Abstract
| Original language | English |
|---|---|
| Title of host publication | CHI EA 17 : Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems |
| Place of Publication | New York |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 2180-2186 |
| ISBN (Print) | 978-1-4503-4656-6 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | 35th Annual ACM CHI Conference on Human Factors in Computing Systems (CHI 2017) - Colorado Convention Center, Denver, United States Duration: 6 May 2017 → 11 May 2017 Conference number: 35 https://chi2017.acm.org/ http://www.scopus.com/inward/record.url?scp=85019570374&partnerID=8YFLogxK (Link to publication in Scopus) |
Conference
| Conference | 35th Annual ACM CHI Conference on Human Factors in Computing Systems (CHI 2017) |
|---|---|
| Abbreviated title | ACM CHI 2017 |
| Country | United States |
| City | Denver |
| Period | 6/05/17 → 11/05/17 |
| Internet address |
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WaveTrace: motion matching input using Wrist-Worn Motion sensors. / Verweij, D.; Esteves, A.E.; Khan, J.V.; Bakker, S.
CHI EA 17 : Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems. New York : Association for Computing Machinery, Inc, 2017. p. 2180-2186.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - WaveTrace: motion matching input using Wrist-Worn Motion sensors
AU - Verweij, D.
AU - Esteves, A.E.
AU - Khan, J.V.
AU - Bakker, S.
PY - 2017
Y1 - 2017
N2 - We present WaveTrace, a novel interaction technique based on selection by motion matching. In motion matching systems, targets move continuously in a singular and pre-defined path -- users interact with these by performing a synchronous bodily movement that matches the movement of one of the targets. Unlike previous work which tracks user input through optical systems, WaveTrace is arguably the first motion matching technique to rely on motion data from inertial measurement units readily available in many wrist-worn wearable devices such as smart watches. To evaluate the technique, we conducted a user study in which we varied: hand; degrees of visual angle; target speed; and number of concurrent targets. Preliminary results indicate that the technique supports up to eight concurrent targets; and that participants could select targets moving at speeds between 180 and 270/s (mean acquisition time of 2237ms, and average success rate of 91%).
AB - We present WaveTrace, a novel interaction technique based on selection by motion matching. In motion matching systems, targets move continuously in a singular and pre-defined path -- users interact with these by performing a synchronous bodily movement that matches the movement of one of the targets. Unlike previous work which tracks user input through optical systems, WaveTrace is arguably the first motion matching technique to rely on motion data from inertial measurement units readily available in many wrist-worn wearable devices such as smart watches. To evaluate the technique, we conducted a user study in which we varied: hand; degrees of visual angle; target speed; and number of concurrent targets. Preliminary results indicate that the technique supports up to eight concurrent targets; and that participants could select targets moving at speeds between 180 and 270/s (mean acquisition time of 2237ms, and average success rate of 91%).
U2 - 10.1145/3027063.3053161
DO - 10.1145/3027063.3053161
M3 - Conference contribution
SN - 978-1-4503-4656-6
SP - 2180
EP - 2186
BT - CHI EA 17 : Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems
PB - Association for Computing Machinery, Inc
CY - New York
ER -