Joint motion capture and navigation in heterogeneous Body Area Networks with distance estimation over neighborhood graph

Hamie, Jihad; Denis, B.; Richard, Cédric

doi:10.1109/wpnc.2013.6533282

Cited by 6 publications

(1 citation statement)

References 17 publications

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“…Other approaches aim at characterizing mesh connectivity with integrated narrow-band devices from a pure communication-oriented perspective [5]. Finally some works simply rely on simulations [6]. But only rare contributions have considered using real devices to assess the actual performance of on-body nodes localization in large scale, while pointing out critical physical effects related to body mobility [7].…”

Section: Introductionmentioning

confidence: 99%

Qualitative analysis of RSSI behavior in cooperative wireless body area networks for mobility detection and navigation applications

Denis

Amiot

Uguen

et al. 2014

2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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In this paper, we account for radio-location experiments aiming at both indoor navigation and mobility detection applications for Wireless Body Area Networks (WBAN). This measurement campaign involved IEEE 802.15.4-compliant integrated radio devices organized within a full mesh topology over on-body and off-body links. The latter devices produce peerto-peer Received Signal Strength Indicators (RSSI) that could feed ranging, positioning or tracking algorithms. An in-depth behavioral analysis of the collected time-stamped radio-location metrics is thus proposed with respect to the captured human mobility (including body shadowing). Based on our observations and interpretations, practical insights are finally drawn in terms of system and algorithms design.

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Section: Introductionmentioning

confidence: 99%

Qualitative analysis of RSSI behavior in cooperative wireless body area networks for mobility detection and navigation applications

Denis

Amiot

Uguen

et al. 2014

2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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Wearable Sensors for Motion Capture

Mishra¹,

Kiourti²

2021

Antenna and Sensor Technologies in Modern Medical Applications

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Body Area Networks and Healthcare

Peri

2014

Advances in Intelligent Systems and Computing

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Derived fromWireless Sensor Networks, Body Area Networks, comprise a wide range of typologies with sensor nodes placed on, close to, or implanted in the body that measure physiological signs.The availability of compact mobile computing devices makes it possible to integrate traditional healthcarewith newpowerfulmeans. Newparadigms in public health are arising from these developments, such as e-health and mHealth, and new converging applications can be envisioned. Physiological data acquisition provided by BANs may give care providers a unobtrusive real-time view on patient's health. On the other hand, the patient may be informed, assisted and even given the proper treatment by care providers. In this chapter, recent work on BANs focused on healthcare and mHealth is surveyed

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Joint motion capture and navigation in heterogeneous Body Area Networks with distance estimation over neighborhood graph

Cited by 6 publications

References 17 publications

Qualitative analysis of RSSI behavior in cooperative wireless body area networks for mobility detection and navigation applications

Qualitative analysis of RSSI behavior in cooperative wireless body area networks for mobility detection and navigation applications

Wearable Sensors for Motion Capture

Body Area Networks and Healthcare

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