American Sign Language (ASL) Fingerspelling dataset for Myo Sensor

This is the dataset used in the following publication. Please cite this publication if use this dataset: This work was published on the 2017 ACM IUI . @inproceedings{paudyal2016sceptre, title={Sceptre: a pervasive, non-invasive, and programmable gesture recognition technology}, author={Paudyal, Prajwal and Banerjee, Ayan and Gupta, Sandeep KS}, booktitle={Proceedings of the 21st International Conference on Intelligent User Interfaces}, pages={282--293}, year={2016}, organization={ACM} } @inproceedings{paudyal2017dyfav, title={Dyfav: Dynamic feature selection and voting for real-time recognition of fingerspelled alphabet using wearables}, author={Paudyal, Prajwal and Lee, Junghyo and Banerjee, Ayan and Gupta, Sandeep KS}, booktitle={Proceedings of the 22nd International Conference on Intelligent User Interfaces}, pages={457--467}, year={2017}, organization={ACM} } 9 users wore the Myo Armband and data was collected for 5s. for each letter of the alphabet. The first 8 columns contain data for the 8 EMG pods, the next 3 are for Accelerometer, the next 3 are for Gyroscope and the final 3are for Orientation (Roll, Pitch and Yaw)

本数据集用于以下已发表的研究成果，若使用本数据集，请引用对应出版物：该成果发表于2017年ACM智能用户界面国际会议（ACM IUI）。

@inproceedings{paudyal2016sceptre, 标题="Sceptre: 普适性、非侵入式且可编程的手势识别技术", 作者="Paudyal, Prajwal、Banerjee, Ayan、Gupta, Sandeep KS", 会议论文集="第21届智能用户界面国际会议论文集", 页码="282--293", 年份="2016", 出版机构="ACM" }

@inproceedings{paudyal2017dyfav, 标题="Dyfav: 面向可穿戴设备实时识别手指拼写字母的动态特征选择与投票方法", 作者="Paudyal, Prajwal、Lee, Junghyo、Banerjee, Ayan、Gupta, Sandeep KS", 会议论文集="第22届智能用户界面国际会议论文集", 页码="457--467", 年份="2017", 出版机构="ACM" }

共有9名受试者佩戴Myo臂环（Myo Armband），针对字母表中的每个字母采集时长为5秒的传感数据。数据集前8列对应8个肌电（EMG）传感器单元的数据，紧随其后的3列为加速度计（Accelerometer）数据，再后续3列为陀螺仪（Gyroscope）数据，最后3列为姿态角数据（滚转、俯仰与偏航）

搜集汇总

背景与挑战

背景概述

该数据集是一个用于Myo传感器的美国手语（ASL）手指拼写数据集，包含9名用户佩戴Myo臂带收集的字母拼写数据，每个字母记录5秒，数据涵盖EMG、加速度计、陀螺仪和方向信息。它主要用于活动识别和美国手语研究，支持手势识别技术的开发，并遵循CC BY 4.0许可。