EmotionCheck

Costa, Jean; Adams, Alexander T.; Jung, Malte; Guimbretière, François; Choudhury, Tanzeem

doi:10.1145/2971648.2971752

Cited by 134 publications

(53 citation statements)

References 37 publications

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“…al. [14] showed how modulating heart rate can help control anxiety in EmotionCheck and demonstrated improved performance of false feedback in math tests [15]. VR experiences have used false feedback to generate and intensify fear [87].…”

Section: Metasomaticmentioning

confidence: 99%

Designing Interactions Beyond Conscious Control

Jain

Horowitz

Schoeller

et al. 2020

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Recent research in psychology distinguishes levels of consciousness into a tripartite model-conscious, unconscious and metaconscious. HCI technologies largely focus on the conscious pathway for computer-to-human interaction, requiring explicit user attention and action. In contrast, the other two pathways provide opportunities to create new interfaces that can alter emotion, cognition and behavior without demands on attentional resources. These direct interfaces connect to cognitive processes that are in our perception but outside our conscious control. In this work, we feature two sub-categories, namely preconscious and metasomatic within the tripartite model of consciousness. Our goal is to provide a finer categorization of cognitive processes that can better help classify HCI research related to activating non-conscious cognitive pathways. We present the design of two wearable devices, MoveU and Frisson. From lessons learned during the iterative design process and the user studies, we present four design considerations that can be used to aid HCI researchers of future devices that influence the mind. With this work we aim to highlight that awareness of consciousness levels can be a valuable design element that can help to expand the range of computer-to-human interface devices we build. CCS Concepts: • Human-centered computing → Interaction design theory, concepts and paradigms; HCI theory, concepts and models.

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Section: Metasomaticmentioning

confidence: 99%

Designing Interactions Beyond Conscious Control

Jain

Horowitz

Schoeller

et al. 2020

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

View full text Add to dashboard Cite

show abstract

“…These are two simple yet effective examples of real time sensing and feedback to influence perception and behavior in a subconscious way. A later study in wearable technology (Costa, Adams, Jung, Guimbetière, & Choudhury, 2016) again demonstrated this mindless computing principle but using deliberate false feedback. Here, the authors create a vibrating wrist worn device from which the user believes the rate of vibration is a direct mirror of their own heart rate.…”

Section: Personalized Mental Health Interventionsmentioning

confidence: 96%

Sensing behavioral symptoms of mental health and delivering personalized interventions using mobile technologies

2017

Self Cite

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Unlike most other health conditions, the treatment of mental illness relies on subjective measurement. In addition, the criteria for diagnosing mental illnesses are based on broad categories of symptoms that do not account for individual deviations from these criteria. The increasing availability of personal digital devices, such as smartphones that are equipped with sensors, offers a new opportunity to continuously and passively measure human behavior in situ. This promises to lead to more precise assessment of human behavior and ultimately individual mental health. More refined modeling of individual mental health and a consideration of individual context, assessed through continuous monitoring, opens the way for more precise and personalized digital interventions that may help increase the number of positive clinical outcomes in mental healthcare. In this paper, we provide a conceptual review of such techniques for measuring, modeling, and treating mental illness and maintaining mental health.

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“…Smartphone applications like Headspace [29] and Calm [10] require the user's full-time attention to follow the meditation instructions, as well as a quiet space to focus on the practice. Also, Emo-tionCheck [17] presented the effect of false tactile feedback of HR by providing vibrations on the wrist. However, it has a lack of the sensing component to provide a closed-loop biofeedback that can reflect on the user's current physiological state in real-time.…”

Section: Related Workmentioning

confidence: 99%

“…Bright-Beat [25] is effective in regulating stress-levels with effortless mindful breathing guidance via visual and auditory feedback. Also, EmotionCheck [17] demonstrated the effects of false tactile feedback on heart beat rate by providing vibrations on the wrist. However, interfaces that communicate with the user about their physiological state bidirectionally, which lead to a behavior change in the user with minimal cognitive effort, are missing.…”

Section: Introductionmentioning

confidence: 99%