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oai:riuma.uma.es:10630/334432026-02-03T10:50:42Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc López-Casado, Carmen author Bauzano-Núñez, Enrique author Rivas-Blanco, Irene author Pérez-del-Pulgar-Mancebo, Carlos Jesús author Muñoz-Martínez, Víctor Fernando author 2019-11-26 Minimally invasive surgery (MIS) techniques are growing in quantity and complexity to cover a wider range of interventions. More specifically, hand-assisted laparoscopic surgery (HALS) involves the use of one surgeon’s hand inside the patient whereas the other one manages a single laparoscopic tool. In this scenario, those surgical procedures performed with an additional tool require the aid of an assistant. Furthermore, in the case of a human–robot assistant pairing a fluid communication is mandatory. This human–machine interaction must combine both explicit orders and implicit information from the surgical gestures. In this context, this paper focuses on the development of a hand gesture recognition system for HALS. The recognition is based on a hidden Markov model (HMM) algorithm with an improved automated training step, which can also learn during the online surgical procedure by means of a reinforcement learning process. López-Casado, C.; Bauzano, E.; Rivas-Blanco, I.; Pérez-del-Pulgar, C.J.; Muñoz, V.F. A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery. Sensors 2019, 19, 5182. https://hdl.handle.net/10630/33443 10.3390/s19235182 Laparoscopia Cirugía - Innovaciones tecnológicas Aprendizaje automático (Inteligencia artificial) A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery.