UC2018 DualMyo Hand Gesture Dataset

This is set of data obtained from two consumer-market EMG sensors (Myo) with a subject performs 8 distinct hand gestures. There are a total of 110 repetitions of each class of gesture obtained across 5 recording sessions. Besides the data set, which is saved in a python pickle file, we include a python test script to load the data, generate random synthetic sequences of gestures and classify them with multiple models. Gesture library: Rest Closed fist Open hand Wave in Wave out Double-tap Hand down Hand up Device placement: The two Myos are placed on the forearm with the usb port pointing outwards, palm and sensor 5 facing upwards. The Myos are next to one another with their middle position close the the thickest section of the forearm. The outwards Myo is rotated slightly so that sensor 5 is aligned with the axis of the palmaris longus tendon. The Myo inside is rotated so that it has an angle of 22.5 degrees with the first Myo, in clockwise direction (subject perspective). Acquisition protocol: The subjects wear the armbands according to the instructions above. The sensors are run for a few minutes to warm-up. The subjects are requested to hold the positions of the gestures for a few seconds while we record 2 seconds of data. The gestures are repeated in random order in several sessions.本数据集源自两台消费级肌电（Electromyography, EMG）传感器（Myo），由受试者完成8种不同的手部动作。每类手势动作共采集110次重复样本，覆盖5次录制会话。除保存为Python pickle格式文件的数据集外，本次资源还附带一份Python测试脚本，可用于加载数据、生成随机手势合成序列，并通过多种模型对序列进行分类。手势库包含以下动作：静止、握拳、张开手掌、向内挥手、向外挥手、双击、手掌向下、手掌向上。设备放置方式：两台Myo传感器均佩戴于前臂，USB接口朝外，手掌与传感器5朝上。两台传感器彼此紧邻，其中间位置靠近前臂最粗壮的区段。外侧的Myo传感器略作旋转，使传感器5与掌长肌腱的轴线对齐；内侧的Myo传感器则沿受试者视角顺时针方向，与外侧Myo传感器呈22.5度夹角。采集流程：受试者按照上述说明佩戴臂带，传感器需预热数分钟。受试者需保持手势姿势数秒，期间采集2秒时长的肌电数据。所有手势动作将以随机顺序在多次会话中重复完成。