This paper presents the preliminary results of classifying human touching behaviors using a haptic interface for a pet-like robot. The haptic interface uses gridded pressure-sensitive conductive ink sheets. Features of the measured pressure data are determined for classification in terms of 1) absolute values, 2) spatial distributions and 3) the temporal differences in measured pressure patterns. Touching behaviors include "slap," "pat," "stroke" and so forth. The experimental results show that a reliable classification of these touching patterns can be accomplished by using the sensor sheet and pressure features. The results of classification can be used as reward signals for reinforcement learning in controlling the behaviors of a pet-like robot that interacts with humans.
o th -b as e d W e arab le S e n s in g D e v ice fo r N u rs in g A ctiv ity R e co g n itio n R e n Oh m u ra F u to s h i N ay a H aru o N o m a K iy o s h i K o g u re A T R M e d ia In fo rm atio n S cie n ce L ab o rato rie s , K y o to , J ap an {re n ,n ay a,n o m a,ko g u re }@ atr.jpAbstract-This paper presents a wearable sensing device called " B -P ack " , which is designed to captu re nu rsing activities in real ho spitals. To pro vide u sability and fl ex ibility , B -P ack featu res wireless co nnectivity u sing B lu eto o th and a rechargeable battery with o n-bo ard charging circu itry . F u rtherm o re, to acq u ire sy nchro niz ed data o n distribu ted parts o f wearer's bo dy , B -P ack featu res a tim e sy nchro niz atio n pro to co l. Thro u gh ex perim ents and interviews, we co nfi rm ed that the data fro m each bo dy part was appro priately co llected fo r nu rsing activity reco gnitio n and that the design is su itable fo r a real nu rsing enviro nm ent.
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