Khaista Rahman

Interval-valued Pythagorean fuzzy geometric aggregation operators and their application to group decision making problem

There are many aggregation operators have been defined up to date, but in this work, we define the interval valued Pythagorean fuzzy weighted geometric (IPFWG) operator, the interval-valued Pythagorean fuzzy ordered weighted geometric (IPFOWG) operator, and the interval-valued Pythagorean fuzzy hybrid geometric operator. We also discuss some properties and give some examples also to develop these operators. At the last we apply the interval-valued IPFWG operator and the interval-valued IPFOWG operator to multiple attribute decision-making problem under the interval-valued Pythagorean fuzzy information.

Current source with low voltage controlled for surface Electrical Stimulation

Functional Electrical Stimulation (FES) is a promising way to restore mobility to Spinal Cord Injury (SCI) patients by applying low-level electrical current to the paralyzed muscles so as to enhance that persons ability to function and live independently. However, due to the limited number of commercially available FES assisted exerciser systems and their rather high cost, the conventional devices are unaffordable for most peoples. Thus, this paper makes a comparative study of the various design of a multiple purpose portable functional electrical stimulator which is used in surface stimulation for patients with spinal cord injuries. The functionality, circuit performance and reliability of the circuits are presented.

Knee joint impedance hybrid modeling and control of functional electrical stimulation (FES)-cyclingfor paraplegic: Free swinging trajectory

Functional electrical stimulation (FES) has been used to restore the function of paralyzed muscles due to spinal cord injury (SCI). FES induced movement control is a significantly challenging area due to complexity and nonlinearity of musculoskeletal system. A crucial issue of FES is the control of motor function by the artificial activation of paralyzed muscles due to the various characteristics of the underlying physiological/biomechanical system. Muscle response characteristics are nonlinear and time-varying with fatigue issues. In this approach only the quadriceps muscle is stimulated to perform the trajectory motion. This paper presents the initial development of control strategies using FLC and GA in order to optimize the system by FES-cycling trajectory control via Analog Digital Converter, ADC.

Some Interval-Valued Pythagorean Fuzzy Einstein Weighted Averaging Aggregation Operators and Their Application to Group Decision Making

Abstract In this paper, we introduce the notion of Einstein aggregation operators, such as the interval-valued Pythagorean fuzzy Einstein weighted averaging aggregation operator and the interval-valued Pythagorean fuzzy Einstein ordered weighted averaging aggregation operator. We also discuss some desirable properties, such as idempotency, boundedness, commutativity, and monotonicity. The main advantage of using the proposed operators is that these operators give a more complete view of the problem to the decision makers. These operators provide more accurate and precise results as compared the existing method. Finally, we apply these operators to deal with multiple-attribute group decision making under interval-valued Pythagorean fuzzy information. For this, we construct an algorithm for multiple-attribute group decision making. Lastly, we also construct a numerical example for multiple-attribute group decision making.

Some Generalized Intuitionistic Fuzzy Einstein Hybrid Aggregation Operators and Their Application to Multiple Attribute Group Decision Making

Abstract The objective of the present work is divided into threefold. Firstly, we developed intuitionistic fuzzy Einstein hybrid averaging (IFEHA) aggregation operator and intuitionistic fuzzy Einstein hybrid geometric (IFEHG) aggregation operator along with their desirable properties. Secondly, we introduced two generalized aggregation operators along with their desirable properties, namely generalized intuitionistic fuzzy Einstein hybrid averaging (GIFEHA) aggregation operator and generalized intuitionistic fuzzy Einstein hybrid geometric (GIFEHG) aggregation operator. The main advantage of using the proposed methods is that these operators and methods give a more complete view of the problem to the decision makers. These methods provide more general, more accurate and precise results as compared to the existing methods. Therefore, these methods play a vital role in real-world problems. Finally the proposed operators have been applied to decision-making problems to show the validity, practicality and effectiveness of the new approach.

Positioning of EEG electrodes for BCI-FES control system development of knee joint movement for paraplegic

Functional Electrical Stimulation (FES) is a promising method to restore mobility to individuals paralyzed due to spinal cord injury (SCI). This method will provide the electrical pulse to the surface electrodes which are attached to paralyze part such as arm or leg and will make this part constructs because of the pulse given and can achieve the desired movement later. Depend on only FES for a rehabilitation method to SCI patient is not a very effective way. The combination between FES and Brain Computer Interface (BCI) may prove useful and effective way in SCI rehabilitation. BCI is a technology that detects a patients intention. The main target of BCI is to create an alternative way for SCI patients between brain and others partfrom their body. This BCI will record the signal from the brain and then will transfer it to paralyze part which wants to control it. There are many methods to obtain the brain signals in BCI such as electroencephalographic (EEG) measurement technique or brain mapping technique. The EEG measurement technique is mostly used in medical rehabilitation and this technique is using EEG scalp and electrodes. The position of EEG electrodes should be correctly placed according to the appropriate movement. This paper will be discussed on the positioning of EEG electrodes for BCI-FES control system development of knee joint movement for paraplegics.

Pythagorean Fuzzy Einstein Hybrid Averaging Aggregation Operator and its Application to Multiple-Attribute Group Decision Making

Abstract Pythagorean fuzzy set is one of the successful extensions of the intuitionistic fuzzy set for handling uncertainties in information. Under this environment, in this paper, we introduce the notion of Pythagorean fuzzy Einstein hybrid averaging (PFEHA) aggregation operator along with some of its properties, namely idempotency, boundedness, and monotonicity. PFEHA aggregation operator is the generalization of Pythagorean fuzzy Einstein weighted averaging aggregation operator and Pythagorean fuzzy Einstein ordered weighted averaging aggregation operator. The operator proposed in this paper provides more accurate and precise results as compared to the existing operators. Therefore, this method plays a vital role in real-world problems. Finally, we applied the proposed operator and method to multiple-attribute group decision making.