Characterizing affiliative touch in humans and its role in advancing haptic design.

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. This basic scientific research on the human affiliative touch system is informed by, and informs, technology design for communicating and regulating emotion through touch. Here, we review recent research on the basic biology and cognitive neuroscience of affiliative touch, its regulatory effects across the lifespan, and the factors that modulate it. We further review recent work on the design of haptic technologies, devices that stimulate the affiliative touch system, such as wearable technologies that apply the sensation of soft stroking or other skin-to-skin contact, to promote physiological regulation. We then point to future directions in interdisciplinary research aimed at both furthering scientific understanding and application of haptic technology for health and wellbeing.

"Making Data the Drug": A Pragmatic Pilot Feasibility Randomized Crossover Trial of Data Visualization as an Intervention for Pediatric Chronic Pain.

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. Participants completed two weeks of Ecological Momentary Assessment (EMA) data collection, one of which also included access to a data visualization platform to view their results. Order of weeks was randomized, participants were not masked to group assignment. Objectives were to establish feasibility related to recruitment, retention, and participant experience. Of 146 youth approached, 48 were eligible and consented to participation, two actively withdrew prior to the EMA. Most participants reported satisfaction with the process and provided feedback on additional variables of interest. Technical issues with the data collection platform impacted participant experience and data analysis, and only 48% viewed the visualizations. Four youth reported adverse events not related to visualizations. Data visualization offers a promising clinical tool, and patient experience feedback is critical to modifying the platform and addressing technical issues to prepare for deployment in a larger trial.

FEELing (key)Pressed: Implicit Touch Pressure Bests Brain Activity in Modelling Emotion Dynamics in the Space Between Stressed and Relaxed.

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.g., "hopeful but getting stressed" vs. "hopeful and starting to relax". We trained participant-dependent hierarchical models of contextualized individual experience to compare emotion classification by modality (brain activity and keypress force from a physical keyboard), then benchmarked classification performance at F1-scores=[0.44, 0.82] (chance F1=0.22, σ = 0.01) and examined high-performing features. Notably, when classifying emotion evolution in the context of an experience that realistically varies in stress, pressure-based features from keypress force proved to be the more informative modality, and more convenient when considering intrusiveness and ease of collection and processing. Finally, we present our FEEL (Force, EEG and Emotion-Labelled) dataset, a collection of brain activity and keypress force data, labelled with self-reported emotion collected during tense videogame play (N=16) and open-sourced for community exploration.

Data visualization as an intervention for pediatric chronic pain: a pilot feasibility study protocol for a randomized controlled crossover trial.

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). As a self-appraised condition, pain experience is influenced by patient's biases and meaning-making in relation to their symptoms and triggers. We propose that interacting with self-reported data will impact the experience of pain by altering understanding and expectations of symptom experience and how pain interacts with other factors (e.g., sleep, emotions, social interactions). In this study, we aim to establish the feasibility and acceptability of using a data visualization platform to track and monitor symptoms and their relationship with other factors, versus simply daily reporting of symptoms using a smartphone-based Ecological Momentary Assessment (EMA). METHODS: This protocol is for a randomized, single-center, open-label crossover trial. We aim to recruit 50 typically developing youth aged 12-18 years with chronic pain to take part in two phases of data collection. The trial will utilize an A-B counterbalanced design in which participants will be randomly assigned to receive either Part A (EMA alone for 7 days) or Part B (EMA plus visualization platform for 7 days) first and then receive the opposite phase after a 7-day break (washout period). Key outcomes will be participant reports of acceptability and feasibility, EMA completion rates, barriers, and perceptions of the benefits or risks of participation. Secondary exploratory analyses will examine the relationship between EMA-reported symptoms over time and in relation to baseline measures, as well as pilot data on any improvements in symptoms related to engaging with the data visualization platform. DISCUSSION: This protocol describes the feasibility and pilot testing of a novel approach to promoting self-management and facilitating symptom appraisal using visualized data. We aim to determine whether there is a sufficient rationale, both from the perspective of feasibility and patient satisfaction/acceptability, to conduct a larger randomized controlled trial of this intervention. This intervention has the potential to support clinical care for youth with chronic pain and other conditions where self-appraisal and understanding of symptom patterns are a critical component of functional recovery. TRIAL REGISTRATION: Open Science Framework doi: https://doi.org/10.17605/OSF.IO/HQX7C . Registered on October 25, 2021, osf.io/hqx7c.

PAL: A Framework for Physically Assisted Learning Through Design and Exploration With a Haptic Robot Buddy.

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, e.g., to sketch experiments they want to try, could lead to fluid interactions and benefit focus. However, a number of technical barriers interfere with testing this approach, and making it accessible to learners and their teachers. In this paper, we propose a framework for Physically Assisted Learning based on stages of experiential learning which can guide designers in developing and evaluating effective technology, and which directs focus on how haptic feedback could assist with design and explore learning stages. To this end, we demonstrated a possible technical pathway to support the full experience of designing an experiment by drawing a physical system on paper, then interacting with it physically after the system recognizes the sketch, interprets as a model and renders it haptically. Our proposed framework is rooted in theoretical needs and current advances for experiential learning, pen-paper interaction and haptic technology. We further explain how to instantiate the PAL framework using available technologies and discuss a path forward to a larger vision of physically assisted learning.

How Do Novice Hapticians Design? A Case Study in Creating Haptic Learning Environments.

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. Teams (predominantly undergraduate engineers with little haptics, interaction design, or education training) designed and built haptic environments to support learning of science topics. Qualitative analysis of surveys, interviews, team blogs, and expert assessments of teams' final demonstrations exposed three themes in these design efforts. 1) Novice teams tended to ignore many of ten design choices that experts navigate, such as explicitly choosing whether haptic and graphic feedback should reinforce versus complement one other. 2) Their design activities differed in timing and inclusion from the ten activities observed in expert process. 3) We identified three success strategies in how teams devised useful and engaging interactions and interpretable multimodal experiences, and communicated about their designs. We compare novice and expert design needs and highlight where future haptic design tools and theory need to support novice practice and training.

Backward and common-onset masking of vibrotactile stimuli.

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). In anticipation of future embedded applications where signals are deliberately masked but levels cannot be individualized, signals were standardized at conservative (harder to mask) levels. Our results confirm the existence of a statistically significant masking effect for both forms of haptic masking explored, with common-onset exhibiting a significantly larger masking effect than backwards. However, an analysis of confidence in response levels shows no difference between the two successful masking techniques. We discuss mechanisms that could be responsible for these results, which have implications for the design of user interfaces that rely on tactile transmission of information.

Predictive haptic guidance: intelligent user assistance for the control of dynamic tasks.

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. Look-ahead guidance outperformed the other methods in both quantitative performance and subjective preference across a range of path complexity and visibility and a force analysis demonstrated that it applied smaller and fewer forces to users. These results (which appear to derive from the predictive guidance's supporting users in taking earlier and more subtle corrective action) suggest the potential of predictive methods in aiding manual control of dynamic interactive tasks where intelligent support is available.

Exploring the role of haptic feedback in enabling implicit HCI-based bookmarking.

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. Results show that haptic notification of bookmark placement, when paired with visual display of bookmark location, significant improves navigation time. Solely visual or haptic display of bookmarks elicited equivalent navigation time; however, only the inclusion of haptic display significantly increased accuracy. Participants preferred haptic notification over no notification at interruption time, and combined haptic and visual display of bookmarks to support navigation to their interrupted location at resumption time. Our contributions include an approach to handling noisy data in implicit HCI, an implementation of haptic notifications that signal implicit system behavior, and discussion of user mental models that may be active in this context.