Mirror Game - CC Measure

Code used in the Mirror Game project to automatically detect Co-Confidence (CC) motion. See details in (Noy, Binun &amp;Golland, 2015).<br>The code is published here in order to describe the exact details of the alogrithm. Some of the functions might need other toolboxes to run. I tried to put all needed functions here, contact me if something is missing.<br>The two main function that compute the CC detection are:MG_Tools_CC_AZCMG_Tools_Segments_Acc_Zero_Cross<br>See inside the code for detailed information<br><br><br><br><br><br><br><br><br>Ref:<br>L. Noy, N. Levit-Binun, and Y. Golland, “Being in the zone: physiological markers of togetherness in joint improvisation”, <b>Frontiers in Human Neuroscience</b>, 9:187, <b>2015</b> <br>本代码为镜像游戏（Mirror Game）项目中用于自动检测共同置信度（Co-Confidence, CC）动作的相关代码，详细信息可参见(Noy, Binun & Golland, 2015)。 本代码公开于此，旨在完整呈现该算法的具体细节。部分功能函数需借助其他工具箱方可运行。笔者已尽力将所有所需函数收录于此，若存在缺失，可联系作者沟通。 用于执行CC检测的两大核心函数为：MG_Tools_CC_AZC 与 MG_Tools_Segments_Acc_Zero_Cross。详细信息请参阅代码内部注释。 参考文献：L. Noy、N. Levit-Binun与Y. Golland，《进入心流状态：联合即兴创作中"同在感"的生理标记物》，《人类神经科学前沿（Frontiers in Human Neuroscience）》，9卷187期，2015年。