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Wearable health devices have transformed the land-scape of vital sign monitoring by enabling continuous, unob-trusive data collection. These compact and lightweight devices bypass the need for large, specialized instruments, facilitating frequent and comprehensive health monitoring essential for di-agnosing various medical conditions. Researchers are leveraging innovative techniques to sense bodily functions through external signals, such as using acoustic signals for joint health and repurposing low-cost sensors like IMUs, temperature sensors, and microphones as biosensors. These advancements aim to create more affordable and widespread health monitoring systems than traditional, costly biosensors. In this work, we present HealthHub, a versatile wearable health prototyping toolkit designed to expedite the development and testing of wearable health devices. HealthHub's modularity and flexibility are demonstrated by its array of onboard sensors and its support for custom snap-on boards that enhance sensing capabilities via the onboard ADC. Our evaluation of HealthHub included testing its power consumption and performance in measuring respiration, where it functioned as a pendant. The system operated for three days on a single coin cell battery, recording data at high sample rates and fidelity. HealthHub proves to be a lightweight, compact, and highly adaptable platform for developing wearable health devices. Its robust performance and extendable design make it an invaluable tool for researchers and developers in wearable health technol-ogy, facilitating the rapid conversion of innovative ideas into functional prototypes. 

Background Mobile health (mHealth) wearable devices are increasingly being adopted by individuals to help manage and monitor physiological signals. However, the current state of wearables does not consider the needs of racially minoritized low–socioeconomic status (SES) communities regarding usability, accessibility, and price. This is a critical issue that necessitates immediate attention and resolution. Objective This study’s aims were 3-fold, to (1) understand how members of minoritized low-SES communities perceive current mHealth wearable devices, (2) identify the barriers and facilitators toward adoption, and (3) articulate design requirements for future wearable devices to enable equitable access for these communities. Methods We performed semistructured interviews with low-SES Hispanic or Latine adults (N=19) from 2 metropolitan cities in the Midwest and West Coast of the United States. Participants were asked questions about how they perceive wearables, what are the current benefits and barriers toward use, and what features they would like to see in future wearable devices. Common themes were identified and analyzed through an exploratory qualitative approach. Results Through qualitative analysis, we identified 4 main themes. Participants’ perceptions of wearable devices were strongly influenced by their COVID-19 experiences. Hence, the first theme was related to the impact of COVID-19 on the community, and how this resulted in a significant increase in interest in wearables. The second theme highlights the challenges faced in obtaining adequate health resources and how this further motivated participants’ interest in health wearables. The third theme focuses on a general distrust in health care infrastructure and systems and how these challenges are motivating a need for wearables. Lastly, participants emphasized the pressing need for community-driven design of wearable technologies. Conclusions The findings from this study reveal that participants from underserved communities are showing emerging interest in using health wearables due to the COVID-19 pandemic and health care access issues. Yet, the needs of these individuals have been excluded from the design and development of current devices. 

Task-based intermittent software systems always re-execute peripheral input/output (I/O) operations upon power failures since tasks have all-or-nothing semantics. Re-executed I/O wastes significant time and energy and risks memory inconsistency. This paper presents EaseIO, a new task-based intermittent system that remedies these problems. EaseIO programming interface introduces re-execution semantics for I/O operations to facilitate safe and efficient I/O management for intermittent applications. EaseIO compiler front-end considers the programmer-annotated I/O re-execution semantics to preserve the task's energy efficiency and idem-potency. EaseIO runtime introduces regional privatization to eliminate memory inconsistency caused by idempotence bugs. Our evaluation shows that EaseIO reduces the wasted useful I/O work by up to 3× and total execution time by up to 44% by avoiding 76% of the redundant I/O operations, as compared to the state-of-the-art approaches for intermittent computing. Moreover, for the first time, EaseIO ensures memory consistency during DMA-based I/O operations. 

Wearables are a potentially vital mechanism for individuals to monitor their health, track behaviors, and stay connected. Unfortunately, both price and a lack of consideration of the needs of low-SES communities have made these devices inaccessible and unusable for communities that would most substantially benefit from their affordances. To address this gap and better understand how members of low-SES communities perceive the potential benefits and barriers to using wearable devices, we conducted 19 semi-structured interviews with people from minority, high crime rate, low-SES communities. Participants emphasized a critical need for safety-related wearable devices in their communities. Still, existing tools do not yet address the specific needs of this community and are out of reach due to several barriers. We distill themes on perceived useful features and ongoing obstacles to guide a much-needed research agenda we term ’Equityware’: building wearable devices based on low-SES communities’ needs, comfortability, and limitations.