Float - One-Handed and Touch-Free Target Selection on Smartwatches
Association for Computing Machinery (ACM) via YouTube
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Explore a conference talk presenting Float, an innovative wrist-to-finger input approach for one-handed and touch-free target selection on smartwatches. Learn about the development process, including motion space exploration for wrist tilt and finger tap detection using photoplethysmogram (PPG) signals combined with accelerometer and gyroscope data. Discover how Float achieves high efficiency and precision using only commercially-available built-in sensors, allowing users to acquire targets of various sizes quickly and accurately in both stationary and walking contexts. Gain insights into the experimental results, limitations, and comparisons with direct touch interaction on smartwatches.
Syllabus
Introduction
Calculations
Sensors
Accuracy
Limitations
Experiments
Questions
Comparison
Taught by
ACM SIGCHI