scholarly journals Development Status and Multilevel Classification Strategy of Medical Robots

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1278
Author(s):  
Yingwei Guo ◽  
Yingjian Yang ◽  
Yang Liu ◽  
Qiang Li ◽  
Fengqiu Cao ◽  
...  
Keyword(s):  
Medical Science ◽  
Service Robots ◽  
Classification Methods ◽  
Surgical Robots ◽  
Medical Robots ◽  
Development Status ◽  
Rehabilitation Robots ◽  
Artificial Intelligence Technology ◽  
Classification Strategy ◽  
Multilevel Classification

The combination of artificial intelligence technology and medical science has inspired the emergence of medical robots with novel functions that use new materials and have a neoteric appearance. However, the diversity of medical robots causes confusion regarding their classification. In this paper, we review the concepts pertinent to major classification methods and development status of medical robots. We survey the classification methods according to the appearance, function, and application of medical robots. The difficulties surrounding classification methods that arose are discussed, for example, (1) it is difficult to make a simple distinction among existing types of medical robots; (2) classification is important to provide sufficient applicability to the existing and upcoming medical robots; (3) future medical robots may destroy the stability of the classification framework. To solve these problems, we proposed an innovative multilevel classification strategy for medical robots. According to the main classification method, the medical robots were divided into four major categories—surgical, rehabilitation, medical assistant, and hospital service robots—and personalized classifications for each major category were proposed in secondary classifications. The technologies currently available or in development for surgical robots and rehabilitation robots are discussed with great emphasis. The technical preferences of surgical robots in the different departments and the rehabilitation robots in the variant application scenes are perceived, by which the necessity of further classification of the surgical robots and the rehabilitation robots is shown and the secondary classification strategy for surgical robots and rehabilitation robots is provided. Our results show that the distinctive features of surgical robots and rehabilitation robots can be highlighted and that the communication between professionals in the same and other fields can be improved.

On the Principle and Application of Concrete Admixtures

2012 ◽  
Vol 557-559 ◽  
pp. 805-808
Author(s):  
Tao Zhang ◽  
Yun Yun Xu ◽  
Lei Chen
Keyword(s):  
Development Prospect ◽  
Construction Technology ◽  
Classification Methods ◽  
Development Status ◽  
Concrete Admixtures ◽  
Working Principle ◽  
Early Strength ◽  
Future Direction ◽  
Air Entraining Agents

Widely used for concrete admixtures, the development status of concrete admixtures is summarized, the two classification methods of concrete admixtures are induced. Especially, currently mainly used four kinds of admixtures, water reducer, air entraining agents, retarders, and early strength agent, the working principle, the problem of construction application, the direction of development and construction technology are analyzed. Finally, admixture overall future direction of development prospect is presented.

scholarly journals Extract Executable Action Sequences from Natural Language Instructions Based on DQN for Medical Service Robots

2021 ◽  
Vol 16 (2) ◽  
Author(s):  
Fengda Zhao ◽  
Zhikai Yang ◽  
Xianshan Li ◽  
Dingding Guo ◽  
Haitao Li
Keyword(s):  
Natural Language ◽  
Short Term Memory ◽  
Average Length ◽  
Service Robots ◽  
Short Term ◽  
Medical Robots ◽  
Agent Based ◽  
Action Sequences ◽  
Long Short Term Memory ◽  
Better Than

The emergence and popularization of medical robots bring great convenience to doctors in treating patients. The core of medical robots is the interaction and cooperation between doctors and robots, so it is crucial to design a simple and stable human-robots interaction system for medical robots. Language is the most convenient way for people to communicate with each other, so in this paper, a DQN agent based on long-short term memory (LSTM) and attention mechanism is proposed to enable the robots to extract executable action sequences from doctors’ natural language instructions. For this, our agent should be able to complete two related tasks: 1) extracting action names from instructions. 2) extracting action arguments according to the extracted action names. We evaluate our agent on three datasets composed of texts with an average length of 49.95, 209.34, 417.17 words respectively. The results show that our agent can perform better than similar agents. And our agent has a better ability to handle long texts than previous works.

scholarly journals Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success

2020 ◽  
Vol 31 (2) ◽  
pp. 267-289
Author(s):  
Daniel Belanche ◽  
Luis V. Casaló ◽  
Carlos Flavián ◽  
Jeroen Schepers
Keyword(s):  
Attribution Theory ◽  
Service Providers ◽  
Service Failure ◽  
Experimental Studies ◽  
Service Robots ◽  
Frontline Employees ◽  
Content Type ◽  
Attributions Of Responsibility ◽  
Service Failures ◽  
Artificial Intelligence Technology

PurposeService robots are taking over the organizational frontline. Despite a recent surge in studies on this topic, extant works are predominantly conceptual in nature. The purpose of this paper is to provide valuable empirical insights by building on the attribution theory.Design/methodology/approachTwo vignette-based experimental studies were employed. Data were collected from US respondents who were randomly assigned to scenarios focusing on a hotel’s reception service and restaurant’s waiter service.FindingsResults indicate that respondents make stronger attributions of responsibility for the service performance toward humans than toward robots, especially when a service failure occurs. Customers thus attribute responsibility to the firm rather than the frontline robot. Interestingly, the perceived stability of the performance is greater when the service is conducted by a robot than by an employee. This implies that customers expect employees to shape up after a poor service encounter but expect little improvement in robots’ performance over time.Practical implicationsRobots are perceived to be more representative of a firm than employees. To avoid harmful customer attributions, service providers should clearly communicate to customers that frontline robots pack sophisticated analytical, rather than simple mechanical, artificial intelligence technology that explicitly learns from service failures.Originality/valueCustomer responses to frontline robots have remained largely unexplored. This paper is the first to explore the attributions that customers make when they experience robots in the frontline.

Robin heart progress - advances material and technology in surgical robots

2010 ◽  
Vol 58 (2) ◽  
pp. 323-327 ◽  
Author(s):  
Z. Nawrat
Keyword(s):  
Material Science ◽  
Surgical Robot ◽  
Surgical Robots ◽  
Medical Robots ◽  
Surgical Tools ◽  
Current State

Robin heart progress - advances material and technology in surgical robotsThe paper presents the current state of works conducted by the Zabrze team under the Robin Heart surgical robot and the Robin Heart Uni System mechatronic surgical tools project as a example of introducing technology and materials advances for progress in surgical robots. The special intention of the author is to show the review of the current and futuristic medical robots needs in the area of material science.

scholarly journals Remote Monitoring System Based on Artificial Intelligence Technology

2022 ◽  
Vol 2146 (1) ◽  
pp. 012039
Author(s):  
Fanhua Wang ◽  
Jiangli Qu
Keyword(s):  
Remote Monitoring ◽  
Intelligent System ◽  
Information Age ◽  
It Industry ◽  
Remote Monitoring System ◽  
Development Status ◽  
Future Challenges ◽  
Artificial Intelligence Technology ◽  
Smart Tv

Abstract With the advent of the information age, IOTT has been favored by many industries and has become another profound revolution in the IT industry. In such an era, the application of IOTT in IB construction can broaden the practicability of intelligent system, ORA, improve the management and service ability of IB, so as to improve people’s quality of life. This paper expounds the development status and future challenges of IOTH, and analyzes the interactive design of smart TV.

Review on Development Status and Key Technologies of Surgical Robots

2020 ◽  
Author(s):  
Yingwei Guo ◽  
Yingjian Yang ◽  
Mengting Feng ◽  
Fengqiu Cao ◽  
Hanhui Wu ◽  
...  
Keyword(s):  
Surgical Robots ◽  
Development Status ◽  
Key Technologies

Robots: The Sorcerer's Apprentice Broom?

2012 ◽  
Vol 20 (3) ◽  
pp. 356-364
Author(s):  
Hendrik van Brussel
Keyword(s):  
Health Care ◽  
Real World ◽  
Research Field ◽  
Industrial Robots ◽  
Service Robots ◽  
Research Experience ◽  
Major Research ◽  
Daily Lives ◽  
Rehabilitation Robots ◽  
Research Questions

By virtue of its outspoken multidisciplinarity, robotics is an extremely popular research field, but is not always exercised by researchers with the broad scientific view required to make breakthroughs. This leads to a very fragmentary research landscape. Robots have their roots in fiction (the Sorcerer’s Apprentice, Frankenstein, Golem, RUR). Their first appearance in the real world came in the early 1960s when Unimation sold their first industrial robots. However, only recently are robots invading people’s daily lives, as service robots, and in health care, as surgery robots, intelligent wheelchairs, and rehabilitation robots, for example. This migration from structured factory environments to cluttered homes is a tremendous step, requiring much more intelligent behaviour. In this paper, the major research questions to be answered will be outlined and illustrated with partial solutions, mainly taken from the author’s own research experience at KU Leuven.

Body-Supported Medical Robots: A Survey

2004 ◽  
Vol 16 (5) ◽  
pp. 513-519 ◽  
Author(s):  
Peter Berkelman ◽  
◽  
Jocelyne Troccaz ◽  
Philippe Cinquin ◽  
Keyword(s):  
Robot Manipulator ◽  
Medical Robotics ◽  
The Body ◽  
Medical Procedure ◽  
Pedicle Screw Placement ◽  
Surgical Robots ◽  
Medical Robots ◽  
Robot Systems ◽  
Set Up ◽  
Improved Accuracy

In medical robotics applications it is often advantageous for a robot to be directly mounted on or supported by the body of the patient during a medical procedure or examination. Whereas early medical robot systems were generally manipulator arms with a large base resting on the floor or mounted to the table next to the patient, several more recently developed systems rest directly on the patient. Body-supported medical robots can be designed to be much more compact and lightweight, leading to improved accuracy and safety and reduced cost, and are easier to set up and use in the operating room environment compared to conventional robot manipulator arms. Five examples of body-supported surgical robots are surveyed in this paper: The ARTHROBOT for total hip arthroplasty, PRAXITELES for knee arthroplasty, MARS for spinal pedicle screw placement and drill guiding, TER for remote ultrasound examinations, and LER for endoscope positioning in minimally invasive surgery.

scholarly journals Performance of Hybrid Ensemble Classification Techniques for Prevalence of Heart Disease Prediction

2019 ◽  
Vol 8 (10) ◽  
pp. 1875-1882
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Medical Science ◽  
The Body ◽  
Ensemble Classification ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Classification Methods ◽  
K Nearest Neighbor ◽  
Classification Techniques

In medical science, heart disease is being considered as fatal problem and in every seconds most of the people dies due to this problem. In heart disease, typically heart stops blood supply to other parts of the body. Hence, proper functioning of body stopped and affected. In this way, timely and accurate prediction of heart disease is an important concern in medical science domain. Diagnosing of heart patients with previous medical history is not being considered as reliable in many aspects. However, machine learning techniques have mystery to classify heart disease data efficiently and effectively and provide reliable solutions. In the past, prediction of heart disease problem various machine learning tools and techniques have been adopted. In this study, hybrid ensemble classification techniques like bagging, boosting, Random Subspace Method (RSM) and Random Under Sampling (RUS) boost are proposed and performance is compared with simple base classification techniques like decision tree, logistic regression, Naive Bays, Support Vector Machine, k-Nearest Neighbor (KNN), Bays Net (BN) and Multi Layer Perceptron (MLP). The heart disease dataset from Kaggle data source containing 305 samples and Matlab R2017a machine learning tool are considered for performance evaluation. Finally, the experimental results stated that hybrid ensemble classification methods outperforms than simple base classification methods in terms of accuracy

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