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The data was collected by a Kinect V2 as a set of X, Y, Z coordinates at 60 fps during 6 different yoga inspired back stretches. There are 541 files in the dataset, each containing position, velocity for 25 body joints. These joints include: Head, Neck, SpineShoulder, SpineMid, SpineBase, ShoulderRight, ShoulderLeft, HipRight, HipLeft, ElbowRight, WristRight, HandRight, HandTipRight, ThumbRight, ElbowLeft, WristLeft, HandLeft, HandTipLeft, ThumbLeft, KneeRight, AnkleRight, FootRight, KneeLeft, AnkleLeft, FootLeft. The program used to record this data was adapted from Thomas Sanchez Langeling’s skeleton recording code. The file was set to record data for each body part as a separate file, repeated for each exercise. Each bodypart for a specific exercise is stored in a distinct folder. These folders are named with the following convention: subjNumber_stretchName_trialNumber The subjNumber ranged from 0 – 8. The stretchName was one of the following: Mermaid, Seated, Sumo, Towel, Wall, Y. The trialNumber ranged from 0 – 9 and represented the repetition number. These coordinates were chosen to have an origin centered at the subject’s upper chest. The data was standardized to the following conditions: 1) Kinect placed at the height of 2 ft and 3 in 2) Subject consistently positioned 6.5 ft away from the camera with their chests facing the camera 3) Each participant completed 10 repetitions of each stretch before continuing on Data was collected from the following population: * Adults ages 18-21 * Females: 4 * Males: 5 The following types of pre-processing occurred at the time of data collection. Velocity Data: Calculated using a discrete derivative equation with a spacing of 5 frames chosen to reduce sensitivity of the velocity function v[n]=(x[n]-x[n-5])/5 Occurs for all body parts and all axes individually Related manuscript: Capella, B., Subrmanian, D., Klatzky, R., & Siewiorek, D. Action Pose Recognition from 3D Camera Data Using Inter-frame and Inter-joint Dependencies. Preprint at link in references. |
