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| Content Provider | ACM Digital Library |
|---|---|
| Author | Theodoridis, Theodoros Wolf, Michael Assad, Christopher Glette, Kyrre Stoica, Adrian |
| Abstract | This paper presents the BioSleeve, a new gesture-based human interface for natural robot control. Detailed activity of the user's hand and arm is acquired via surface electromyography sensors and an inertial measurement unit that are embedded in a forearm sleeve. The BioSleeve's accompanying software decodes the sensor signals, classifies gesture type, and maps the result to output commands to an external robot. The current BioSleeve system can reliably decode as many as sixteen discrete hand gestures and estimate the continuous orientation of the forearm. The gestures are used in several modes: for supervisory point-to-goal commands, virtual joystick for teleoperation, and high degree-of-freedom (DOF) mimicked manipulation. We report results from three control applications: a manipulation robot, a small ground vehicle, and a 5-DOF hand. |
| Starting Page | 69 |
| Ending Page | 70 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781467330558 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-03-03 |
| Access Restriction | Subscribed |
| Subject Keyword | Gesture recognition Gesture control Emg |
| Content Type | Text |
| Resource Type | Article |
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