Abstract
Over the past decade, smartwatches and other medical wearable devices have been marketed as tools that empower people to monitor their own health. They can track biomarkers such as glucose, heart rate, and stress, and flag concerning trends long before a routine clinic visit. At the same time, they quietly shift everyday monitoring work, such as charging, interpreting alerts, and deciding when to seek care, from clinicians to patients and their families. That shift doesn’t hit everyone the same way. Older adults, residents of rural areas, and those with less money or digital literacy often struggle to meet the new expectations that medical wearables create. My coupled thesis sits in the middle of this tension. On the technical side, I worked on Lumos, a multi-wavelength photoplethysmography (PPG) smartwatch aimed at medical-grade sensing. On the STS side, I examined how medical wearables, promoted as access tools, shift monitoring labor from clinicians to patients and families, and with what unequal effects by class, disability, age, and geography. Together, these projects address the sociotechnical problem of how wearable health systems can be made both technically reliable and socially equitable.
My technical report addresses the problem of storing large volumes of physiological data on a small, power-constrained wearable device in a way that is robust, safe, and transparent to users and clinicians. For the Lumos smartwatch project, I developed a C++ flash memory driver and an append-only logging library designed to preserve high-rate, multi-channel sensor data even when the watch is offline and subject to power interruptions. The system uses a low-level driver to perform reset, read, program, and erase operations, while the higher-level logging layer writes structured records with sequence numbers and checksums, skipping corrupt blocks and recovering the current write position. This architecture allows the watch to resume logging after reboots without overwriting prior data, which is essential for real-world wearable use where charging and restarting are common. In testing, the system filled one flash block every twenty minutes and provided twenty-eight days of storage capacity. A 7.5-hour logging session produced records that were all successfully recovered with no corrupted entries observed. Overall, this project shows that reliable, long-term wearable data storage can be achieved on constrained embedded hardware without the overhead of a general-purpose filesystem, making Lumos a stronger platform for research-grade sensing.
My STS research paper examines the same broader issue from the perspective of ethics, inequality, and care work. I ask how medical wearables, often framed as tools of empowerment and access, redistribute monitoring labor from clinicians to patients and families, and how that redistribution is shaped by class, disability, age, and geography. Using a structured qualitative synthesis of peer-reviewed literature along with case studies, I argue that wearable devices do not simply make care more convenient. Rather, they relocate the labor of monitoring into homes and relationships. Patients and caregivers must keep devices charged, worn, and interpreted, while also deciding when alerts or trends require professional intervention. This labor is not distributed equally. Studies show that wearable adoption varies by income, education, and age, and that users with fewer resources often face greater barriers to effective participation in remote monitoring. Further research shows that these systems can provide reassurance while also generating new burdens of vigilance and responsibility. Additionally, clinicians are not removed from the system, since remote monitoring often creates additional work in the form of education, troubleshooting, and coordination. I conclude that medical wearables should be evaluated not only by whether they expand access to health data, but also by how much hidden labor they require, how equitably they fit into different lives, and how clearly they assign responsibility when something goes wrong.
Taken together, these two projects show the value of approaching medical wearables as a sociotechnical problem rather than only a technical one. Although these projects do not address every challenge involved in remote monitoring, they contribute to a broader understanding of what more responsible wearable design should require.
