In this paper, we consider a radio fingerprinting-based localization system for indoor motion capture applications. Fingerprinting allows target localization on the basis of radio-frequency measurements of the Received radio Signal Strength (RSS), taking into account the presence of fading by means of a training phase. Motion capture is then performed by localizing, through fingerprinting, a group of targets placed on the portion of interest of the user arm---the approach can be easily extended to other portions of the user body. We experimentally investigate, through a SunSPOT wireless sensor network test-bed, different fingerprinting-based localization algorithms, namely deterministic and probabilistic, optimizing, in each case, the system parameters. In particular, the optimization is carried out by minimizing the localization error.

Fingerprinting-based wireless 3D localization for motion capture applications / M., Giuberti; M., Martalo'; Ferrari, Gianluigi. - (2011), pp. 1-8. (Intervento presentato al convegno First ACM MobiHoc Workshop on Pervasive Wireless Healthcare (MobileHealth 2011), in conjunction with MobiHoc 2011 Conference tenutosi a Parigi, Francia nel maggio) [10.1145/2007036.2007044].

Fingerprinting-based wireless 3D localization for motion capture applications

FERRARI, Gianluigi
2011-01-01

Abstract

In this paper, we consider a radio fingerprinting-based localization system for indoor motion capture applications. Fingerprinting allows target localization on the basis of radio-frequency measurements of the Received radio Signal Strength (RSS), taking into account the presence of fading by means of a training phase. Motion capture is then performed by localizing, through fingerprinting, a group of targets placed on the portion of interest of the user arm---the approach can be easily extended to other portions of the user body. We experimentally investigate, through a SunSPOT wireless sensor network test-bed, different fingerprinting-based localization algorithms, namely deterministic and probabilistic, optimizing, in each case, the system parameters. In particular, the optimization is carried out by minimizing the localization error.
2011
9781450307802
Fingerprinting-based wireless 3D localization for motion capture applications / M., Giuberti; M., Martalo'; Ferrari, Gianluigi. - (2011), pp. 1-8. (Intervento presentato al convegno First ACM MobiHoc Workshop on Pervasive Wireless Healthcare (MobileHealth 2011), in conjunction with MobiHoc 2011 Conference tenutosi a Parigi, Francia nel maggio) [10.1145/2007036.2007044].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2384409
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