Validation Stage Research Articles

Echocardiography Based Cardiac Ischemic Detection Using Red-CNN Classifier

One of the most vital and hardest-working organs of the human body is the Heart. Nevertheless, a condition termed Cardiac Ischemia or CAD is engendered by the inadequate supply of blood along with oxygen to the heart muscle. So, with the aid of a Regularisation Dropout-centered Convolutional Neural Network (ReD-CNN) classifier, an efficient CAD detection system is proposed. At first, the input videos and the data are amassed from the Echonet Dynamic dataset. Next, frame conversion is undergone by the input video. For further processing, keyframes are extracted and preprocessed after frame conversion. Afterward, by means of a Contraction Expansion-Residual Network (CE-ResNet), the heart chambers are segmented, and then the features are extracted. Simultaneously, utilizing the Feynman Kan Formalism-based Tissue Doppler Imaging (FKF-TDI) approach, wall motion is estimated. Meanwhile, the features are extracted from the data and grouped via Average Distance-centric Fuzzy C Means (AD-FCM). After that, mapping of the features extracted from the frames and the grouped features occurs and the resultant data is divided into training, testing, along with validation stages. Then, utilizing the Cosine Similarity-centered Circulatory System Based Optimization (2(CS)BO) methodology, the Feature Selection (FS) is done. Therefore, to compute the Ischemic index, the features that are selected and the estimated wall motions are wielded. Lastly, for effective classification, the Ischemic index and the selected features are fed into the ReD-CNN classifier. Finally, to ascertain the superiority of this technique, the proposed system’s performance is contrasted with the prevailing methodologies.

Construction and validation of the Nursing Care Self-assessment Scale in Obstetric Services (EAESO)

Objective: To describe the stages of construction and validation of the Nursing Care Self-Assessment Scale in Obstetric Services. Methods: Methodological study, based on the Psychometric Model proposed by Pasquali. The stages were covered: theoretical foundation; selection and elaboration of items and domains; content validation. Descriptive statistical analysis was performed. Internal validity of the construct analyzed by the Content Validity Coefficient and internal consistency by Cronbach's alpha. Results: Scale with 31 items for self-assessment of obstetric nursing care evaluated by 7 experts. Items with a Content Validity Coefficient of less than 0.8 were modified. Second evaluation, with 5 experts, resulted in a Content Validity Coefficient greater than 0.8. Semantic analysis carried out with 56 nursing professionals. In the end, the scale consisted of 23 questions and obtained a Cronbach's alpha of 0.764. Conclusions: The scale demonstrated good results in the content validation process, verbal comprehension and internal consistency.

Pop-Up Book Learning Media Used with the Problem Based Learning Model to Determine Characters in Fictional Stories

The low student learning outcomes in Indonesian are caused by a lack of media or a mismatch in the learning models used by teachers in learning. This research aims to develop Pop-Up Book learning media with a Problem-Based Learning (PBL) learning model to improve Indonesian language learning outcomes for fourth-grade elementary school students. This type of research is developed using the Borg & Gall development model. The research subjects were 25 students. The experts who are the subject of this research are media experts and material experts. The methods used to collect data are observation, interviews, questionnaires, documentation, and tests. This research instrument is in the form of a questionnaire and test questions. Data analysis techniques use data normality tests (Kolmogorov Smirnov), paired t-tests, and N-gain tests. The research results showed that after going through the product validation stage by material experts, a score of 90.9% was obtained. According to media experts obtained a score of 85.4% in the very feasible category. The effectiveness of the media was tested by calculating the results of the initial and final tests using the paired t-test. It was found that there were differences in the average learning outcomes before and after applying the Pop-Up Book learning media with the PBL model. It was concluded that the Pop-Up Book was effective and suitable for learning and improved students' ability to understand the material of finding fictional story characters in Indonesian subjects. The implication of this research is that the Pop-Up Book developed can be used in Indonesian language learning.

Multicriteria solar photovoltaic potential evaluation for high educational buildings. Case study of Polytechnic University of Valencia, Spain

Solar PV technologies have been expanding rapidly, and the installed power has increased, especially in the last decade. Their inclusion in university buildings arises as a key factor for sustainable transition in cities, since they have an important potential as case studies for urban experimentation positive effects on students and other stakeholders. This paper proposes a method to determine the availability for installing solar PV in universities' rooftops, considering simulation and cartography data, together with a final experimental validation stage. Unavailable areas for each rooftop are determined, including obstacles, the inner use of the rooftop and shadowed areas. Finally, the method verifies the technical suitability for all the proposed scenarios and applies an economic-environmental multicriteria evaluation to select the most suitable one. The methodology is validated in the Universitat Politècnica de València Vera-Campus. In total, 88913 m2 of the rooftops are suitable for solar PV incorporation, representing 48 % of the total surface. 52 % of the solar PV installable capacity takes place in surfaces which can incorporate more than 100 kW, 20.6 % between 50 and 100 kW and 27.4 % less than 50 kW. Finally, the multicriteria evaluation proved that the scenario with all the possible installations is the most suitable one.

Power hardware-in-loop emulation of a battery for charging systems and grid applications

Relevance. Batteries are playing an increasingly vital role in power systems due to their utilization in various applications including microgrids, electric vehicles, sustaining geographically isolated communities, and energization of automated devices. Since they are considered as the enabling technology for renewable energy integration, the absence of battery systems from islanded microgrids can result in decreased system reliability and compromised performance due to the intermittency of local sources. Nevertheless, the hazardousness associated with their charging mechanism has led to the urgent continuous development of charging technologies and battery management systems. Aim. To develop a safe testbed to examine the functionality of newly produced battery charging stations and battery managers without employing actual physical batteries to avoid the hazardous manipulation of batteries and increase flexibility during the design and validation stage. This is accomplished by modeling the electrochemical dynamics of the battery system and integrating the device-under-test to a DC converter, which reacts based on these modeled dynamics. Novelty. This work adapts one of the most successful Li-ion battery models available in the literature and utilizes it to interact with power electronic devices that exchange power signals. Unlike other work in this field, the design is based on power hardware-in-loop principles and has minimized power consumption characteristics due to its unique configuration. The constructed computer model can be easily reparametrized to describe the dynamics of various battery capacities. Methods. MATLAB-based simulations of the proposed testbed were conducted for high and low power capacity. A LabView-based program was interfaced with the testbed hardware using a NI-DAQ board to validate the proposed design practically. The testbed hardware components were entirely developed from scratch for experimentation purposes. Results. The proposed testbed successfully imitated the dynamics of the battery, while the practical results concurred the simulated ones.

Crop classification in Google Earth Engine: leveraging Sentinel-1, Sentinel-2, European CAP data, and object-based machine-learning approaches

ABSTRACT In contemporary agriculture and environmental management, the need for precise and accurate crop maps has never been more vital. Although object-based (OB) methods within Google Earth Engine (GEE) improve accuracy and output quality in contrast to pixel-based approaches, their application to crop classification remains relatively rare. Therefore, this study aimed to develop an OB classification methodology for crops located in central Italy’s Lake Trasimeno area. This methodology employed spectral bands, spectral indices (Normalized Difference Vegetation Index and Modified Radar Vegetation Index), and textural information (Gray-Level Co-occurrence Matrix) derived from Sentinel-2 L2A (S2) and Sentinel-1 GRD (S1) data within the GEE platform. Moreover, European Common Agricultural Policy (CAP) data associated with cadastral parcels were employed and served as ground information during the training and validation stages. The CAP crop classes were aggregated into three levels (Level 1–3 crop types, Level 2–5 crop types, and Level 3–7 crop types). Subsequently, optimized Random Forest (RF) classifiers were applied to map crops effectively. Feature selection analysis highlighted the importance of certain textural features. Additionally, findings demonstrated high overall accuracy results (89% for Level 1, 86% for Level 2, and 82% for Level 3). It was found that winter crops achieved the highest F-score at Level 1, while specific subclasses, such as winter cereals and warm-season cereals, excelled at Level 2. Overall, this study provides a promising approach for improved crop mapping and precision agriculture in the GEE environment.

Validation Studies a Questionnaire Developed to Measure Incubator Business Technology Performance using PLS-SEM Approach

This research aims to collect data nationally using a questionnaire based on statements related to the performance factors of the Technology Business Incubator in Indonesia. This research uses the Structural Equation Modeling (SEM) method to test the validity and reliability of adapted scales. There are five stages starting with an outer model test to test the validity and reliability of the questionnaire's feasibility. The population in this research are organizations that are affiliated with the Indonesian Business Incubator Association (AIBI) and Ministry of Research, Technology and Higher Education, including business incubators belonging to ministries, local governments, the private sector and universities, there are 182 Technology Business Incubators in Indonesia. Testing in this research looks at whether the questions in the questionnaire are valid or not by going through two stages of convergent validity and discriminant validity. The first stage is convergent validity that aim of finding out the correlation between indicators and their latent variables. The second stage is discriminant validity which aims to find out whether the latent variable has adequate discriminant value and this was done to find out whether the statement items in the questionnaire were reliable and consistent in measuring the same symptoms in respondents. This research looks at the results of convergent validity analysis to consider the results of factor loading indicators on relevant factors, the results of testing the validity of all factors with a value greater than 0.50, one of which is an AVE value of 0.550, indicating that the indicators in these variables have a strong contribution in measuring the desired construct, and the reliability test of all variables is reliable because it exceeds 0.70, one of which is the facility variable which has a value of 0.858.

Educational technology for patients with external fixator in the lower limbs

The objective of the work is to develop and validate an educational technology in the form of a booklet for guidance on the care of orthopedic patients using external fixators in the lower limbs. This is a study of methodological, bibliographical development, with a qualitative-quantitative approach. A questionnaire containing Likert scale variables was used as an instrument for evaluating educational technology, and the Content Validity Index for each validation stage was used for analysis, considering items equal to or greater than 0.80 to be valid. Validation was carried out by 18 expert judges, among them 8 (44.44%) were nurses, 3 (16.66%) doctors, 3 (16.66%) physiotherapists and 4 (22.22%) nursing technicians , while validation by the target audience occurred with 20 patients undergoing treatment with an external fixator in the lower limbs. It is considered validated by professionals with a global Content Validity Index of 1.0 and by patients, with a global Content Validity Index of 0.98. The educational material proved to be valid in terms of appearance and content, and suitable to contribute to health promotion and use in trauma-orthopedics care practice.

Theoretical Approaches to Process Validation in Pharmaceutical Manufacturing Process

Under the more general statutory CGMP provisions of section 501(a)(2)(B) of the Federal Food, Drug and Cosmetic Act, validation of manufacturing processes is deemed a legal part of current good manufacturing practice for active pharmaceutical ingredients (APIs). Validation of manufacturing processes is required by the Current Good Manufacturing Practice (CGMP) regulations for finished pharmaceuticals (21 CFR 211.100 and 211.110). A medication should be created that is suitable for its intended purpose, according to the fundamental tenet of quality assurance. Procedure Validation is the collection and estimation of data that proves a process can reliably produce high-quality goods, starting with process design and continuing through commercial production. Three stages of validation are suggested by the 2011 USFDA process validation guideline - Process design, Process qualification, Continued Process qualification. An introduction and broad review of process validation in the pharmaceutical manufacturing process, specifically in the tablet manufacturing process, are provided in this article. Process validation ensures that a process will consistently create a product that meets its predefined quality features and qualities. It is a crucial step in the design, prototyping, and manufacturing processes. Since quality is always a necessary precondition for any product, pharmaceuticals must be produced to the greatest standards of quality. Furthermore, end-product testing does not ensure the product's quality on its own; rather, quality assurance methods need to be applied to incorporate the product's quality throughout the whole process, rather than only testing it at the conclusion.

THE INFLUENCE OF TEACHER CREATIVITY IN MANAGING LEARNING ON MOTIVATION STUDENT LEARNING

This research is quantitative research with an ex post facto type of research, the research location is located in Cinnong Village, Sibulue District, namely SMA Negeri 12 Bone and the data sources are economics subject teachers and students in class XI IPS 1 and XI IPS 2. Data collection process, researchers used observation, documentation and questionnaires with follow-up of the data using descriptive analysis techniques with validity and reliability testing stages, as well as hypothesis testing with simple regression equations and t tests (partial). The results of research using questionnaires related to teacher creativity and student learning motivation, the validity test carried out on variable table 0.05. In variable Y, the sig value of each item is the highest value 0.042 < 0.05 from number 12 and the calculated r value > r table with the lowest value 0.271, r table 0.05, namely 0.260. The reliability test for In hypothesis testing, the constant number 154,448 means that if there is no variable .05 with the conclusion that H0 is rejected. In the t test the calculated t value is -4.166 with df = n-2 (10 – 2 = 8) with a value of 1.860 which has a significant effect.

Development and psychometric evaluation of uncertainty about disease and treatment scale in hemodialysis patients: a sequential-exploratory mixed-method study

Background and objectiveThe need for long-term treatment and frequent visits to treatment centers for hemodialysis can lead to psychological problems such as Uncertainty about Disease and Treatment (UC about D&T) in patients with chronic kidney failure. In order to understand uncertainty about disease and treatment and to plan for preventive measures and care interventions in various dimensions, there is a need for reliable and valid tools. The present study was conducted to design and psychometrically evaluate the Uncertainty about Disease and Treatment Scale (UC about D&TS) in patients undergoing hemodialysis.MethodsThis study is of a methodological type and conducted in two stages. The first stage included a deductive (literature review) and an inductive approach (face-to-face interviews). In the second stage, psychometric indices of the UC about D&TS, including face validity (qualitative-quantitative), content validity (qualitative-quantitative), construct validity (exploratory factor analysis), and reliability (using Cronbach's alpha and McDonald's omega) were examined.ResultsIn the literature review stage, 66 items were extracted, and in the qualitative stage, 48 items were extracted. After merging similar items, 29 items were entered into the psychometric process. No items were removed in the face and content validity stages. In the construct validity stage, five factors were extracted, including self-uncertainty, uncertain situation, uncertain future, uncertainty of treatment outcomes, and information uncertainty, which constituted a total of 82.16% of the total variance. In this stage, five items were removed from the study due to a corrected item-total correlation below 0.32, and four items were removed due to cross-loading. The α and Ω were calculated as 0.828 and 0.818, respectively. The measurement stability and standard error of measurement were estimated at 0.977 and 2.019, respectively.ConclusionThe results showed that the UC about D&TS is a valid and reliable measure for patients undergoing hemodialysis. This scale is specifically designed to measure UC about D&T in hemodialysis patients, and it is recommended that healthcare providers (Hcps) use this scale in follow-up visits.

Effects of climate change on streamflow in the Dez Basin of Iran using the IHACRES model based on the CMIP6 model

Abstract Understanding the changes in river flow is an important prerequisite for designing hydraulic structures as well as managing surface water resources in basins. By using the LARS-WG statistical downscaling model, the outputs of the general circulation model of the sixth report, including the ACCESS-ESM1 and BCC-CSM-MR models, under the SSP5.8.5 and SSP2.4.5 release scenarios. A more accurate spatial scale and daily precipitation and temperature time series were obtained for the studied area during the period of 2015–2043. Then the IHACRES rainfall-runoff model was calibrated in the study area. Based on the fit statistics in the calibration and validation stages, the overall performance of the developed model was evaluated as satisfactory. The calibrated hydrological model was driven by rainfall data and reduced air temperature to predict the effect of climate change on the output of the studied basin. The study showed that the studied basin has more rainfall (on average, 20.8% in the ACCESS-ESM1 model and 33.2% in the BCC-CSM2-MR model). The flow rate of the main river in the ACCESS-ESM1 model will decrease by 15% compared to the base period, and in the BCC-CSM2-MR model, it will increase by 16% compared to the base period.

The Development of Chemistry Electronic Module Based on Guided Discovery Learning on Teaching Chemical Bonding

The COVID-19 pandemic had many impacts on education. The teaching and learning process was done through distance learning and was carried out online through several online platforms and media. This study aimed to produce an independent learning media for students in the form of an online module based on the Guided Discovery Learning model in the class on chemical bonding of class X in senior high school. This study used the methods outlined in Research and Development by Borg and Gall (2003) and followed the descriptive quantitative method. The instrument used in this study was a questionnaire. The module was validated by three experts for content and language and also validated by three experts for media and graphics. The module was also trialled by 20 students in grade 10 science, 35 college students in the chemistry education program and 8 chemistry teachers. The ratings that were given by experts, students, and teachers from the validation and trial stages can be categorized as good and up to very good, so it can be concluded that the module is feasible to be used as a learning media on in the class on chemical bonding of class 10 in senior high school.
 Keywords: online module, guided discovery learning model, chemical bonding

The Development of Electronic Modules (E-Module) For Learning Chemical Safety and Security in High School Laboratories

The use of e-learning was very helpful in the distance learning process that was implemented during the COVID-19 pandemic. One of the applications of e-Learning media that can be used is the electronic module (e-Module). The purpose of this study is to develop electronic modules (e-Module) on chemical safety and security in high school laboratories. This study uses a descriptive quantitative method with research and development outlined by Borg and Gall. The instrument used in this study was a questionnaire. The e-Module was validated by experts in media and graphics, and experts in content and language. The e-Module was also tested by chemistry teachers, students in 10th grade, and college students in the chemistry education program. The result from the assessment given by experts, teachers, and students from the validation and trial stage can be interpreted as well up to very good. It can be concluded that the e-Module is feasible to be used as a learning media of Chemistry on Chemical Safety and Security in High-School Laboratories for high-school students.
 Keywords: electronic module, chemical safety, security

Influenza Diagnosis Deep Learning: Machine Learning Approach for Pharyngeal Image Infection

INTRODUCTION: Annual influenza epidemics and rare pandemics represent a significant global health risk. Since the upper respiratory tract is the primary target of influenza, a diagnosis of influenza illness might be made using deep learning applied to pictures of the pharynx. Using pharyngeal imaging data and clinical information, the researcher created a deep-learning model for influenza diagnosis. People who sought medical attention for flu-like symptoms were the subjects included. METHODOLOGY: The study created a diagnostic and predicting Artificial Intelligence (AI) method using deep learning techniques to forecast clinical data and pharyngeal pictures for PCR confirmation of influenza. The accuracy of the AI method as a diagnostic tool was measured during the validation process. The extra research evaluated the AI model's diagnosis accuracy to that of three human doctors and explained the methodology using high-impact heat maps. In the training stage, a cohort of 8,000 patients was recruited from 70 hospitals. Subsequently, a subset of 700 patients, including 300 individuals with PCR-confirmed influenza, was selected from 15 hospitals during the validation stage. RESULTS: The AI model exhibited an operating receiver curve with an area of 1.01, surpassing the performance of three doctors by achieving a sensitivity of 80% and a specificity of 80%. The significance of heat maps lies in their ability to provide valuable insights. In AI models, particular attention is often directed towards analyzing follicles on the posterior pharynx wall. Researchers introduced a novel artificial intelligence model that can assist medical professionals in swiftly diagnosing influenza based on pharyngeal images.

DEVELOPMENT OF INTERACTIVE LEARNING MEDIA BASED ON THE PROBLEM SOLVING METHOD USING PREZI FOR THE TOPIC OF ENVIRONMENTAL CHANGES

The process of learning Biology is still dominated by teachers as the sole source of information, using less interactive teaching media such as chalkboards and textbooks. The use of interactive media is considered appropriate for fostering students' problem-solving abilities, especially in the topic of Environmental Changes. The development of interactive media is crucial. This study aims to develop an interactive learning media using Prezi based on the problem-solving method for the topic of Environmental Changes. The research utilizes the R&D (Research and Development) model following the Borg and Gall research design, with the following stages: potential and problem stage, data collection stage, product design stage, design validation stage, design revision stage, and product revision stage

Clinical implementation of a commercial synthetic computed tomography solution for radiotherapy treatment of glioblastoma

Background and PurposeMagnetic resonance (MR)-only radiotherapy (RT) workflow eliminates uncertainties due to computed tomography (CT)-MR image registration, by using synthetic CT (sCT) images generated from MR. This study describes the clinical implementation process, from retrospective commissioning to prospective validation stage of a commercial artificial intelligence (AI)-based sCT product. Evaluation of the dosimetric performance of the sCT is presented, with emphasis on the impact of voxel size differences between image modalities. Materials and methodssCT performance was assessed in glioblastoma RT planning. Dose differences for 30 patients in both commissioning and validation cohorts were calculated at various dose-volume-histogram (DVH) points for target and organs-at-risk (OAR). A gamma analysis was conducted on regridded image plans. Quality assurance (QA) guidelines were established based on commissioning phase results. ResultsMean dose difference to target structures was found to be within ± 0.7 % regardless of image resolution and cohort. OARs’ mean dose differences were within ± 1.3 % for plans calculated on regridded images for both cohorts, while differences were higher for plans with original voxel size, reaching up to −4.2 % for chiasma D2% in the commissioning cohort. Gamma passing rates for the brain structure using the criteria 1 %/1mm, 2 %/2mm and 3 %/3mm were 93.6 %/99.8 %/100 % and 96.6 %/99.9 %/100 % for commissioning and validation cohorts, respectively. ConclusionsDosimetric outcomes in both commissioning and validation stages confirmed sCT’s equivalence to CT. The large patient cohort in this study aided in establishing a robust QA program for the MR-only workflow, now applied in glioblastoma RT at our center.

"Translation, cultural adaptation, and validation of perinatal grief scale in Urdu: Addressing a gap in the research of perinatal loss in Pakistan-Cross-sectional validation study".

Perinatal grief have a significant influence on maternal mental health, hence appropriate tools for assessment are necessary. In this study, we translated and validated the Perinatal Grief Scale in Urdu (PGS-Urdu) for use in Pakistan, therefore filling the gap in validated tools. Data was collected from 165 women using consecutive sampling. Initially, "forward/backward" translation was used. For validity, content validity index and confirmatory factor analysis (CFA) were used respectively, and "Cronbach's-Alpha" for reliability. In the validity stage, items 8, 11, 23, and 32 of the original scale were eliminated based on feedback from the target groups and the expert panel. For data-analysis, SPSS 26 and Amos 26 were used. In analyzing the "Confirmatory factor analysis", the "all-fitness indicators" validated the three-factor structure of 29-item main scale. Cronbach alpha value was 0.83 for the entire scale The CFA results showed that all fitness indicators, with the exception of four, had loadings greater than 0.20, supporting the main scale's three-factor structure. With a Cronbach's Alpha value of 0.83 for overall reliability, and varied from 0.81 to 0.87 for the PGS-U variables. the PGS-U exhibits an acceptable level of internal consistency. The PGS-U identifies women in perinatal grief for medical and social care. This research supports using the Urdu perinatal grief scale in obstetrics and bereavement counseling to reduce maternal mental health issues.

Prediction of daily river water temperatures using an optimized model based on NARX networks

Water temperature is an important physical indicator of rivers because it impacts many other physical and biogeochemical processes and controls the metabolism of aquatic species in rivers. Having a good knowledge of river thermal dynamics is of great importance. In this study, an advanced machine learning based model that is fast, accurate and easy to use, namely the nonlinear autoregressive network with exogenous inputs (NARX) neural network, was coupled with Bayesian Optimization (BO) algorithm for optimizing the number of NARX hidden nodes and lagged input/target values and the Bayesian Regularization (BR) backpropagation algorithm for the NARX training, to forecast daily river water temperatures (RWT). Long-term observed data from 18 rivers of the Vistula River Basin, one of the largest rivers in Europe, were used for model testing, and model performance was compared with the air2stream model. The results showed that the NARX-based model performs significantly better than the air2stream model in the calibration and validation stages, and can better capture the seasonal pattern and peak values of RWT. Input combinations impact the performance of the NARX-based model in RWT modeling, and air temperature and the day of the year (DOY) are the major inputs, while streamflow and rainfall play a minor role on modeling RWT at the Vistula River Basin. Considering that future times series of air temperatures are easily accessible from climate models and DOY is easy to be considered in the model, the NARX-based model can serve as a promising tool to investigate the impact of climate change on river thermal dynamics.

Brain-computer interface-based hand exoskeleton with bidirectional long short-term memory methods

It takes at least 3 months to restore hand and arm function to 70% of its original value. This condition certainly reduces the quality of life for stroke survivors. The effectiveness in restoring the motor function of stroke survivors can be improved through rehabilitation. Currently, rehabilitation methods for post-stroke patients focus on repetitive movements of the affected hand, but it is often stalled due to the lack of professional rehabilitation personnel. This research aims to design a brain-computer interface (BCI)-based exoskeleton hand motion control for rehabilitation devices. The Bidirectional long short-term memory (Bi-LSTM) method performs motion classification for the ESP32 microcontroller to control the movement of the DC motor on the exoskeleton hand in real-time. The statistical features, such as mean and standard deviation from the sliding windows process of electroencephalograph (EEG) signals, are used as the input for Bi-LSTM. The highest accuracy at the validation stage was obtained in the combination of mean and standard deviation features, with the highest accuracy of 91% at the offline testing stage and reaching an average of 90% in real-time (80%-100%). Overall, the control system design that has been made runs well to perform movements on the hand exoskeleton based on the classification of opening and grasping movements.