Women are increasingly turning to technology to monitor their everyday health and manage major life events such as menopause and fertility. However, the design of apps and wearables commonly make promises they are unable to keep and assumptions which do not line up with people's everyday realities. In this talk, we discuss a few years of research on how women's health tracking apps have often excluded certain types of people and their needs, created or perpetuated feelings of anxiety, and presented unrealistic expectations of control. We will also introduce our ongoing project with SURF-IoT student Marawin Chheang on how people perceive descriptions of AI and algorithms in apps designed to promote fertility. Daniel Epstein is an Assistant Professor in the Department of Informatics at the University of California, Irvine with a courtesy appointment in the Department of Computer Science. His work examines how personal tracking technology can acknowledge and account for the realities of everyday life, designing new technology and studying people's use of current technology. He has explored and designed technology for personal tracking around physical activity, diet, migraine, mood, and menstruation. Yunan Chen is an Associate Professor in the Department of Informatics at the University of California, Irvine. Her research interests lie at the intersection of Human-Computer Interaction (HCI), Computer Supported Cooperative Work (CSCW) and Health Informatics. In particular, she is interested in designing and evaluating interactive systems for clinical documentation, patient-provider interaction, and personal information management for chronic care. Mayara Costa Figueiredo is an Informatics PhD at the University of California, Irvine, working under the supervision of Dr. Yunan Chen. Her research interests lie at the intersections of human-computer interaction (HCI), computer-supported cooperative work (CSCW), and health informatics. She focuses on the use of patient-generated health data and its consequences. She is currently investigating the challenges and uncertainties women face when self-tracking their fertility for different goals, and the role that current technology, particularly mobile apps, play in this complex and potentially emotionally-loaded context.

Nikil Dutt, Distinguished Professor, Computer Science Amir Rahmani, Asst. Professor, Nursing (Join via Zoom link below)

Jesse Jackson, Assoc. Professor, Arts-Studio Art Rapid Response Design & Making at the Speculative Prototyping Lab (Register via Zoom link below)

2020 SURF-IoT fellows and projects: Marawin Chheang Project: Understanding User Perceptions of Algorithms Prediction in Personal Health Aviv Benchorin Project: Live Update Service for ZotCare Multi-Level IoT-Based Health Monitoring System John Le Project: Mobile and Webapp for ZotCare Multi-Level IoT-Based Health Monitoring System Jonathan Sugijoto Project: Smart Watches/Rings as a Predictive/Preventative for Sleep Promotion in Pregnant Women Judit Castellanos Project: Pain Buddy - Treating Pain in Children with Cancer Ananth Krishnan Project: Rapid Response Design & Making at the Speculative Prototyping Lab Yilei Wu Project: Applications of Deep Learning in 3D Cardiac MRI Segmentation Angelou Lao Project: Continuous Physiological Monitoring for COVID-19 Darwin Salgado Project: Detection of SARS-CoV-2 Virus in Salivahas Melinda Li Project: IoT Application to Monitor COVID-19 Social Distancing on Campus Miriam Munoz Project: Evaluating the Feasibility of Conducting Language and Cognitive Assessments for Bilingual Children using Telepractice: A Validity Study Yuchong Chen Project: WIoT Data Analysis for Dementia Family Caregiver Home Visit Intervention Study Regine DeGuman Project: Exploring Multimodal Voice Interface Design in Alexa Games for Children Vikram Miryala Project: A Privacy Policy Engine for the Internet of Things Jiaxin Luo Project: Translating Audiological Tests from Labs to Homes Shuyang Zhang Project: Translating Audiological Tests from Labs to Homes Xinghua Zhou Project: Translating Audiological Tests from Labs to Homes Jiawen Zhang Project: Understanding Patient Questions about their Medical Data and How such Questions are Answered through the Collective Wisdom in Online Patient Communities