Anna Pereira1, Juan P Wachs2, Kunwoo Park1, David Rempel3. 1. University of California at Berkeley. 2. Purdue University, West Lafayette, Indiana. 3. University of California at Berkeley david.rempel@ucsf.edu.
Abstract
OBJECTIVE: The purpose of this study was to develop a lexicon for 3-D hand gestures for common human-computer interaction (HCI) tasks by considering usability and effort ratings. BACKGROUND: Recent technologies create an opportunity for developing a free-form 3-D hand gesture lexicon for HCI. METHOD: Subjects (N = 30) with prior experience using 2-D gestures on touch screens performed 3-D gestures of their choice for 34 common HCI tasks and rated their gestures on preference, match, ease, and effort. Videos of the 1,300 generated gestures were analyzed for gesture popularity, order, and response times. Gesture hand postures were rated by the authors on biomechanical risk and fatigue. RESULTS: A final task gesture set is proposed based primarily on subjective ratings and hand posture risk. The different dimensions used for evaluating task gestures were not highly correlated and, therefore, measured different properties of the task-gesture match. APPLICATION: A method is proposed for generating a user-developed 3-D gesture lexicon for common HCIs that involves subjective ratings and a posture risk rating for minimizing arm and hand fatigue.
OBJECTIVE: The purpose of this study was to develop a lexicon for 3-D hand gestures for common human-computer interaction (HCI) tasks by considering usability and effort ratings. BACKGROUND: Recent technologies create an opportunity for developing a free-form 3-D hand gesture lexicon for HCI. METHOD: Subjects (N = 30) with prior experience using 2-D gestures on touch screens performed 3-D gestures of their choice for 34 common HCI tasks and rated their gestures on preference, match, ease, and effort. Videos of the 1,300 generated gestures were analyzed for gesture popularity, order, and response times. Gesture hand postures were rated by the authors on biomechanical risk and fatigue. RESULTS: A final task gesture set is proposed based primarily on subjective ratings and hand posture risk. The different dimensions used for evaluating task gestures were not highly correlated and, therefore, measured different properties of the task-gesture match. APPLICATION: A method is proposed for generating a user-developed 3-D gesture lexicon for common HCIs that involves subjective ratings and a posture risk rating for minimizing arm and hand fatigue.