首页|University College London (UCL) Reports Findings in Robotics (Tactile emoticons: Conveying social emotions and intentions with manual and robotic tactile feedba ck during social media communications)

University College London (UCL) Reports Findings in Robotics (Tactile emoticons: Conveying social emotions and intentions with manual and robotic tactile feedba ck during social media communications)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news reporting from London, United Kingdom, by NewsR x journalists, research stated, "Touch offers important non-verbal possibilities for socioaffective communication. Yet most digital communications lack capabili ties regarding exchanging affective tactile messages (tactile emoticons)." Financial supporters for this research include European Research Council, HORIZO N EUROPE European Research Council, University College London, University Colleg e London, University College London. The news correspondents obtained a quote from the research from University Colle ge London (UCL), "Additionally, previous studies on tactile emoticons have not c apitalised on knowledge about the affective effects of certain mechanoreceptors in the human skin, e.g., the C-Tactile (CT) system. Here, we examined whether ge ntle manual stroking delivered in velocities known to optimally activate the CT system (defined as ‘tactile emoticons'), during lab-simulated social media commu nications could convey increased feelings of social support and other prosocial intentions compared to (1) either stroking touch at CT sub-optimal velocities, o r (2) standard visual emoticons. Participants (N = 36) felt more social intent w ith CToptimal compared to sub-optimal velocities, or visual emoticons. In a sec ond, preregistered study (N = 52), we investigated whether combining visual emot icons with tactile emoticons, this time delivered at CT-optimal velocities by a soft robotic device, could enhance the perception of prosocial intentions and af fect participants' physiological measures (e.g., skin conductance rate) in compa rison to visual emoticons alone. Visuotactile emoticons conveyed more social int ent overall and in anxious participants affected physiological measures more tha n visual emoticons."

LondonUnited KingdomEuropeEmerging TechnologiesMachine LearningRoboticsRobots

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jun.25)