both (11) and (12), i.e.S1 = 2 [ 1; 1] and S2 = 2 [1; 1; 1; 1]. Notice that these sequences are also of the form of (13)...

    S. Gambini, et al. Interference robust self-mixing UWB systems using phase-domain spreadi...

    • ...This solution is used in several embedded sensors, such as The “Human++” platform [6] or Smart Dust [7]...
    • ...Several methods exist from a static value defined by the user up to dynamic algorithm as in the Otsu method [6]...

    Anthony Kolar, et al. Prototype of Video Endoscopic Capsule With 3-D Imaging Capabilities

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