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Informatics 2018, 5(2), 28; https://doi.org/10.3390/informatics5020028

Real-Time and Embedded Detection of Hand Gestures with an IMU-Based Glove

1
Faculty of Engineering, University of Freiburg, 79085 Freiburg im Breisgau, Germany
2
Ubiquitous Computing, University of Siegen, 57068 Siegen, Germany
This article builds upon an original conference paper [1], targeting the use of the IMU-based glove for generic gestures, and including additional experiments regarding the fusion of IMU data.
*
Author to whom correspondence should be addressed.
Received: 28 February 2018 / Revised: 4 June 2018 / Accepted: 6 June 2018 / Published: 11 June 2018
(This article belongs to the Special Issue Sensor-Based Activity Recognition and Interaction)
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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. View Full-Text
Keywords: gesture recognition; data gloves; inertial sensing; hand articulation tracking gesture recognition; data gloves; inertial sensing; hand articulation tracking
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Mummadi, C.K.; Leo, F.P.P.; Verma, K.D.; Kasireddy, S.; Scholl, P.M.; Kempfle, J.; Laerhoven, K.V. Real-Time and Embedded Detection of Hand Gestures with an IMU-Based Glove. Informatics 2018, 5, 28.

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