Towards Haptic Performance Analysis Using K-Metrics

Authors:
Richard Hall;Hemang Rathod;Mauro Maiorca;Ioanna Ioannou;Edmund Kazmierczak;Stephen O'Leary;Peter Harris
Affiliations:
Melbourne University Virtual Environment for Simulation,;Melbourne University Virtual Environment for Simulation,;Melbourne University Virtual Environment for Simulation,;Melbourne University Virtual Environment for Simulation,;Department of Computer Science and Software Engineering,;Department of Otolaryngology,;Biomedical Multimedia Unit, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Australia
Venue:
HAID '08 Proceedings of the 3rd international workshop on Haptic and Audio Interaction Design
Year:
2008

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Abstract

It is desirable to automatically classify data samples for the assessment of quantitative performance of users of haptic devices as the haptic data volume may be much higher than is feasible to manually annotate. In this paper we compare the use of three k-metrics for automated classifaction of human motion: cosine, extrinsic curvature and symmetric centroid deviation. Such classification algorithms make predictions about data attributes, whose quality we assess via three mathematical methods of comparison: root mean square deviation, sensitivity error and entropy correlation coefficient. Our assessment suggests that k-cosine might be more promising at analysing haptic motion than our two other metrics.