SMARTWATCH GLANCEABLE VISUALIZATION FOR FAMILY CO-REGULATION WITH ADHD CHILDREN - [PLANNED]
Methods
Interviews
Within-Subject Experiment
High-Fidelity Design
Field deployment
This is a project focused on helping ADHD children develop skills related to emotion self-regulation and goal setting through the collaboration with family members.
This experiment and design study will involve the deployment of a smartwatch and a shared display in the home with visualizations depicting different family member's daily mood and personal goals.
My objective is to investigate the impact to family collaboration and awareness from the use of the different devices. Additionally, it will explore the potential of watchfaces (the watch's home screen) for increased awareness between family members.
SUPPORTING SELF-TRACKING THROUGH VOICE ASSISTANT CONVERSATIONS - [COMPLETED]
Methods
Interviews
Co-design
Low/Mid-Fidelity Design
Field deployment
I have conducted co-design activities to explore people's desired conversational interactions for food journaling and for recollection and reflection of eating behavior.
Based on the co-design sessions, I will develop and deploy conversational journals with Alexa and Google assistant to explore people's perspectives on different conversational styles for food tracking.
SUPPORTING CHILDREN WITH ADHD - [COMPLETED]
Methods
Interviews
High/Low-Fidelity Design
Field deployment
Co-design
Families used an Apple Watch and phone app that promotes children’s self-regulation and self-efficacy with the collaboration of their parents.
I interviewed families about their experiences with the apps and ideal technology support for managing ADHD, as well as app and wearable log analysis.
I am leading co-design activities with parents and children on co-visualizing wearable tracking data, mood, responsibilities/to-dos, and others, for family collaboration around wellbeing and self-regulation.
MULTIMODAL FOOD TRACKING - [COMPLETED]
Methods
Interviews
High/Low-Fidelity Design
Field deployment
Survey
We explored opportunities for leveraging multimodal and multiple devices for food tracking.
This was achieved through the deployment of a prototype for Alexa, Google Assistant, smartphones, computer, and Apple Watch.
We analyzed logs and interviews to investigate people's preferred food description practices, and opportunities for multimodality and multiple devices in food journaling.