Subliminal Copresence Systems

Leichsenring C (2016)
Bielefeld: Universität Bielefeld.

Bielefeld Dissertation | English
Telepresence research has focused on the ideal of recreating face-to-face conversations via remote mediated channels – maximising what has been termed social presence. A mostly overlooked aspect of communication is the simple sense of being together; the ability to be close to someone without necessarily having to interact consciously. Goffman described this as copresence. We propose a class of systems to specifically support this mode of communication over a distance which we call subliminal copresence systems (SCS); they fulfil the definition of calmness as coined by Weiser. We think such systems have the potential to fill a gap that was left during the increase in technologically mediated communication as a consequence of the rise in long-distance relationships in recent decades and the rapidly growing importance of computer-based media in social interactions such as e-mail and especially online social networks. In this work, we explore SCS in terms of their user acceptance, their effectiveness to convey information, their potential to influence and create feelings of connectedness and presence, and their ability to do so without being annoying or distracting. To this end, we implemented two proof-of-concept subliminal copresence systems called feelabuzz and upstairs. In feelabuzz, two unmodified smartphones are used to constantly transmit one user’s movements to another user as vibration of the phone and vice versa. In upstairs, two remote rooms are virtually stacked so that it sounds as if Room A were located above Room B and conversely, Room B were above Room A. For this, contact microphones are used to transduce the structure-borne sounds of the floor. Three user studies were conducted to evaluate the effectiveness of these systems. Firstly, feelabuzz was shown to recognisably confer basic activity types. Feelabuzz and upstairs were then tested in two related, longitudinal studies to evaluate the systems’ capabilities to evoke a sense of copresence over a distance. Both systems were shown to create copresence to a significantly larger extent than social presence. User acceptance was higher for upstairs than for feelabuzz and upstairs incurred a significantly smaller amount of cognitive load on its users. To address remaining acceptance and cognitive load issues brought up in these studies, we investigate the introduction of automatic filters to reduce the necessity of interpretation by the users. We explore context recognition in the area of subliminal copresence systems and present two such systems – one using instant messaging clients and another using mobile phones. Both achieved good recognition rates but worrying about user acceptance of such black box systems whose subsymbolic models are incomprehensible even for experts, we present a system that ex- tracts symbolic rules from these models. We compare existing methods for the extraction of such rules and also discuss different ways to present rule sets to the users in order for them to modify them and feed them back into the system. A partial prototype of one such system was implemented and is also discussed.

Cite this

Leichsenring C. Subliminal Copresence Systems. Bielefeld: Universität Bielefeld; 2016.
Leichsenring, C. (2016). Subliminal Copresence Systems. Bielefeld: Universität Bielefeld.
Leichsenring, C. (2016). Subliminal Copresence Systems. Bielefeld: Universität Bielefeld.
Leichsenring, C., 2016. Subliminal Copresence Systems, Bielefeld: Universität Bielefeld.
C. Leichsenring, Subliminal Copresence Systems, Bielefeld: Universität Bielefeld, 2016.
Leichsenring, C.: Subliminal Copresence Systems. Universität Bielefeld, Bielefeld (2016).
Leichsenring, Christian. Subliminal Copresence Systems. Bielefeld: Universität Bielefeld, 2016.
All files available under the following license(s):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Main File(s)
Access Level
OA Open Access
Last Uploaded
MD5 Checksum

This data publication is cited in the following publications:
This publication cites the following data publications:


0 Marked Publications

Open Data PUB

Search this title in

Google Scholar