Metrics of Comfort: Development of Physiological Correlates to Subjective Responses

Abstract

Comfort drives purchasing decisions for the equipment we interact with each day. Though manufacturers would like to claim to provide the most comfort over their competitors, a quantifiable metric based on physiological responses does not exist. The current research project examined the potential relationship of physiological measures with an individual's subjective level of comfort and discomfort. Heart rate variability and skin conductance responses were collected in a controlled laboratory environment along with a behavioral measure, the number of times the seated position was adjusted. During a 20 minute seated trial participants provided periodic responses to their subjective levels of comfort and discomfort. Discomfort was predicted through an interaction of the seat type (padded or rigid) and the number of adjustments made during a trial. Comfort had no significant predictors. Results showed no predictive power of heart rate variability or skin conductance responses. These results point toward use of measures of discomfort, rather than comfort, and observation of behaviors while seated.

Ai vs. Human: The Public's Perceptions of the Design Abilities of Artificial Intelligence

“…In Figure 1, the design goals people think can be reached significantly better (p<0.01) by a human designer than an AI are creating bicycles that are safe, stylish, easy-to-use, comfortable, and customer likes. As hypothesised earlier in this paper, these goals are all very subjective characteristics that demand more consideration of human preferences and needs (Davis, 1989;Lan et al, 2008;McDonald and McLaughlin, 2021), which people may not believe an AI can understand and design for. Contrastingly, the respondents perceive an AI to exceed a human designer in generating a large number of designs and creating easily manufacturable designs, which are both quantitative and user-independent goals.…”

“…The respondents expect eight of the 16 bicycle design goals (high quality, safe, stylish, easy-to-use, environmentally friendly, comfortable, customer likes, useful) would be better achieved by a human designer (one sample t-test, p<0.05). Interestingly, five of these eight goals that show greater significance (one sample t-test, p<0.01) (safe, stylish, easy-to-use, comfortable, and customer likes) are highly subjective or user-dependent goals (Davis, 1989;Lan et al, 2008;McDonald and McLaughlin, 2021).…”

“…Does the general public perceive AI or humans as performing better or worse on achieving specific design goals? It can be hypothesised that the public perceives human designers to be better at achieving design goals that require more consideration of human preferences and needs, such as aesthetics and comfortability (Lan et al, 2008;McDonald and McLaughlin, 2021), and AIs to be better at those that are more quantitative, such as creating a large quantity of designs.…”