Hierarchical Recurrent-Inception Residual Transformer (HRIRT) for Multidimensional Hand Force Estimation Using Force Myography Sensor

In this letter, we present the hierarchical recurrent-inception residual transformer (HRIRT), an innovative deep neural network architecture designed for accurate hand force estimation in human-robot collaboration (HRC). The HRIRT combines recurrent layers, inception modules, residual connections, t...

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Veröffentlicht in:	IEEE sensors letters 2024-09, Vol.8 (9), p.1-4
Hauptverfasser:	Zafar, Muhammad Hamza, Moosavi, Syed Kumayl Raza, Sanfilippo, Filippo
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Data models Errors Estimation Force force myography (FMG) sensors hand force estimation Hand tools human–robot collaboration (HRC) Machine learning Mathematical models model interpretability Neural networks Real time real-time estimation Robots Sensor applications Sensors Three-dimensional displays Transformers
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