Publications by authors named "Karon E MacLean"

In-body lived emotional experiences can be complex, with time-varying and dissonant emotions evolving simultaneously; devices responding in real-time to estimate personal human emotion should evolve accordingly. Models assuming generalized emotions exist as discrete states fail to operationalize valuable information inherent in the dynamic and individualistic nature of human emotions. Our multi-resolution emotion self-reporting procedure allows the construction of emotion labels along the Stressed-Relaxed scale, differentiating not only what the emotions are, but how they are transitioning - e.

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Data tracking is a common feature of pain e-health applications, however, viewing visualizations of this data has not been investigated for its potential as an intervention itself. We conducted a pilot feasibility parallel randomized cross-over trial, 1:1 allocation ratio. Participants were youth age 12-18 years recruited from a tertiary-level pediatric chronic pain clinic in Western Canada.

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An emerging view in cognitive neuroscience holds that the extraction of emotional relevance from sensory experience extends beyond the centralized appraisal of sensation in associative brain regions, including frontal and medial-temporal cortices. This view holds that sensory information can be emotionally valenced from the point of contact with the world. This view is supported by recent research characterizing the human affiliative touch system, which carries signals of soft, stroking touch to the central nervous system and is mediated by dedicated C-tactile afferent receptors.

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Background: Chronic pain is a common and costly condition in youth, associated with negative implications that reach far beyond the pain experience itself (e.g., interference with recreational, social, and academic activities, mental health sequelae).

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Robots are an opportunity for interactive and engaging learning activities. In this paper we consider the premise that haptic force feedback delivered through a held robot can enrich learning of science-related concepts by building physical intuition as learners design experiments and physically explore them to solve problems they have posed. Further, we conjecture that combining this rich feedback with pen-and-paper interactions, , to sketch experiments they want to try, could lead to fluid interactions and benefit focus.

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Access to haptic technology is on the rise, in smartphones, virtual reality gear, and open-source education kits. However, engineers and interaction designers are often inexperienced in designing with haptics, and rarely have tools and guidelines for creating multisensory experiences. To examine the impact of this deficit, we supplied a haptic design kit, custom software, and technical support to nine teams (25 students) for an innovation challenge at a major haptics conference.

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We examine how haptic feedback could enable an implicit human-computer interaction, in the context of an audio stream listening use case where a device monitors a user's electrodermal activity for orienting responses to external interruptions. When such a response is detected, our previously developed system automatically places a bookmark in the audio stream for later resumption of listening. Here, we investigate two uses of haptic feedback to support this implicit interaction and mitigate effects of noisy (false-positive) bookmarking: (a) low-attention notification when a bookmark is placed, and (b) focused-attention display of bookmarks during resumptive navigation.

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To inform the design of haptic information displays for noisy environments, we investigated two mechanisms for temporal masking of vibrotactile stimuli (backwards and common-onset) using a commodity display. We used a two-channel setup, presenting stimuli to the middle and ring finger of a participant's right hand. The stimuli consisted of 250 Hz sinusoidal waveforms displayed at a fixed amplitude in various combinations of duration (0, 30 or 300 ms) and stimulus onset asynchrony (0 or 30 ms).

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Intelligent systems are increasingly able to offer real-time information relevant to a user's manual control of an interactive system, such as dynamic system control space constraints for animation control and driving. However, it is difficult to present this information in a usable manner and other approaches which have employed haptic cues for manual control in "slow" systems often lead to instabilities in highly dynamic tasks. We present a predictive haptic guidance method based on a look-ahead algorithm, along with a user evaluation which compares it with other approaches (no guidance and a standard potential-field method) in a 1-DoF steered path-following scenario.

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