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This work deals with the design, the development and the evaluation of a set of sensing garments for human posture and gesture classification, from the characterization of innovative elastic and piezo-resistive textile-based sensors to the methodologies employed to gather information on the posture and movement from raw sensor data. The presented prototypes have been realized trough the integration of conductive elastomer (CE) sensors into textile substrates. CE materials show piezo-resistive properties: a fabric deformation can be related to a sensor electrical resistance variation. The basic concept of the proposed technology is that having a redundant distribution of sensors around the joints to be monitored, it is possible to associate the sensor status to parameters related to user movements. The methodology to address several technical issues, intrinsically related to the new developed technology, is reported. Data deriving from the prototypes are analyzed and compared with those of "standard" movement tracking systems. The realized kinaesthetic garments have shown very promising performance in terms of posture reconstruction and gesture classification.

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Alessandro Tognetti is a Post Doc researcher at the Interdepartmental Research Center "E. Piaggio". He received a degree in Electronic Engineering and a Ph.D. degree in Bioengineering from the University of Pisa. His main research interests are in sensor design and signal and information processing.

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