Implementation of ANN-Based Auto-Adjustable for a Pneumatic Servo System Embedded on FPGA

Cabrera-Rufino, Marco-Antonio; Ramos-Arreguín, Juan Manuel; Rodríguez‐Reséndiz, Juvenal; Gorrostieta-Hurtado, Efrén; Aceves-Fernández, Marco Antonio

doi:10.3390/mi13060890

Cited by 9 publications

(5 citation statements)

References 18 publications

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“…Recent advances in the fields of robotics, sensors control, computer vision, and artificial intelligence have fueled rapid growth in the area of medical robotics [ 34 , 35 , 36 ]. Over the last few decades, several types of endovascular robots have been developed.…”

Section: Key Technologies and Application Areas Of Vascular Intervent...mentioning

confidence: 99%

Technical and Clinical Progress on Robot-Assisted Endovascular Interventions: A Review

Duan

Akinyemi

et al. 2023

Micromachines

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Prior methods of patient care have changed in recent years due to the availability of minimally invasive surgical platforms for endovascular interventions. These platforms have demonstrated the ability to improve patients’ vascular intervention outcomes, and global morbidities and mortalities from vascular disease are decreasing. Nonetheless, there are still concerns about the long-term effects of exposing interventionalists and patients to the operational hazards in the cath lab, and the perioperative risks that patients undergo. For these reasons, robot-assisted vascular interventions were developed to provide interventionalists with the ability to perform minimally invasive procedures with improved surgical workflow. We conducted a thorough literature search and presented a review of 130 studies published within the last 20 years that focused on robot-assisted endovascular interventions and are closely related to the current gains and obstacles of vascular interventional robots published up to 2022. We assessed both the research-based prototypes and commercial products, with an emphasis on their technical characteristics and application domains. Furthermore, we outlined how the robotic platforms enhanced both surgeons’ and patients’ perioperative experiences of robot-assisted vascular interventions. Finally, we summarized our findings and proposed three key milestones that could improve the development of the next-generation vascular interventional robots.

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Section: Key Technologies and Application Areas Of Vascular Intervent...mentioning

confidence: 99%

Technical and Clinical Progress on Robot-Assisted Endovascular Interventions: A Review

Duan

Akinyemi

et al. 2023

Micromachines

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“…Robots. An articulated robot is an open chain structure composed of a series of connecting linkages connected by joints [26,27]. To accurately describe the robot's poses, this paper uses D-H method, which constructs a kinematic model using a fourth-order transformation homogeneous matrix to describe the relationships of adjacent links and deriving the positional relationships of each linkage relative to the base in a recursive manner.…”

Section: The Kinematic Model Of Articulatedmentioning

confidence: 99%

The Parallel Solving Method of Robot Kinematic Equations Based on FPGA

Zhang,

Jiang,

Zhe

2023

Journal of Robotics

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In the implementation of robot motion control, complex kinematic computations consume too much central processing unit (CPU) time and affect the responsiveness of robot motion. To solve this problem, this paper proposes a parallel method for solving kinematic equations of articulated robots based on the coordinate rotation digital computer (CORDIC) algorithm. The method completes the fast calculation of the transcendental function based on the CORDIC algorithm, adopts the tree structure method to optimize the key computational paths of forward and inverse solutions, and designs a parallel pipeline to realize the low latency and high throughput of the kinematic equations. The experiments of the proposed method are validated based on the field-programmable gate array (FPGA) hardware experimental platform, and the experimental results demonstrate that the computational time to complete the entire kinematic equations is 4.68 μs, of which the computational time for the kinematic positive solution is 0.52 μs and the computational time for the kinematic inverse solution is 4.16 μs.

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“…These schemes have been used mainly in classification problems [ 23 ], object detection [ 24 ], image processing [ 25 ], and to estimate sustainable transport demand [ 26 ], controllers [ 27 , 28 ], melanoma detection [ 29 ], among others.…”

Section: Preliminariesmentioning

confidence: 99%

Design and Implementation of a Prosthesis System Controlled by Electromyographic Signals Means, Characterized with Artificial Neural Networks

et al. 2022

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Around the world many people loss a body member for many reasons, where advances of technology may be useful to help these people to improve the quality of their lives. Then, designing a technologically advanced prosthesis with natural movements is worthy for scientific, commercial, and social reasons. Thus, research of manufacturing, designing, and signal processing may lead up to a low-cost affordable prosthesis. This manuscript presents a low-cost design proposal for an electromyographic electronic system, which is characterized by a neural network based process. Moreover, a hand-type prosthesis is presented and controlled by using the processed electromyographic signals for a required particular use. For this purpose, the user performs several movements by using the healthy-hand to get some electromyographic signals. After that, the obtained signals are processed in a neural network based controller. Once an usable behavior is obtained, an exact replica of controlled motions are adapted for the other hand by using the designed prosthesis. The characterization process of bioelectrical signals was performed by training twenty characteristics obtained from the original raw signal in contrast with other papers in which seven characteristics have been tested on average. The proposed model reached a 95.2% computer test accuracy and 93% accuracy in a real environment experiment. The platform was tested via online and offline, where the best response was obtained in the online execution time.

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Implementation of ANN-Based Auto-Adjustable for a Pneumatic Servo System Embedded on FPGA

Cited by 9 publications

References 18 publications

Technical and Clinical Progress on Robot-Assisted Endovascular Interventions: A Review

Technical and Clinical Progress on Robot-Assisted Endovascular Interventions: A Review

The Parallel Solving Method of Robot Kinematic Equations Based on FPGA

Design and Implementation of a Prosthesis System Controlled by Electromyographic Signals Means, Characterized with Artificial Neural Networks

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