Publication: Long-Term Stable Electromyography Classification Using Canonical Correlation Analysis
Long-Term Stable Electromyography Classification Using Canonical Correlation Analysis
Date
Date
Date
Citations
Donati, E., Benatti, S., Ceolini, E., & Indiveri, G. (2023). Long-Term Stable Electromyography Classification Using Canonical Correlation Analysis. Proceedings of the International IEEE/EMBS Conference on Neural Engineering, online. https://doi.org/10.1109/ner52421.2023.10123768
Abstract
Abstract
Abstract
Discrimination of hand gestures based on the decoding of surface electromyography (sEMG) signals is a well-establish approach for controlling prosthetic devices and for Human-Machine Interfaces (HMI). However, despite the promising results achieved by this approach in well-controlled experimental conditions, its deployment in long-term real-world application scenarios is still hindered by several challenges. One of the most critical challenges is maintaining high EMG data classification performance across multiple days without retrain
Metrics
Downloads
Views
Additional indexing
Creators (Authors)
- Donati, Elisa
- Benatti, Simone
- Ceolini, Enea
Event Title
Event Title
Event Title
Event Location
Event Location
Event Location
Event Country
Event Country
Event Country
Event Start Date
Event Start Date
Event Start Date
Event End Date
Event End Date
Event End Date
Page range/Item number
Page range/Item number
Page range/Item number
Item Type
Item Type
Item Type
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Language
Language
Language
Date available
Date available
Date available
Series Name
Series Name
Series Name
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
ISBN or e-ISBN
ISBN or e-ISBN
ISBN or e-ISBN
Additional Information
Additional Information
Additional Information
OA Status
OA Status
OA Status
Publisher DOI
Metrics
Downloads
Views
Citations
Donati, E., Benatti, S., Ceolini, E., & Indiveri, G. (2023). Long-Term Stable Electromyography Classification Using Canonical Correlation Analysis. Proceedings of the International IEEE/EMBS Conference on Neural Engineering, online. https://doi.org/10.1109/ner52421.2023.10123768
