Informing the Design of Novel Input Methods with Muscle Coactivation Clustering

被引:33
作者
Bachynskyi, Myroslav [1 ]
Palmas, Gregorio [2 ]
Oulasvirta, Antti [3 ]
Weinkauf, Tino [2 ]
机构
[1] Cluster Excellence MMCI, D-66123 Saarbrucken, Germany
[2] Max Planck Inst Informat, D-66123 Saarbrucken, Germany
[3] Aalto Univ, Sch Elect Engn, Otakaari 13000, Finland
关键词
Muscle coactivation clustering; user interface design; physical ergonomics; user performance; biomechanical simulation; MOTOR-PERFORMANCE VARIES; ARM MOVEMENTS; DYNAMIC SIMULATIONS; DIFFERENT PARTS; UPPER-EXTREMITY; SPACE; SPEED; ACTIVATION; AMPLITUDE; CAPACITY;
D O I
10.1145/2687921
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This article presents a novel summarization of biomechanical and performance data for user interface designers. Previously, there was no simple way for designers to predict how the location, direction, velocity, precision, or amplitude of users' movement affects performance and fatigue. We cluster muscle coactivation data from a 3D pointing task covering the whole reachable space of the arm. We identify 11 clusters of pointing movements with distinct muscular, spatio-temporal, and performance properties. We discuss their use as heuristics when designing for 3D pointing.
引用
收藏
页数:25
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