Forearm Gesture Dataset: Gesture Recognition under Different Arm Postures and Force Levels

_{We present a forearm gesture dataset named "}_FEMG-VPF_{", comprising simultaneously recorded high-density sEMG, sparse multi-channel sEMG, and Euler angle signals of the forearm muscles. High-density sEMG signals were recorded with a 64-channel high-density grid as well as sparse 8-channel sEMG and 3-channel Euler angle signals were recorded with a Myo armband. Specifically, 28 healthy subjects performed 38 hand gestures under two distinct forearm states: 1) the upper arm naturally drooping with the forearm parallel to the ground, and 2) the upper arm naturally drooping with the forearm at a 45-degree angle to the ground. Each arm posture incorporates one resting gesture, 15 finger movements, and 3 grasping gestures. The finger movements encompassed in the database include single-finger movement, double-finger movement, triple-finger movement, and full-hand movements. The grasping gestures incorporate actions grasping cylindrical objects (i.e., mineral water bottles), planar objects (i.e., books), and spherical objects (i.e., tennis balls), respectively. Each gesture was performed in 6 repeated trials, namely four high-force trials and two low-force trials.}

我们提出了一款名为"FEMG-VPF"的前臂手势数据集，该数据集包含同步采集的前臂肌肉高密度表面肌电（surface electromyography, sEMG）、多通道稀疏表面肌电信号以及欧拉角信号。其中，高密度表面肌电信号采用64通道高密度肌电网格采集，8通道稀疏表面肌电信号与3通道欧拉角信号则通过Myo臂带采集。具体而言，28名健康受试者在两种不同的前臂姿态下完成了38种手部手势动作：第一种为上臂自然下垂，前臂与地面平行；第二种为上臂自然下垂，前臂与地面呈45度夹角。每种前臂姿态均包含1种静息手势、15种手指动作与3种抓握手势。本数据集涵盖的手指动作包括单指运动、双指运动、三指运动及全手协同运动。抓握手势则分别对应抓取圆柱形物体（如矿泉水瓶）、平面物体（如书本）及球形物体（如网球）的动作。每种手势均完成6次重复试验，其中4次为高力度试验，2次为低力度试验。