Reading Face, Reading Health: Exploring Face Reading Technologies for Everyday Health

Biosensors & Physiological MonitoringContext-Aware ComputingPhysicians, Nurses & CliniciansPsychiatrists & Psychotherapists

With the recent advancement in computer vision, Artificial Intelligence (AI), and mobile technologies, it has become technically feasible for computerized Face Reading Technologies (FRTs) to learn about one's health in everyday settings. However, how to design FRT-based applications for everyday health practices remains unexplored. This paper presents a design study with a technology probe called Faced, a mobile health checkup application based on the facial diagnosis method from Traditional Chinese Medicine (TCM). A field trial of Faced with 10 participants suggests potential usage modes and highlights a number of critical design issues in the use of FRTs for everyday health, including adaptability, practicality, sensitivity, and trustworthiness. We end by discussing design implications to address the unique challenges of fully integrating FRTs into everyday health practices.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/chi/4430/2019

AdRecommended

Learn AI Coding at CodeNow

At a Glance

Paper Snapshot

fact_check
dataset
Source
CHI
calendar_month
Year
2019
emoji_events
Award
No award tagged
group
Authors
6 authors
sell
Subtopics
Biosensors & Physiological Monitoring, Context-Aware Computing
work
Professions
Physicians, Nurses & Clinicians, Psychiatrists & Psychotherapists
article
Content Status
Abstract only
hub
Related Papers
2 related papers