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.硬件系统：本数据集的核心硬件为一款数据手套，包含传感、处理与板载电源调节三个功能单元。其中传感单元由5个2.2英寸柔性传感器（SEN-10264）和一块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。 数据集概述：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种仅需特定手指屈曲动作，无需手部移动，因此被归类为静态手势；反之，剩余16种手势需配合手部移动与手指屈曲动作，方可准确表达美国手语词典中定义的语义。此外，本数据集由25名受试者（19名男性、6名女性）通过统一的录制流程完成数据采集，所有数据均在独立的录制会话中获取。整体而言，本数据集共采集以下模态的数据：体轴与地轴方向的三轴加速度信号、三轴角速度信号、四元数数据（共4通道）以及柔性传感器数据（共5通道）。数据由数据手套的处理单元采集，并通过USB接口连接至笔记本电脑完成存储。采样频率设定为100Hz，且每名受试者需重复完成每个手势10次，以采集不同执行场景下的动作变异性数据。但在数据集补充信息中标记的部分录制会话中，由于笔记本电脑连接了充电器，导致对应录制数据中出现了交流电源感应噪声。 数据录制流程：正式开始录制前，每名受试者需签署知情同意书，授权其数据用于本研究，并由研究人员讲解数据录制流程。由于受试者在研究前并不熟悉目标手势，研究人员会通过在线视频材料预先教授每名受试者所有目标手势。数据由数据手套采集并同步存储至笔记本电脑，为此研究人员在笔记本电脑上运行Python脚本，实现数据手套与电脑的通信握手，并按照手势类别与受试者编号将数据存储至对应文件夹。在每个录制会话开始时，系统会提示受试者播报其受试者编号与当前录制的手势名称，随后笔记本电脑屏幕将显示5秒倒计时，供受试者准备动作。每个手势样本的录制时长为1.5秒窗口，受试者可在该窗口内轻松完成一次手势动作。在单个手势的录制会话中，该流程需重复执行10次。