Name
Abstract | ||
|---|---|---|
Wearables are increasingly used during training to quantify performance and provide valuable real-time information. However, interacting with these devices in motion may disrupt the movements of the activity. We propose a method of interaction involving tapping specific locations on the body, identify candidate locations for running and cycling, and compare them in a series of controlled experiments with athletes. A purpose-built prototype measures speed of interaction and gives feedback cues for athletes to report the physical effects on the activity itself. Our results suggest that specific locations are faster and have minimal disruption to movement, even under induced fatigue conditions. The overall method is fast - 1.31s for running and 1.65s for cycling. Preferred locations differ significantly across sports, with stable body parts ranking higher. We effectively demonstrated the use of a single hand for interaction during running with two distinct tap gestures. A set of guidelines inform the design of new sports technologies. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3206505.3206527 | AVI'18: PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON ADVANCED VISUAL INTERFACES |
Keywords | Field | DocType |
Running, cycling, sports training, on-body interaction, interaction in motion | Athletes,Ranking,Computer science,Wearable computer,Gesture,Cycling,Human–computer interaction,Tapping | Conference |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Velko Vechev | 1 | 26 | 2.91 |
| Alexandru Dancu | 2 | 50 | 8.33 |
| Simon T. Perrault | 3 | 196 | 19.15 |
| Quentin Roy | 4 | 18 | 4.33 |
| Morten Fjeld | 5 | 531 | 73.73 |
| Shengdong Zhao | 6 | 963 | 78.40 |