Smart medical device selection based on intuitionistic fuzzy Choquet integral

Büyüközkan, Gülçin; Göçer, Fethullah

doi:10.1007/s00500-018-3563-5

Cited by 54 publications

(46 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The Denavit–Hartenberg modeling method establishes a coordinate system on each connecting rod in the system and uses a 4 × 4 homogeneous transformation matrix to express the relative position of and relationship between the coordinates [ 27 ]. The position coordinates of the center of mass of the connecting rod are shown below:

where c j is the member parameter; l i , θ i are the length of the i member and its angle with the vertical direction; and d i is the distance between the mass center of the member and the joint.…”

Section: Intelligent Medical Treatment and Rehabilitation Treatmenmentioning

confidence: 99%

“…The purpose of lower limb rehabilitation training is to enable the abnormal lower limbs to exercise properly and effectively, promote the healing of damaged joint tissue, enhance the muscle strength of lower limbs, improve the toughness of tendons and ligaments, and improve the mobility, stability, and coordination of joints, so as to gradually recover [ 27 , 28 ].…”

Section: Intelligent Medical Treatment and Rehabilitation Treatmenmentioning

confidence: 99%

See 1 more Smart Citation

Lower Limb Joint Nursing and Rehabilitation System Based on Intelligent Medical Treatment

Geng

Jia

Guo

2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

With the aggravation of the problem of aging population, all kinds of lower limb paralysis caused by various diseases occur frequently. People’s demand for lower limb nursing and rehabilitation treatment is growing. In this paper, combined with intelligent medical technology and lower limb kinematics model, this paper proposes to build a lower limb joint nursing and rehabilitation system based on intelligent medical treatment. It is expected that, through the following limb joint rehabilitation robot as the main rehabilitation means, a smart nursing rehabilitation system which can quickly respond to users and realize remote rehabilitation nursing can be designed. First of all, it is clear that the main body of the lower limb joint rehabilitation system consists of the robot body and the state display system. Then, the sensor, amplifier, and data acquisition card are set in the data acquisition system, and the plantar balance force is detected using a FlexiForce film pressure sensor. The final control system mainly includes the main control module program and the lower limb action recognition program. The motor control software adopts PID regulation method, and the lower limb action recognition adopts SVM one-to-one classification method. After the construction of lower limb joint nursing and rehabilitation system, the accuracy rate of action recognition and classification was tested. In the third experiment, the accuracy of all the movements was 100%. Then, the joint displacement and angle changes of the experimenter assisted by the system were analyzed. The experimenter’s knee joint and hip joint show a normal walking state, and the joint angle changes tend to be normal. Ten out of 55 rehabilitation system users were randomly selected for interview survey. The total scores of operation convenience, wearing comfort, intensity suitability, and movement science of the system were 90, 83, 84, and 91, respectively. This shows that the rehabilitation action designed by the system is scientific and easy to operate and can be put into use in rehabilitation training after improving the wearing comfort.

show abstract

Section: Intelligent Medical Treatment and Rehabilitation Treatmenmentioning

confidence: 99%

Section: Intelligent Medical Treatment and Rehabilitation Treatmenmentioning

confidence: 99%

Lower Limb Joint Nursing and Rehabilitation System Based on Intelligent Medical Treatment

Geng

Jia

Guo

2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

show abstract

“…Tuzkaya [31] suggested that IFCI operators should adopt MCDM method, take advantage of the interaction between fuzziness of decision environment and decision criteria, and combine supplier evaluation processes. Gülçin Büyüközkan et al [32] presented a creative approach to evaluate the smart medical device selection process in a group decision-making with intuitionistic fuzzy set based on fuzzy choquet integral. Mousavi et al [33] adopted a hierarchical group decision-making approach to new product selection based on VIKOR.…”

Section: Related Workmentioning

confidence: 99%

A Group Decision‐Making Approach Based on DST and AHP for New Product Selection under Epistemic Uncertainty

Zhang

Zhong

2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Selecting the most appropriate new product(s) is regarded as a critical decision which greatly influences the development of manufacturing enterprises. In order to improve the accuracy of selection, more experts are required to be invited to predict key indicators for new products selection. Due to limited knowledge, experts use fuzzy numbers more confidently than using numerical values in the prediction. Therefore, new product selection is a multiattribute group decision-making process under epistemic uncertainty. The purpose of this paper is to introduce a new hybrid decision-making approach based on Analytic Hierarchy Process (AHP) and Dempster-Shafer Theory (DST) to evaluate and select a new product. AHP and DST are used in weight determination to improve the accuracy and objectivity. In addition, this paper proposes that DST is a proper mathematical framework to deal with the epistemic uncertainty on the indicators of new product scheme selection. In particular, the initial assessments from experts are disassembled and then combined into the evidence information. By setting confidence degree, reliability function and likelihood function are used to evaluate and rank new products. A case study in a home appliance manufacturer is provided to illustrate the proposed hybrid approach and demonstrate its applicability.

show abstract

“…One of the latest favored methods to evaluate and analyze these problems is based on MCDM concept. Although MCDM approaches are devised to find faster and efficient solutions to problems, if the methodology is not set straight and structured adequately, MCDM cannot guarantee to find the best solution [10]. On the other hand, if MCDM methods are adequately applied, they can play an indispensable role of finding the solution to the problem.…”

Section: Introductionmentioning

confidence: 99%

Improving sustainable supplier evaluation by an integrated MCDM method under pythagorean fuzzy environment

Göçer

2021

Cumhuriyet Science Journal

Self Cite

View full text Add to dashboard Cite

Sustainability plays a significant role in promoting competence and collaboration in supply chain management due to increased environmental awareness, tightened regulations, and government policies. The evaluation of sustainable suppliers and selecting the best one is indispensable for companies to promote sustainability. Due to multi-criteria nature of the supplier selection process, it has been considered as a multi-criteria decision making (MCDM) problem in many studies. In this study, a state-of-the-art MCDM method for sustainable supplier selection is developed by integrating AHP and TOPSIS techniques within the Pythagorean Fuzzy Sets (PFSs) linguistic setting. A Group Decision Making (GDM) environment is utilized due to superiority of group consensus over individual decisions. Finally, an apparel industry example is used to illustrate the effectiveness and feasibility of the proposed sustainable supplier selection method. A comparison with existing techniques and sensitivity analysis are done to verify and validate the given outcome.

show abstract

Smart medical device selection based on intuitionistic fuzzy Choquet integral

Cited by 54 publications

References 66 publications

Lower Limb Joint Nursing and Rehabilitation System Based on Intelligent Medical Treatment

Lower Limb Joint Nursing and Rehabilitation System Based on Intelligent Medical Treatment

A Group Decision‐Making Approach Based on DST and AHP for New Product Selection under Epistemic Uncertainty

Improving sustainable supplier evaluation by an integrated MCDM method under pythagorean fuzzy environment

Contact Info

Product

Resources

About