Wearable Multisensory Glove for Shape, Size, and Stiffness Recognition Based on Off-the-Shelf Components

This dataset contains multisensory time-series recordings collected using a wearable glove designed for object recognition based on shape, size, and stiffness. The glove integrates off-the-shelf sensing components, including five force-sensing resistors (FSR402) placed on the fingertips and five 6-axis inertial measurement units (MPU6050) positioned on the posterior distal phalanges. The sensors provide tactile and proprioceptive information during grasping interactions. The dataset was collected from five subjects interacting with 16 3D-printed objects. The objects belong to four shapes: cube, parallelepiped, tetrahedron, and sphere. Each shape was produced in two sizes, large and small, and two stiffness levels, hard and soft. For each trial, participants wore the glove and performed a grasp–hold–release action on one object. Each subject repeated the interaction 30 times per object, resulting in a total of 2400 trials