3D movement and muscle activity patterns in a violin bowing task

Objective: Overuse injuries in violinists are a problem that has been primarily analyzed through the use of questionnaires. Simultaneous 3D motion analysis and EMG to measure muscle activity has been suggested as a quantitative technique to explore this problem by identifying movement patterns and muscular demands which may predispose violinists to overuse injuries. This multi-disciplinary analysis technique has, so far, had limited use in the music world. The purpose of this study was to use it to characterize the demands of a violin bowing task. Subjects: Twelve injury-free violinists volunteered for the study. The subjects were assigned to a novice or expert group based on playing experience, as determined by questionnaire. Design and Settings: Muscle activity and movement patterns were assessed while violinists played five bowing cycles (one bowing cycle = one down-bow + one up-bow) on each string (G, D, A, E), at a pulse of 4 beats per bow and 100 beats per minute. Measurements: An upper extremity model created using coordinate data from markers placed on the right acromion process, lateral epicondyle of the humerus and ulnar styloid was used to determine minimum and maximum joint angles, ranges of motion (ROM) and angular velocities at the shoulder and elbow of the bowing arm. Muscle activity in right anterior deltoid, biceps brachii and triceps brachii was assessed during maximal voluntary contractions (MVC) and during the playing task. Data were analysed for significant differences across the strings and between experience groups. Results: Elbow flexion/extension ROM was similar across strings for both groups. Shoulder flexion/extension ROM increaslarger for the experts. Angular velocity changes mirrored changes in ROM. Deltoid was the most active of the muscles assessed (20% MVC) and displayed a pattern of constant activation to maintain shoulder abduction. Biceps and triceps were less active (4 - 12% MVC) and showed a more periodic 'on and off pattern. Novices' muscle activity was higher in all cases. Experts' muscle activity showed a consistent pattern across strings, whereas the novices were more irregular. The agonist-antagonist roles of biceps and triceps during the bowing motion were clearly defined in the expert group, but not as apparent in the novice group. Conclusions: Bowing movement appears to be controlled by the shoulder rather than the elbow as shoulder ROM changed across strings while elbow ROM remained the same. Shoulder injuries are probably due to repetition as the muscle activity required for the movement is small. Experts require a smaller amount of muscle activity to perform the movement, possibly due to more efficient muscle activation patterns as a result of practice. This quantitative multidisciplinary approach to analysing violinists' movements can contribute to fuller understanding of both playing demands and injury mechanisms .

Players and Avatars: The Connections between Player Personality, Avatar Personality, and Behavior in Video Games

The increasing variety and complexity of video games allows players to choose how to behave and represent themselves within these virtual environments. The focus of this dissertation was to examine the connections between the personality traits (specifically, HEXACO traits and psychopathic traits) of video game players and player-created and controlled game-characters (i.e., avatars), and the link between traits and behavior in video games. In Study 1 (n = 198), the connections between player personality traits and behavior in a Massively Multiplayer Online Roleplaying Game (World of Warcraft) were examined. Six behavior components were found (i.e., Player-versus-Player, Social Player-versus-Environment, Working, Helping, Immersion, and Core Content), and each was related to relevant personality traits. For example, Player-versus-Player behaviors were negatively related to Honesty-Humility and positively related to psychopathic traits, and Immersion behaviors (i.e., exploring, role-playing) were positively related to Openness to Experience. In Study 2 (n = 219), the connections between player personality traits and in-game behavior in video games were examined in university students. Four behavior components were found (i.e., Aggressing, Winning, Creating, and Helping), and each was related to at least one personality trait. For example, Aggressing was negatively related to Honesty-Humility and positively related to psychopathic traits. In Study 3 (n = 90), the connections between player personality traits and avatar personality traits were examined in World of Warcraft. Positive player-avatar correlations were observed for all personality traits except Extraversion. Significant mean differences between players and avatars were observed for all traits except Conscientiousness; avatars had higher mean scores on Extraversion and psychopathic traits, but lower mean scores on the remaining traits. In Study 4, the connections between player personality traits, avatar traits, and observed behaviors in a life-simulation video game (The Sims 3) were examined in university students (n = 93). Participants created two avatars and used these avatars to play The Sims 3. Results showed that the selection of certain avatar traits was related to relevant player personality traits (e.g., participants who chose the Friendly avatar trait were higher in Honesty-Humility, Emotionality, and Agreeableness, and lower in psychopathic traits). Selection of certain character-interaction behaviors was related to relevant player personality traits (e.g., participants with higher levels of psychopathic traits used more Mean and fewer Friendly interactions). Together, the results of the four studies suggest that individuals generally behave and represent themselves in video games in ways that are consistent with their real-world tendencies.