DU-ASL-DATA-GLOVE-DB

Hardware The primary hardware is a data glove consisting of three units, namely sensing, processing, and onboard power regulation unit. The sensing unit is comprised of five 2.2" flex sensors (SEN-10264) and an IMU (MPU-6050) which has a triaxial accelerometer and a triaxial gyroscope. Dataset Overview. We explored 40 signs from the standard ASL dictionary that including 26 letters and 14 words. Among these signs, 24 require only a certain finger flexion and no hand motion; hence, are addressed as static signs or gestures. Conversely, the remaining 16 signs need hand motion alongside the finger flexion to portray meaningful expression according to the ASL dictionary. Moreover, we collected the signs from 25 subjects (19 Male and 6 Female) in separate data recording sessions with a consistent protocol. Overall, three channels for acceleration in both body and earth axis, three for angular velocity, four for quaternion, and five for flex sensors were recorded in the dataset. The data was recorded by the data glove processing unit which was connected to a laptop for data storage via USB. The sampling frequency is set to 100 Hz and each gesture was repeated 10 times to record the performance variabilities of each subject. However, during a few sessions denoted in the dataset supplementary information, the laptop charger was connected which resulted in AC-induced noise all over those specific recorded data. Data recording protocol. Before starting the recording process, each subject signed an approval form for the usage of their data in this research and was briefed about the data recording steps. As the subjects were not familiar with the signs before the study, they were taught each sign before the data recording via online video materials. The data was recorded by the data glove and stored on the laptop at the same time. Hence, a Python script was used on the laptop to make the handshake between the two devices and to store the data in separate folders as per the signs and the subjects. At the beginning of each data recording session, the subjects were prompted to declare their subject id and the gesture name. Afterward, a five-second countdown is prompted on the laptop screen for preparation. Each instance of the gesture data is recorded for a 1.5 seconds window and the subjects can easily perform their gesture once within that window. In a single gesture recording session, this process is repeated 10 times.硬件配置：本数据集的核心硬件为数据手套（data glove），包含三个功能单元，分别为传感单元、处理单元与机载电源调节单元。其中传感单元由5个2.2英寸柔性传感器（型号SEN-10264）以及一枚集成三轴加速度计与三轴陀螺仪的惯性测量单元（Inertial Measurement Unit, IMU，MPU-6050）组成。 数据集概览：本数据集从标准美国手语（American Sign Language, ASL）词典中选取了40种手势，涵盖26个字母与14个单词。其中24种手势仅需特定手指屈曲动作，无需手部移动，因此归类为静态手势；剩余16种手势则需配合手部移动与手指屈曲动作，以符合ASL词典的表意规范。此外，本数据集通过统一的实验流程，分多批次采集了25名受试者（19名男性、6名女性）的手势数据。本数据集共采集多通道传感数据：包含体轴与地轴方向的三轴加速度数据、三轴角速度数据、4通道四元数数据以及5通道柔性传感器数据。数据由数据手套的处理单元采集，并通过USB连接至笔记本电脑进行存储。采样频率设置为100Hz，且每位受试者的每种手势均重复采集10次，以记录不同受试者的动作表现差异。但在数据集补充材料中注明的部分采集批次中，因笔记本电脑连接了市电充电器，导致对应采集数据中引入了交流市电干扰噪声。 数据采集流程：采集开始前，每位受试者需签署知情同意书，授权其数据用于本研究，并由实验人员讲解数据采集步骤。由于受试者在实验前均不熟悉目标手势，实验人员将通过在线视频材料，在采集前为每位受试者教学所需的手势动作。数据由数据手套实时采集并同步存储至笔记本电脑，为此实验人员在笔记本电脑上运行Python脚本，实现设备间的通信握手，并按照手势类别与受试者信息将数据分别存储至对应文件夹。每一轮采集批次开始时，系统会提示受试者输入受试者编号与当前手势名称，随后在笔记本电脑屏幕上显示5秒倒计时以供受试者准备。每段手势数据的采集时长为1.5秒，受试者需在此窗口内完成一次手势动作。每一种手势的采集流程均重复10次。