Abstract:
Affective computing, with its potential to enhance human-computer interaction, is experiencing an expansion of its use in many areas such as health care and the gaming in...Show MoreMetadata
Abstract:
Affective computing, with its potential to enhance human-computer interaction, is experiencing an expansion of its use in many areas such as health care and the gaming industry. One obstacle to its widespread adoption can be the high cost requirement for biofeedback. Indeed, typical laboratory setups are often expensive which makes them out of reach for many. This paper explores lower-cost alternatives to expensive laboratory solutions. Data from several recent studies totaling over 200 hours of physiological recordings are leveraged to compare high-end solutions to a lower cost one. Heart rate, electrodermal activity, facial action units, head movement, and eye movement - five of the most used bio-behavioural signals - have their respective higher and lower cost sensors compared. The resulting comparison illustrates that lower-cost solutions are not drop-in replacements. While a correlation of 0.62 between electrodermal activity readings was found, notable differences between reported heart rate readings over small timescales were also observed. Head tracking recordings shared similarity (0.51), but eye tracking did not (0.18). As for facial action units recognition, only those linked to smiling had significant correlation (around 0.48). These results should broaden the range of contexts in which biofeedback could be exploited. This aim may be fulfilled by informing the reader of the extent of lower cost solution applications.
Date of Conference: 06-09 October 2019
Date Added to IEEE Xplore: 28 November 2019
ISBN Information: