The EAVI ExG Muscle/brain hybrid physiological sensing
Atau Tanaka, David Fierro, Francesco Di Maggio, Martin Klang, and Stephen Whitmarsh
Proceedings of the International Conference on New Interfaces for Musical Expression
- Year: 2023
- Location: Mexico City, Mexico
- Track: Demos
- Pages: 566–568
- Article Number: 80
- DOI: 10.5281/zenodo.11189290 (Link to paper)
- PDF link
Abstract:
We present an update on the EAVI physiological interface, a wireless, microcontroller based hardware design for the acquisition of bioelectrical signals. The system has been updated to process electroencephalogram brain signals in addition to muscle electromyogram. The hardware/firmware system interfaces with host software carrying out feature extraction and signal processing. Recent advances in electronics have made physiological computing applications practical and feasible. However, there is a gap between high end biomedical equipment and consumer DIY solutions. The hardware design we present here bridges this gap, and combines a specialized biosignal acquisition chip mated with a general-purpose microcontroller. It is based on the Texas Instruments ADS129x family a single chip integrated solution for high quality biosignal amplification and digitization. It serves as analogue front end via programmable gain amplifiers to a 24bit delta-sigma analog-digital converter. The microcontroller is the STMicroelectronics STM32F427, a Cortex-M4 family microcontroller with floating point unit . In addition to EMG acquisition, the board includes a Kionix KX122 three-axis accelerometer . The TI and Kionix sensing chipts communicate with the ST microcontroller over an I2C digital serial bus. The board communicates with the host computer or rest of the music system wirelessly over Bluetooth LE 4.2 using an ST SPBTLE-1S transceiver. The board can also communicate over USB where it registers with the host as a class compliant audio and MIDI device. Audio and physiological signals are treated in the same signal processing chain using the OWL framework. The demo will show multichannel EMG, and single channel EEG. We call this hybridization “ExG”. We will present documentation of the EAVI board used in the lab and on stage, in user studies with neuro-diverse musicians and trained instrumentalists, as well as in performance with the experimental all-female band, Chicks on Speed.
Citation:
Atau Tanaka, David Fierro, Francesco Di Maggio, Martin Klang, and Stephen Whitmarsh. 2023. The EAVI ExG Muscle/brain hybrid physiological sensing. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.11189290BibTeX Entry:
@inproceedings{nime2023_80, abstract = {We present an update on the EAVI physiological interface, a wireless, microcontroller based hardware design for the acquisition of bioelectrical signals. The system has been updated to process electroencephalogram brain signals in addition to muscle electromyogram. The hardware/firmware system interfaces with host software carrying out feature extraction and signal processing. Recent advances in electronics have made physiological computing applications practical and feasible. However, there is a gap between high end biomedical equipment and consumer DIY solutions. The hardware design we present here bridges this gap, and combines a specialized biosignal acquisition chip mated with a general-purpose microcontroller. It is based on the Texas Instruments ADS129x family a single chip integrated solution for high quality biosignal amplification and digitization. It serves as analogue front end via programmable gain amplifiers to a 24bit delta-sigma analog-digital converter. The microcontroller is the STMicroelectronics STM32F427, a Cortex-M4 family microcontroller with floating point unit . In addition to EMG acquisition, the board includes a Kionix KX122 three-axis accelerometer . The TI and Kionix sensing chipts communicate with the ST microcontroller over an I2C digital serial bus. The board communicates with the host computer or rest of the music system wirelessly over Bluetooth LE 4.2 using an ST SPBTLE-1S transceiver. The board can also communicate over USB where it registers with the host as a class compliant audio and MIDI device. Audio and physiological signals are treated in the same signal processing chain using the OWL framework. The demo will show multichannel EMG, and single channel EEG. We call this hybridization “ExG”. We will present documentation of the EAVI board used in the lab and on stage, in user studies with neuro-diverse musicians and trained instrumentalists, as well as in performance with the experimental all-female band, Chicks on Speed.}, address = {Mexico City, Mexico}, articleno = {80}, author = {Atau Tanaka and David Fierro and Francesco Di Maggio and Martin Klang and Stephen Whitmarsh}, booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression}, doi = {10.5281/zenodo.11189290}, editor = {Miguel Ortiz and Adnan Marquez-Borbon}, issn = {2220-4806}, month = {May}, numpages = {3}, pages = {566--568}, title = {The EAVI ExG Muscle/brain hybrid physiological sensing}, track = {Demos}, url = {http://nime.org/proceedings/2023/nime2023_80.pdf}, year = {2023} }