Float: One-Handed and Touch-Free Target Selection on Smartwatches

Touch interaction on smartwatches suffers from the awkwardness of having to use two hands and the "fat finger" problem. We present Float, a wrist-to-finger input approach that enables one-handed and touch-free target selection on smartwatches with high efficiency and precision using only commercially-available built-in sensors. With Float, a user tilts the wrist to point and performs an in-air finger tap to click. To realize Float, we first explore the appropriate motion space for wrist tilt and determine the clicking action (finger tap) through a user-elicitation study. We combine the photoplethysmogram (PPG) signal with accelerometer and gyroscope to detect finger taps with a recall of 97.9% and a false discovery rate of 0.4%. Experiments show that using just one hand, Float allows users to acquire targets with size ranging from 2mm to 10mm in less than 2s to 1s, meanwhile achieve much higher accuracy than direct touch in both stationary (98.9%) and walking (71.5%) contexts.

@inproceedings{ke2017, author = {Sun, Ke and Wang, Yuntao and Yu, Chun and Yan, Yukang and Wen, Hongyi and Shi, Yuanchun}, title = {Float: One-Handed and Touch-Free Target Selection on Smartwatches}, year = {2017}, isbn = {9781450346559}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3025453.3026027}, doi = {10.1145/3025453.3026027}, abstract = {}, booktitle = {Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems}, pages = {692–704}, numpages = {13}, keywords = {finger gesture, one-handed interaction, target selection, smartwatch, tilt}, location = {Denver, Colorado, USA}, series = {CHI '17} }