abstract

• This research seeks to establish a precedent for future work in motor skill transfer using a human-to-human interface system. We propose an integrated wearable device for electromyography signal acquisition, an AI-based data classification algorithm and a graphic interface for signal visu-alization. Our proposed design is based on intelligent wearable system composed of a shirt with Nylon-silver fabric electrodes that emulate a conventional textile. The textile electrodes are embedded in body locations optimized to detect muscle signals corresponding to drum playing activity. We demonstrate that the proposed textile electrodes are capable to monitor optimal EMG signal that is useful to train an AI algorithm to classify diverse types of drum strokes, positions and strength level. © 2024 IEEE.

publication date

• 2024-01-01

funding provided via

• Au-tonomus University of San Luis Potosi; Mirai Innovation Research Institute; Universidad Autónoma de Nuevo León, UANL  Grant

published in

• 2024 IEEE/SICE International Symposium on System Integration, SII 2024  Proceedings

keywords

• Electrodes; Signal processing; Textiles; Acquisition systems; Conductive fabrics; Electromyography signals; Human Interface; Interface system; Motor skills; Skill transfer; Textile electrodes; Transfer devices; Wearable devices; Wearable technology

Digital Object Identifier (DOI)

• 10.1109/SII58957.2024.10417562

PubMed ID

start page

• 190

end page

• 195

volume

issue