Real-Time and Embedded Detection of Hand Gestures with an IMU-Based Glove†
Journal Title: Informatics - Year 2018, Vol 5, Issue 2
Abstract
This article focuses on the use of data gloves for human-computer interaction concepts, where external sensors cannot always fully observe the user’s hand. A good concept hereby allows to intuitively switch the interaction context on demand by using different hand gestures. The recognition of various, possibly complex hand gestures, however, introduces unintentional overhead to the system. Consequently, we present a data glove prototype comprising a glove-embedded gesture classifier utilizing data from Inertial Measurement Units (IMUs) in the fingertips. In an extensive set of experiments with 57 participants, our system was tested with 22 hand gestures, all taken from the French Sign Language (LSF) alphabet. Results show that our system is capable of detecting the LSF alphabet with a mean accuracy score of 92% and an F1 score of 91%, using complementary filter with a gyroscope-to-accelerometer ratio of 93%. Our approach has also been compared to the local fusion algorithm on an IMU motion sensor, showing faster settling times and less delays after gesture changes. Real-time performance of the recognition is shown to occur within 63 milliseconds, allowing fluent use of the gestures via Bluetooth-connected systems.
Authors and Affiliations
Chaithanya Kumar Mummadi, Frederic Philips Peter Leo, Keshav Deep Verma, Shivaji Kasireddy, Philipp M. Scholl, Jochen Kempfle and Kristof Van Laerhoven
Keywords
Related Articles
- EP ID EP44132
- DOI https://doi.org/10.3390/informatics5020028
- Views 219
- Downloads 0
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Acknowledgement to Reviewers of Informatics in 2016
The editors of Informatics would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016. We greatly appreciate the contribution of expert reviewers, which is crucial to the...