Perceived Empathy of Technology Scale (PETS): Measuring Empathy of Systems Toward the User
Full-Paper: Affective computing improves rapidly, allowing systems to process human emotions. This enables systems such as conversational agents or social robots to show empathy toward users. While there are various established methods to measure the empathy of humans, there is no reliable and validated instrument to quantify the perceived empathy of interactive systems. Thus, we developed the Perceived Empathy of Technology Scale (PETS) to assess and compare how empathic users perceive technology. We followed a standardized multi-phase process of developing and validating scales. In total, we invited 30 experts for item generation, 324 participants for item selection, and 396 additional participants for scale validation. We developed our scale using 22 scenarios with opposing empathy levels, ensuring the scale is universally applicable. This resulted in the PETS, a 10-item, 2-factor scale. The PETS allows designers and researchers to evaluate and compare the perceived empathy of interactive systems rapidly.
Uncovering and Addressing Blink-Related Challenges in Using Eye Tracking for Interactive Systems
Full-Paper: Currently, interactive systems use physiological sensing to enable advanced functionalities. While eye tracking is a promising means to understand the user, eye tracking data inherently suffers from missing data due to blinks, which may result in reduced system performance. We conducted a literature review to understand how researchers deal with this issue. We uncovered that researchers often implemented their use-case-specific pipeline to overcome the issue, ranging from ignoring missing data to artificial interpolation. With these first insights, we run a large-scale analysis on 11 publicly available datasets to understand the impact of the various approaches on data quality and accuracy. By this, we highlight the pitfalls in data processing and which methods work best. Based on our results, we provide guidelines for handling eye tracking data for interactive systems. Further, we propose a standard data processing pipeline that allows researchers and practitioners to pre-process and standardize their data efficiently.
Sitting Posture Recognition and Feedback: A Literature Review
Full-Paper: Extensive sitting is unhealthy; thus, countermeasures are needed to react to the ongoing trend toward more prolonged sitting. A variety of studies and guidelines have long addressed the question of how we can improve our sitting habits. Nevertheless, sitting time is still increasing. Here, smart devices can provide a general overview of sitting habits for more nuanced feedback on the user’s sitting pos-ture. Based on a literature review (N=223), including publications from engineering, computer science, medical sciences, electronics, and more, our work guides developers of posture systems. There is a large variety of approaches, with pressure-sensing hardware and visual feedback being the most prominent. We found factors like environment, cost, privacy concerns, portability, and accuracy important for deciding hardware and feedback types. Further, one should consider the user’s capabilities, preferences, and tasks. Re-garding user studies for sitting posture feedback, there is a need for better comparability and for investigating long-term effects.
PhysioCHI: Towards Best Practices for Integrating Physiological Signals in HCI
Workshop: Recently, we saw a trend toward using physiological signals in interactive systems. These signals, offering deep insights into users’ internal states and health, herald a new era for HCI. However, as this is an interdisciplinary approach, many challenges arise for HCI researchers, such as merging diverse disciplines, from understanding physiological functions to design expertise. Also, isolated research endeavors limit the scope and reach of findings. This workshop aims to bridge these gaps, fostering cross-disciplinary discussions on usability, open science, and ethics tied to physiological data in HCI. In this workshop, we will discuss best practices for embedding physiological signals in interactive systems. Through collective efforts, we seek to craft a guiding document for best practices in physiological HCI research, ensuring that it remains grounded in shared principles and methodologies as the field advances.
More Information: https://www.hcilab.org/physiochi24/