Investigating mechanical properties of a fabric-based affective haptic display through electrodermal activity analysis

• Published in: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2016; pp. 407 - 410
• Main Authors: Greco, Alberto, Valenza, Gaetano, Scilingo, Enzo Pasquale
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.08.2016
• Subjects: Adult; Area Under Curve; Autoregressive processes; Biomedical monitoring; Fabrics; Feature extraction; Female; Force; Galvanic Skin Response - physiology; Haptic interfaces; Healthy Volunteers; Humans; Male; Manikins; Mechanical Phenomena; Models, Theoretical; Signal Processing, Computer-Assisted; Skin; Surveys and Questionnaires; Textiles
• ISSN: 1557-170X
• DOI: 10.1109/EMBC.2016.7590726

The aim of this study is the development of a classification system able to discern between two levels of velocity of a caress-like haptic stimulus, through information gathered from the analysis of the Electrodermal Activity (EDA) dynamics. We designed and performed an experiment where EDA signals were acquired during caress-like stimuli conveyed to 32 healthy volunteers (16 females) by means of four different fabrics (hemp, burlap, velvet and silk) and at two velocity levels (9.4 mm/s and 65 mm/s). CvxEDA model was used to process the EDA signal and extract features from both tonic and phasic components. The feature set was used as an input to a K-NN classifier implementing a leave-one-subject-out procedure. Considering all fabrics, results show an accuracy of velocity recognition between 91.07% and 96.43%. Conversely, poor accuracy was achieved considering the fabric classification. Results also suggest that caress velocity significantly affects EDA dynamics regardless of the typology of fabrics. This is probably due to the fact that velocity is strictly related to the valence of the affective stimuli.