After spending some time thinking on how to use Myo for text input and experimenting a little bit we think we can share some of our findings.
Myo does have some strengths when compared to other input devices.
1- It is minimally intrusive and can be used for mobile interaction.
2- It can sense hand poses.
3- It has IMU with accelerometers and gyros to detect arm movement.
Some of them are due to myo's specific sensing technology
1- There are only a few hand poses that the MYO can recognize
2- It seems to be sensitive to the initial calibration.
3- Hand poses can be stressful and difficult to change between them (this is required for proper detection).
4- Many false negatives (generally for the less stressful poses).
Some are shared with other 3D interface devices:
1-Live mic problem - hand poses can be activated by accident, though rarely.
2-Lack of spatial frame of reference.
To overcome the limitations we tried several things in our design:
1-Restrict the set of hand poses used frequently to the ones that offer less false negatives (wave-in and wave-out).
2-Use the initial set of recognized hand poses as primitives to obtain a larger set ( add gesture and gyroscope data).
3-Allow for continuation of gestures. Since most gestures are stressful, allow to user to specify parameters by continuing the motion.
4-Try to use relative hand positions instead of using absolute space positions.
5-Try to transition between gestures that are easy to perform (some gestures are hard to transition e.g. between fist an open hand).
We hope that these ideas are useful to others designing interaction techniques using Myo.