Smart Cable-Driven Camera Robotic Assistant

Rivas-Blanco, Irene; López-Casado, Carmen; Pérez-del-Pulgar, Carlos Jesús; Garcia-Vacas, F.; Fraile, Juan-Carlos; Muñoz, V.F.

doi:10.1109/thms.2017.2767286

Cited by 23 publications

(9 citation statements)

References 37 publications

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“…The different robot actions have been further analyzed and verified in previous works of our group. The endoscope motion combines a reactive behavior based on instrument tracking with a proactive behavior based on the surgery workflow [26]. This control makes it possible to accommodate the camera view to the current state of the task with enough flexibility enable it to adapt its behavior to unplanned or unforeseen situations.…”

Section: Methodsmentioning

confidence: 99%

A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery

López-Casado

Bauzano

Rivas-Blanco

et al. 2019

Sensors

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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.

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Section: Methodsmentioning

confidence: 99%

A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery

López-Casado

Bauzano

Rivas-Blanco

et al. 2019

Sensors

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“…Gras and Yang studied eye‐tracking method for autonomous laparoscope control. Rivas‐Blanco et al proposed a vision‐based field of view control method based on reinforcement learning. However, it is difficult to build the production rules and cognize the surgical task.…”

Section: Introductionmentioning

confidence: 99%

Visual‐based autonomous field of view control of laparoscope with safety‐RCM constraints for semi‐autonomous surgery

Sun

Pan

et al. 2020

Robotics Computer Surgery

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Purpose The surgeon is not timely in direct control of his field of view. Autonomous laparoscope control can provide appropriate surgical field of view and facilitate the intelligent level of surgical robot system. Methods This study explores an autonomous laparoscope control framework for semiautonomous surgery. We propose a novel concept that integrates two forms of Remote Center of Motion (RCM) constraint. We also propose a novel safety‐RCM model to cope with the collision condition. We modify the image Jacobian matrix to realize RCM constraint. The two models constitute a dual‐RCM constraint for robot laparoscope arm. We perform validation of the algorithm with two experiments. Results The experimental results show that the RCM position error can be reduced with the dual‐RCM constraint. Owing to safety‐RCM model, autonomous surgical field of view control could still be realized in case of collision. Conclusion The autonomous laparoscope control could be realized with safety‐RCM and dual‐RCM algorithms.

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“…Moreover, the actuator elements that assist lens positioning and provide stabilization functions play a significant role in ensuring the high performance of camera modules. It is essential that mobile cameras used in biomedical applications are compact in size as well as highly accurate [2].…”

Section: Introductionmentioning

confidence: 99%

Next Generation Autofocus and Optical Image Stabilization System for Camera Modules Using Magnetic Shape Memory Actuators

Gabdullin

Ahmad

2020

IEEE Access

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Currently, camera modules are used in a wide range of applications ranging from micropositioning actuator systems used in smartphones to larger modules used in stationary cameras, CCTV, and others. Modern camera modules are required to perform positioning functions to improve the stability and quality of captured images. These functions mainly include the autofocus (AF) and optical image stabilization (OIS) functions. Traditionally, separate actuators and sensors are used for AF and OIS, each contributing towards energy consumption, module size, and manufacturing costs. This is particularly disadvantageous in the case of smartphones owing to their inherent space and battery charge limitations. This paper presents a novel Magnetic Shape Memory (MSM) actuator system that combines the AF and OIS functions, which are performed using two actuators; thus, this system is a simple, compact, and costeffective solution to the drawbacks of conventional technology. Furthermore, the smart properties of MSM alloys reduce the energy consumption of these systems through the utilization of their inherent holding forces and the associated shape memory effect. The realization of AF and OIS functions is discussed and verified experimentally for the proposed actuator system using data obtained from a fabricated prototype.

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Smart Cable-Driven Camera Robotic Assistant

Cited by 23 publications

References 37 publications

A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery

A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery

Visual‐based autonomous field of view control of laparoscope with safety‐RCM constraints for semi‐autonomous surgery

Next Generation Autofocus and Optical Image Stabilization System for Camera Modules Using Magnetic Shape Memory Actuators

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