Design and preliminary affective characterization of a novel fabric-based tactile display

In this work we present a novel wearable haptic system based on an elastic fabric which can be moved forward and backward over the user forearm thus simulating a human caress. The system allows to control both the velocity of the “caress-like” movement, by regulating motor velocity, and the “strength of the caress”, by regulating motor positions and hence the force exerted by the fabric on the user forearm. Along with a description of the mechanical design and control of the system, we also report the preliminary results of psycho-physiological assessment tests performed by six healthy participants. Such an assessment is intended as a preliminary characterization of the device capability of eliciting tactually emotional states in humans using different combinations of velocity and caress strength. The emotional state is expressed in terms of arousal and valence. Moreover, the activation of the autonomic nervous system is also evaluated through the analysis of the electrodermal response (EDR). The main results reveal a statistically significant correlation between the perceived arousal level and the “strength of the caress” and between the perceived valence level and the “velocity of the caress”. Moreover, we found that phasic EDR is able to discern between pleasant and unpleasant stimuli. These preliminary results are very encouraging and confirm the effectiveness of this device in conveying emotional-like haptic stimuli in a controllable and wearable fashion

Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis

Understanding people's response to affective text messages and personalisation

The obesity and overweight growing rates are a major global concern for both developed and developing countries. Digital technologies can potentially deliver effective interventions to tackle this crisis, with mobile phones uniquely positioned to deliver scalable, real-time, inexpensive, and interactive support for all at risk. A meta-analysis showed that SMS interventions are effective for promoting weight loss and physical activity. The content of SMS messages of digital behaviour change interventions is usually seen as the main driver of effectiveness. It has been suggested that personalised communication, reaching people on emotional as well as rational levels, is more effective. However, there is no previous study exploring people’s affective responses to message wordings and personalisation, which could lead to more effective tools for promoting healthier behaviours, like physical activity. Affect is a term used to define the experience of a feeling or an emotion. Psychophysiological and self-reported measures of arousal and valence, the two main dimensions of emotions, were used to measure message impact on different levels of consciousness; and as methods to better understand people’s response to affective messages and personalisation. The first study in this thesis examined electrodermal activity and facial electromyography as objective measures of arousal and valence, respectively, and found strong associations between these measures. Study 2 compared psychophysiological and self-reported responses to previously evaluated affective and cognitive messages but found no significant difference between them. Study 3 used the same methods to test the effect of personalisation of affective and cognitive messages using identification (participant’s name) and contextualisation (participant’s preferred physical activity). Personalisation of messages using contextualisation and identification were found to be effective strategies for eliciting emotional responses and persuasiveness. This thesis contributes to our knowledge about using psychophysiology and self-report as methods to measure people’s response to affective and personalised messages, and the value of measuring the emotional impact of text messages on the recipient before using these in randomised controlled trials. The developers of SMS interventions and other digital techniques could benefit from using these methods. Future work needs to investigate the impact of messages designed using these methods on actual behaviour