Analyze data from surface EMG sensors, accelerometer, and gyroscope to recognize several hand-motion patterns, which can then be associated with a specific pattern in the 3D printed prosthetic arm 💪🏼
Public and open-source version of a 2018 project using the combination of transcranial magnetic stimulation (TMS) and electromyography (EMG) in order to produce motor maps of the motor cortex of the human brain and represent them on 2 and 3 dimensional forms of an MRI Brain image. This project, source code, and all else within is governed by the AGPL 3.0 license. All modifications, alterations, and reproductions of any part of this project are subject to the terms of the AGPL 3.0 license. For more information regarding the terms of the AGPL 3.0 license, the software, and project as a whole, refer to the README.md file found in the top level of the repository.
Studying facial muscle activation and their relationship with facial kinematics via facial landmarks. Utilizes an Arduino to generate a square wave with a specific duty cycle and frequency and synchronously trigger EMG and image acquisition.
See here for quality control guidelines and suggested filters per MW application type.
Is it also possible to provide users with the number of segments lost due to each of these criterion for easy reporting? Rather than "dropping" segments, can we remove them from the main data and provide the
Merged with #13 and #44
See here for quality control guidelines and suggested filters per MW application type.
Is it also possible to provide users with the number of segments lost due to each of these criterion for easy reporting? Rather than "dropping" segments, can we remove them from the main data and provide the