As Extended Reality (XR) advances, a device has the potential to be used across contexts from immersive productivity at a desk to on-the-go, public scenarios. Existing input solutions lack the versatility to provide both high-throughput, mouse-grade input and subtle, ergonomic interaction. We introduce FlowRing, a novel ring-form device that combines microgestures with precise 2D mouse-like input on surfaces. FlowRing supports five microgestures for discreet interaction and 2D input for richer tasks, using an optical flow sensor, skin-contact microphone, and IMU at the base of the finger. In a study with 11 participants, FlowRing achieved 93.6% microgesture recognition accuracy across sessions and 85.2% across unseen users, rising to 90.1% with just four gesture set examples from a new user. A separate 2D Fitts’ law study demonstrated its effectiveness for continuous input on various surfaces. FlowRing emerges as a versatile, user-friendly solution for the future of interactive technology.

This paper presents a mixed-methods study of app-based motorcycle taxis in Thailand to explore the social dynamics of rideshare drivers and their exercised autonomy both through social pressure and a hostile work environment. As motorcycle taxis are open-air vehicles, drivers can be exposed to prolonged air pollution and other weather events, potentially impacting their health. In an initial quantitative study of server-side rideshare logs, we unexpectedly found that drivers do not exercise the autonomy provided by their rideshare platform to avoid air pollution events. This prompted a follow-on investigation through semi-structured interviews of both drivers and passengers in three provinces to explore why these drivers fail to experience the autonomy promised by gig-work in this context and elucidated further examples this lack of autonomy experienced by drivers. Our study sheds light on the social context that may constrain a driver's agency, including financial pressures, weather conditions, conflicts with local taxi organizations, and a false perception that drivers need to work around the ride assignment algorithm to avoid being blacklisted. We find that when leveraging app-based rideshare opportunities, drivers simultaneously perceive increased flexibility in their work hours and a lack of agency to prioritize their health and safety. We conclude with a discussion on potential interventions aimed at mitigating the forces preventing drivers from exercising their autonomy.

Designing privacy-respecting and human-centric smart cities requires a careful investigation of people’s attitudes and concerns toward city-wide data collection scenarios. To capture a holistic view, we carried out this investigation in two phases. We first surfaced people’s understanding, concerns, and expectations toward smart city scenarios by conducting 21 semi-structured interviews with people in underserved communities. We complemented this in-depth qualitative study with a 348-participant online survey of the general population to quantify the significance of smart city factors (e.g., type of collected data) on attitudes and concerns. Depending on demographics, privacy and ethics were the two most common types of concerns among participants. We found the type of collected data to have the most and the retention time to have the least impact on participants’ perceptions and concerns about smart cities. We highlight key takeaways and recommendations for city stakeholders to consider when designing inclusive and protective smart cities.

According to the World Health Organisation (WHO), 235 million people suffer from respiratory illnesses which causes four million deaths annually. Regular lung health monitoring can lead to prognoses about deteriorating lung health conditions. This article presents our system SpiroMask that retrofits a microphone in consumer-grade masks (N95 and cloth masks) for continuous lung health monitoring. We evaluate our approach on 48 participants (including 14 with lung health issues) and find that we can estimate parameters such as lung volume and respiration rate within the approved error range by the American Thoracic Society (ATS). Further, we show that our approach is robust to sensor placement inside the mask.

We describe the design, development, and characterization of a system that uses only a commodity smartphone and a consumer fan to measure the voltage of an electricity grid. This system represents the first known example of a system for measuring power quality of an electricity grid without specialized equipment, and can enable those with electricity access who live in "weak grid" environments to determine the current state of their electricity system, especially whether it is safe to plug in appliances. Our work leverages the microphone of the phone to measure the disturbance created on a pure sinusoidal tone into a running fan. The distance between adjacent harmonics in this disturbance is a direct proxy for the electricity grid voltage. We build a system to exploit this phenomenon and show that it is robust to a variety of fan types, phone types, and background audio environments, consistently producing voltage estimations within +/- 2%. We also show that our method works for smartphones as well as feature phones, making it applicable in a wide range of settings.