m.c. schraefel’s research while affiliated with University of Southampton and other places

Objective. This study investigated the potential of estimating various mental workload levels during two different tasks using a commercial in-ear electroencephalography (EEG) system, the IDUN ‘Guardian’. Approach. Participants performed versions of two classical workload tasks: an n-back task and a mental arithmetic task. Both in-ear and conventional EEG data were simultaneously collected during these tasks. In an effort to facilitate a more comprehensive comparison, the complexity of the tasks was intentionally increased beyond typical levels. Special emphasis was also placed on understanding the significance of γ band activity in workload estimations. Therefore, each signal was analyzed across low frequency (1–35 Hz) and high frequency (1–100 Hz) ranges. Additionally, surrogate in-ear EEG measures, derived from the conventional EEG recordings, were extracted and examined. Main results. Workload estimation using in-ear EEG yielded statistically significant performance levels, surpassing chance levels with 44.1% for four classes and 68.4% for two classes in the n-back task and was better than a naive predictor for the mental arithmetic task. Conventional EEG exhibited significantly higher performance compared to in-ear EEG, achieving 80.3% and 92.9% accuracy for the respective tasks, along with lower error rates than the naive predictor. The developed surrogate measures achieved improved results, reaching accuracies of 57.5% and 85.5%, thus providing insights for enhancing future in-ear systems. Notably, most high frequency range signals outperformed their low frequency counterparts in terms of accuracy validating that high frequency γ band features can improve workload estimation. Significance. The application of EEG-based Brain–Computer Interfaces beyond laboratory settings is often hindered by practical limitations. In-ear EEG systems offer a promising solution to this problem, potentially enabling everyday use. This study evaluates the performance of a commercial in-ear headset and provides guidelines for increased effectiveness.

We present discomfort as a new material for HCI researchers and designers to consider in applications that help a person develop a new skill, practice, or state. In this context, discomfort is a fundamental precursor to a necessary adaptation which leads to the development of a new skill, practice, or state. The way in which discomfort is perceived, and when it is experienced, is often part of a rationale for rejecting or adopting a practice. Factors that influence the choice to accept or reject a practice of discomfort create opportunities for designing interactions that facilitate discomfort. Enabling effective engagement with discomfort may therefore open opportunities for increased personal development. We propose incorporating discomfort-as-material into our designs explicitly as a mechanism to make desired adaptations available to more of us, more effectively, and more of the time. To explore this possibility, we offer an overview of the physiology and neurology of discomfort in adaptation and propose three issues related to incorporating discomfort into design: preparation for discomfort, need for recovery, and value of the practice.

In an effort to make biosignal integration more accessible to explore for more HCI researchers, this paper presents our investigation of how well a standard, near ubiquitous webcam can support remote sensing of heart rate and respiration rate across skin tone ranges. The work contributes: how the webcam can be used for this purpose, its limitations, and how to mitigate these limitations affordably, including how the skin tone range affect the estimation results.

This paper aims to establish a design space for tools to crowdsource data about Journey eXperience (JX). Understanding JX could provide a range of benefits in various domains, including transport planning, urban design, and individual route planning, and support efforts to achieve more sustainable transport systems. A key challenge in studying JX is finding effective ways to collect data. We present initial results from a diary study that explores what JX means and how JX data might be collected. We show how the experience of journeying through space differs from experiences of being in space, provide an initial description of factors that influence JX, and offer high-level insights of relevance to the design space of JX data collection.

Introduction A goal of inbodied interaction is to explore how tools can be designed to provide external interactions that support our internal processes. One process that often suffers from our external interactions with modern computing technology is our breathing. Because of the ergonomics and low-grade-but-frequent stress associated with computer work, many people adopt a short, shallow breathing pattern that is known to have a negative effect on other parts of our physiology. Breathing guides are tools that help people match their breathing patterns to an external (most often visual) cue to practice healthy breathing exercises.However, there are two leading protocols for how breathing cues are offered by breathing guides used in non-clinical settings: simple paced breathing (SPB) and Heart Rate Variability Biofeedback (HRV-b). Although these protocols have separately been demonstrated to be effective, they differ substantially in their complexity and design. Paced breathing is a simpler protocol where a user is asked to match their breathing pattern with a cue paced at a predetermined rate and is simple enough to be completed as a secondary task during other activities. HRV-b, on the other hand, provides adaptive, real-time guidance derived from heart rate variability, a physiological signal that can be sensed through a wearable device. Although the benefits of these two protocols have been well established in clinical contexts, designers of guided breathing technology have little information about whether one is better than the other for non-clinical use. Methods To address this important gap in knowledge, we conducted the first comparative study of these two leading protocols in the context of end-user applications. In our N=28 between-subject design, participants were trained in either SPB or HRV-b and then completed a 10-minute session following their training protocol. Breathing rates and heart rate variability scores were recorded and compared between groups. Results and discussion Our findings indicate that the exercises did not significantly differ in their immediate outcomes – both resulted in significantly slower breathing rates than their baseline and both provided similar relative increases in HRV. Therefore, there were no observed differences in the acute physiological effects when using either SPB or HRV-b. Our paper contributes new findings suggesting that simple paced breathing – a straightforward, intuitive, and easy-to-design breathing exercise – provides the same immediate benefits as HRV-b, but without its added design complexities.

Many service providers require permissions to access privacy-sensitive data that are not necessary for their core functionality. To support users’ privacy management, we propose a novel agent-based negotiation framework to negotiate privacy permissions between users and service providers using a new multi-issue alternating-offer protocol based on exchanges of partial and complete offers. Additionally, we introduce a novel approach to learning users’ preferences in negotiation and present two variants of this approach: one variant personalised to each individual user, and one personalised depending on the user’s privacy type. To evaluate them, we perform a user study with participants, using an experimental tool installed on the participants’ mobile devices. We compare the take-it-or-leave-it approach, in which users are required to accept all permissions requested by a service, to negotiation, which respects their preferences. Our results show that users share personal data 2.5 times more often when they are able to negotiate while maintaining the same level of decision regret. Moreover, negotiation can be less mentally demanding than the take-it-or-leave-it approach and it allows users to align their privacy choices with their preferences. Finally, our findings provide insight into users’ data sharing strategies to guide the future of automated and negotiable privacy management mechanisms.