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Reverse engineering on an electromyographic device, the Myo armband
The Myo armband is a commercially available electromyographic (EMG) device which can be used in a variety of applications where muscle activity has to be measured. In the current application, it is used to control upper-limb exoskeletons for rehabilitation purposes.
Keywords: electromyography, electronics, signal processing, exoskeleton, robotics, human robot interaction, mechatronics, engineering, rehabilitation
The Neural Control of Movement Lab (NCM) and the Rehabilitation Engineering Lab (RELab) are both using the Myo armband to control exoskeletons. The Myo armband is an electromygraphic device to measure muscle activity on the forearm. It is composed of 8 dry surface electrodes and sends the measured EMG signals via Bluetooth to a nearby computer. Raw data generated by the Myo clearly reflects muscle activity but has no common measure with a professional setup; data are downsampled because of the Bluetooth connection, probably filtered and unitless. This is not optimal for a proper assessment of muscle activities. Thereby, the device remains a black box to the user and the inner data processing is unknown. Finally, the design and sizing of the Myo is not versatile among different sizes especially for thin forearms, i.e. for children.
Therefore, the project will be to: evaluate the transfer function of the Myo armband, i.e. what is the output signal for a given input signal, tear it down in order to identify components and inner functioning, and eventually reassemble it in different configurations (with less electrodes to fit thinner forearm).
The Neural Control of Movement Lab (NCM) and the Rehabilitation Engineering Lab (RELab) are both using the Myo armband to control exoskeletons. The Myo armband is an electromygraphic device to measure muscle activity on the forearm. It is composed of 8 dry surface electrodes and sends the measured EMG signals via Bluetooth to a nearby computer. Raw data generated by the Myo clearly reflects muscle activity but has no common measure with a professional setup; data are downsampled because of the Bluetooth connection, probably filtered and unitless. This is not optimal for a proper assessment of muscle activities. Thereby, the device remains a black box to the user and the inner data processing is unknown. Finally, the design and sizing of the Myo is not versatile among different sizes especially for thin forearms, i.e. for children.
Therefore, the project will be to: evaluate the transfer function of the Myo armband, i.e. what is the output signal for a given input signal, tear it down in order to identify components and inner functioning, and eventually reassemble it in different configurations (with less electrodes to fit thinner forearm).
**Tasks**
System identification:
- Black box analysis: find transfer function (e.g. with Matlab system identification).
- Input different waveform (sinus, rectangle, dc) and analyze Myo output -> find filters.
- Find Myo saturation level, compare Myo raw data with professional setup, etc.
Myo teardown:
- Open up the Myo while minimizing damages.
- Identify components, routing, etc.
- Analyze electrodes design and amplification electronics.
Myo reassembly:
- Try to reassemble the Myo with less electrodes and make it work (may be problematic on software side).
**Your Profile**
- self-organized and independent
- disciplined
- reliable
better to have:
- experience in electronics
- experience in processing
- experience with Matlab
nice to have:
- experience in reverse engineering
- already living in Zurich
**Tasks**
System identification:
- Black box analysis: find transfer function (e.g. with Matlab system identification). - Input different waveform (sinus, rectangle, dc) and analyze Myo output -> find filters. - Find Myo saturation level, compare Myo raw data with professional setup, etc.
Myo teardown:
- Open up the Myo while minimizing damages. - Identify components, routing, etc. - Analyze electrodes design and amplification electronics.
Myo reassembly:
- Try to reassemble the Myo with less electrodes and make it work (may be problematic on software side).
**Your Profile**
- self-organized and independent - disciplined - reliable
better to have:
- experience in electronics - experience in processing - experience with Matlab
nice to have:
- experience in reverse engineering - already living in Zurich
Submit your letter of motivation, a CV and a record of your studies to:
Charles Lambelet
Neural Control of Movement Lab, NCM Lab
ETH Zürich
charles.lambelet@hest.ethz.ch
http://www.ncm.hest.ethz.ch/
Submit your letter of motivation, a CV and a record of your studies to: