2026-06-01T13:38:37Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/335412026-02-03T11:24:13Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
López Casado, Carmen
author
Bauzano-Núñez, Enrique
author
Rivas-Blanco, Irene
author
Pérez-del-Pulgar-Mancebo, Carlos Jesús
author
Muñoz-Martínez, Víctor Fernando
2024-09-26T17:47:18Z
2024-09-26T17:47:18Z
2019
Lopez-Casado M.C.; Bauzano E.; Rivas-Blanco I.; Perez-del- Pulgar C.J.; Muñoz-Martinez V.F. A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery. MDPI Sensors 2019, 19(23), 5182. December 2019. https://doi.org/10.3390/s19235182
https://hdl.handle.net/10630/33541
10.3390/s19235182
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.
eng
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Cirugía
Robótica
A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery
journal article
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URL
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