American Sign Language (ASL) Fingerspelling dataset for Myo Sensor

Published: 16-10-2018| Version 1 | DOI: 10.17632/dbymbhhpk9.1
Contributor:
Prajwal Paudyal

Description

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)

Files

Steps to reproduce

Use Myo armband on the primary hand and collect data for 5s.