Enacted Embodiment in Adaptive Architecture: Physiological Interactions Between Inhabitants and Biofeedback Architecture

Jaeger, Nils

Abstract

This thesis argues for an enactive embodied approach to understanding interactions with Adaptive Architecture. The growing interest in Ubiquitous and Pervasive Computing, including the current trends of wearable, sensor infused technology, shows the inevitable confluence of Human-Computer Interaction (HCI) and Architecture. Specifically, the availability of real-time physiological data allows environments to respond directly to the bodily behaviours of their users. This creates an interaction cycle or loop, which temporarily couples architectural environment and human body. One instantiation of such an interaction loop are so called biofeedback environments, which reflect an inhabitant's physiological behaviour back to the inhabitant. Very few such environments exist, little empirical research has been done regarding their effects on inhabitants, and none have specifically engaged with, appropriated, and discussed the concept of enacted embodiment in this context so far, especially regarding multi-occupancy. To investigate enacted embodied interactions with adaptive environments I use a three-tiered, mixed-method approach. In an in-depth, quantitative study of an existing prototype (ExoBuilding) I first investigated the enacted control-relationship between environment and an individual inhabitant. I found that, by manipulating the control relationship between the biofeedback environment and its occupant, the environment can actively influence the physiological behaviour of its inhabitant, which in this case was respiration rate. The reasons why participants changed their behaviour after having lost practical control over the interaction were found to either be a pre- cognitive bodily interaction with the environment or to be an intentional synchronising with the changing environment in order to maintain cognitive control of the situation. Secondly, these findings and interpretations lead to a research-based design of a new multi-inhabitant prototype environment allowing enacted embodied interactions between the inhabitants themselves and between them and the environment called WABI. While expandable, WABI currently envelopes two sections, each of which accommodates one inhabitant. Through further co-development of the software platform originally used for ExoBuilding, WABI can distribute biofeedback spatially to both its building sections in multiple ways. Thirdly, I investigated the effects of three feedback distribution modes on the two inhabitants of WABI in a qualitative exploratory study, which found that physiological synchrony is highest when the environment distributes real-time feedback such that participants are surrounded by their partner's phys- iology. I propose a model of triadic enacted embodiment that conceptualises the observed interactions between inhabitants and between them and WABI. This work makes three key contributions to HCI and Architecture. First, it provides empirical data to the limited existing knowledge of the effects of adaptive environments on their inhabitants. Specifically, it increases our un- derstanding of the control relationship between inhabitant and adaptive en- vironment. And for the first time it provides an insight into interpersonal physiological synchrony between inhabitants of adaptive environments. Secondly, this work adds a new class of adaptive environment that enables shared biofeedback between its inhabitants. And thirdly, the previous two contributions expand the existing concepts of embodiment, which so far have ignored the bodily relationship between inhabitants and adaptive envi- ronments.

Citation

Jaeger, N. Enacted Embodiment in Adaptive Architecture: Physiological Interactions Between Inhabitants and Biofeedback Architecture. (Thesis). University of Nottingham. Retrieved from https://nottingham-repository.worktribe.com/output/4381761

• Thesis Type: Thesis
• Deposit Date: May 4, 2020
• Public URL: https://nottingham-repository.worktribe.com/output/4381761
• Award Date: Dec 10, 2015