NUST Institutions Library Catalogue Search for 'au:"Muhammad Asim"'

Transport maintenance and management system

By Muhammad Asim.. Islamabad : NUST School of Electrical Engineering & Computer Science, 2003 . v, 48 p. : , Supervisor : Dr. Adaidullah Anwar 27 cm. +.

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Eyes on the road traffic police assistant

By Muhammad Asim Mahboob. Islamabad NUST School of Electrical Engineering and Computer Science 2012 . 51p. , Supervisors: Mr. Kamran Zaidi, Dr. Rehan Hafiz, Mr. Asad Ali Shah :27cm.+.

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Design of a 3 phase inverter for speed and torque control of induction motors

By Syed Hasan Masood Rizvi. Islamabad NUST-SEECS 2012 . 42p. , Supervisors: Dr. Awais Kamboh, Dr. Habib ur Rehman ;27cm.+.

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Configurable wireless sensor nodes

By Ahsan Rafique. Islamabad NUST-SEECS 2012 . 73p. , Supervisors: Dr. Awais Kamboh, Dr. Hamid Mukhtar ;27cm.+.

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Implementation of a mobile adhoc network routing protocol

By Ishaque, Capt Muhammad Asim BESE-03. MCS 2001 . 127 p.

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Hardware Implementation of RGB Display System /

By Asif, PC Haniya TE-41. Rawalpindi MCS 2008 . 52 p.;

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Geocasting In Heterogeneous Wireless Mobile Ab- HOC Networks

By Mubarik, Muhammad Asim (MSCS-13). Rawalpindi MCS,NUST 2010 . x,69,p;

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Teacher's Assistant (TA)

By Asim, Muhammad BESE-18. MCS, NUST Rawalpindi 2016 . iv, 86 p

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Qualitative and Quantitative Survey Of Combined Industrial and Municipal Effluents In Paharang Drain, Faisalabad

By Asim,Muhammad. Islamabad IESE(SCEE) NUST 2009 . 110 p. , Theses MS EE

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Islamic Jurisprudence Part I & II

By Muhammad Asim Alhaddad. Lahore Al-Faisal 2005 . 659p.

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Structural Design of Simple Rectangular Wing

By Muhammad Asim. Risalpur NUST Risalpur 1999 , AE 449

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To Integrate wind Tunnel Pyramidal balance System with Lab view 5.0 CAEG-54 (A)

By Muhammad Asim Qazi. Risalpur NUST 2001 . 161p , BE-Project Report

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Fabrication ahd Testing of an Infinite wing in open Circuit subsonic wind Tunnel, in Stationary and Osscilating modes CAEG-56 (A)

By Muhammad Asim. Risalpur NUST 2002 . 89p , BE Project Report

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Daira

By Muhammad Asim Butt. Lahore Sang-e-Meel Publications 2014 . 254p. , General Books

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Design and Development of Electronic Identification System for PAF Vehicles 66 "B" EC

By Umer Javaid; Prof Muhammad Asim, Advisor. Rawalpindi NUST 2009 . 58p , BE Project Report

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Afsaney

By Muhammad Asim Butt. Lahore Takhleekat 2014 . hb

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Transport maintenance and management system

By Muhammad Asim.. Islamabad : NUST School of Electrical Engineering & Computer Science, 2003 . v, 48 p. : , Supervisor : Dr. Adaidullah Anwar 27 cm. +.

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Pakistani adab ke mamaar /

By Butt, Muhammad Asim. 2008 -; Islamic Research Institute press, 2008 . 148 p. ;

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Classification of Functional motions of Hand for Upper Limb Prosthesis With Surface Electromyography (EMG) /

By Waris, Muhammad Asim. Islamabad : SMME - NUST 2013 . 86 p. : ill, ; , Hardcover. 30cm..

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Effects of Privatization on firms performance case of telecom sector in Pakistan

By Aslam Asim Muhammad,. Islamabad: NBS- NUST, 2013 . 37 p.: ill.; , hardcover 30cm..

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Business Group Affiliation & Dividend Policy /

By Khan, Muhammad Asim. Islamabad: NBS - NUST, 2013 . 23 p. : ill. ; 30cm..

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Finite Element Analysis of Knee Implant for Orthopedic Applications /

By Zahir, Mian Muhammad Asim. Islamabad: SMME - NUST, 2015 . 32 p.: ill.; 30cm..

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Efficiency Maximization of Photovoltaic (PV) Energy System under Partial Shading /

By Javaid, Muhammad Asim. Islamabad: SEECS - NUST, 2015 . 44 p.: ill.; 30cm..

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Deep Excavation Support System in Urban Environment Syn#31

By Muhammad Asim .

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Development of Zirconia Base Thermal Barrier coating On Inconel 718 Substrate via Atmosphere Plasma Spraying Techinique

By Muhammad Asim. Islamabad scme 2008 . 118p

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Fikah ul sunnah

By Muhammad Asim Ul Hadad. LAHORE ADARA FARUGH-E-URDU 1999

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PR-SOF-1531-DESIGN OF A FLYING WING UAV USING A BACKWARD FACING STEP WING PROFILE

By NS ALI ABDULLAH PC MUHAMMAD ASIM SHEHZAD NS SYED MUHAMMAD ABDULLAH . ISLAMABAD NUST COLLEGE OF EME 2016

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PR-SOF-1401-JARVIS REMOTE ACCESS SOLUTION FOR PC AND ANDROID USING HTTP PROTOCOL

By MUHAMMAD AJMAL, MUHAMMAD ALI,MUHAMMAD ASIM, MUHAMMAD SAMI AHMAD. ISLAMABAD NUST COLLEGE OF EME

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PR-SOF-1962-Autonomous 5- Axis Robotic Arm

By Syed Saad Waqar. Suleman Qamar. Hassan Tariq. Muhammad Asim Riaz. ISLAMABAD NUST COLLEGEOF EME 2020

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TH-SOF-2003-A Model-Driven Framework for Embedded Systems Design Verification through Portable Test & Stimulus Standard (PSS)

By Muhammad Asim Minhas. ISLAMABAD: NUST COLLEGE OF EME, 2022

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Simulation and analysis of a simplified solar energy forecast model based on weather parameters /

By Muhammad Asim Munir (00000204246). USPCAS-E, NUST, Islamabad : 2020 . 41 p.

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Short-term wind resource forecasting for the wind farm, under the influence of extreme seasonal variations and inter-farms wake /

By Raja Muhammad Asim Feroz (00000206014). USPCAS-E, NUST, Islamabad : 2020 . 70 p.

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Detecting Musculoskeletal Co-contraction for Ankle Rehabilitation through Variational Mode Decomposition in sEMG /

By Yasmeen, Sania . . 56p. 30cm.

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Comparative Analysis of UNET-Based and Transformer-Based Medical Image Segmentation Models on Lungs X-rays /

By Ghafoor, Muhammad Fazeel . . 66p. 30cm.

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Comparison And Correlation of Hamstring Reinforcing Exercise With Sprint In terms of Muscles Activity And Force Production /

By Habib, Adnan . . 44p. 30cm.

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Optimizing Feature Reduction and Selection Techniques for Surface Electromyography /

By Khan, Affaf . . 65p. 30cm.

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EMG Feature Reduction Technique For Optimal Accuracies /

By Abbas, Usman . . 94p. 30cm.

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Mobile Tablet Base Therapies for Cognitive Rehabilitation of Stroke Patients /

By Shad, Amna. . 66p. ; 30cm..

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Enhancing Gait Symmetry: The Impact of Prolonged Sitting and the Efficacy of Flexibility Exercises /

By Khan, Habib Ullah. . 62p. , Due to advancement in technology, we have seen a shift in the modern work environment. A notable surge has been seen in the percentage of people with jobs requiring prolonged sitting. There is a strong link between sedentary behavior and health risks down the road. Gait of a person is also linked to sedentary behavior which is believed to be significantly affected by prolonged inactivity. Gait asymmetry can be a very good indicator of overall physical health and that is why it used extensively to assess the physical health of subjects. Due to prolonged sitting, tightening of certain muscles, reduction in core strength and reduction in joint flexibility can lead to various Gait abnormalities. Our study is designed to compare the Gait asymmetry of physically active individuals with those of inactive individuals. We took into account various gait related features to find out the gait asymmetry between the right and left limb. We then also assessed the impact of exercise on gait symmetry and introduce flexibility training to the Sedentary group. Sedentary group performed Flexibility Training for 4 weeks every day. The exercises were performed thrice every day for 30 minutes. Results were substantial in supporting the link between sedentary behavior and increased gait asymmetry. Results also showed improvements in gait symmetry using flexibility training exercises. 30cm.

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Comparison of a Human Portable Blood Glucose Meter and Automated Chemistry Analyzer for Measurement of Blood Glucose Concentrations in Human Diabetic Patients /

By Asad-Ur-Rehman. . 46p. , Diabetes is the most prevalent chronic metabolic disorder in Pakistan which is characterized by an increased Blood Glucose level. An accurate diagnosis of diabetes is very essential for its early detection and treatment. Almost 90\% of the cases are of Type II Diabetes and the patients are required to continuously monitor their Blood Glucose level to maintain a near-normal range of Blood sugar. A practical way to monitor sugar levels is using a portable Glucometer at home which is faster and more convenient for diabetes patients. The purpose of this study is to compare Blood Glucose levels measured using Oxidase Method and a Portable Glucometer with reference Hexokinase Method in Type II Diabetes patients to determine if Glucometers can be used as a home-based selfmonitoring device. A cross-sectional study was conducted with a total of 150 Type II Diabetes patients. Blood samples were collected from the capillary of fingers for a portable Glucometer and from veins for Hexokinase and Oxidase Plasma methods after overnight fasting of 8 hours. Independent t-test and Pearson Correlation were used to check the significance of our results. There was no statistically significant difference in Blood Glucose readings obtained from Oxidase Method (128.31 + 61.4, p = 0.947) and Glucometer (122.53 + 59.6, p = 0.370) with Reference Hexokinase Method (128.78 + 61.2). A statistically significant positive correlation was observed in both methods with reference Hexokinase Method. Glucometer readings positively correlate with Hexokinase, showing that Glucometer can be used as a home-based self-monitoring Blood Glucose Device. 30cm.

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Effect of Process Parameters on the Mechanical Properties of UV Resin in Stereo Lithography /

By Asim, Muhammad . . 72p. , Stereo lithography, which is mostly use for rapid tooling applications, is the earliest technique developed for rapid prototyping. It converts CAD models directly into real parts, which offers the considerable benefit of shorter lead times and less waste. Layer thickness, build orientation, exposure time, and other process variables all affect the strength of part produced via masked stereo lithography. This work aims to identify, investigate and maximize the influence of process variable on the part produce by Anycubic Dental non castable resin in Anycubic Photon S LCD SL printer. To do this, L9 orthogonal array designed using the Taguchi method has been developed, which lowers the number of experimental runs compared to other approaches. In addition, an empirical regression model linking part strength and process variables such layer thickness, build orientation, and exposure time was created. Prior to physically fabricating the item, this process model may forecast the amount of strength that can be attained for the specified set of process parameters. Additionally, the model demonstrates how strength is dependent on the specified process parameters, which is particularly beneficial for technical individuals like designers, engineers, and RP machine users. 30cm.

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Effect of load and size on wear depth per cycle in Total Knee Replacement (TKR) /

By Ahmed, Hajira. . 97p. , The sole objective of this research thesis is to evaluate the effect of size and load on the wear per cycle in prosthetic knee joints. Prosthetic knee joints are abundantly used in the medical field to cater the deteriorating natural knees and help maintain a better standard of living. The prosthetic knees come in seven universal sizes and each one acts differently under same load conditions. Initially, seven different models developed on SolidWorks constituting the femoral and disk part. The parts were mated so that the femoral component can slide on the disk. Then, the wear analysis was carried out using Abaqus. Firstly, materials were assigned to the two components i.e., Cobalt Chromium Molybdenum Alloy (CoCrMo) to the femoral component and Ultra High Molecular Weight Polyethylene Disk (UHMWPE) to the polyethylene disk. Meshing was done and boundary conditions were defined to execute the whole analysis. The use of this method resulted in the calculation of contact stresses on the area of contact between the two parts. The contact stresses were calculated at 700N, 950N and 1200N for each size. The contact stresses were maximum at the edges due to small area concentration and minimum at the center attributing to the large area. Moreover, the maximum contact stress was utilized to evaluate the wear depth by utilizing Archard’s wear law. The wear depth was calculated for one gait cycle. The wear depths (𝑊d) for size 1 against loads of 700 N, 950 N and 1200 N were 26.131 nm/cycle, 31.706 nm/cycle and 37.253 nm/cycle respectively. The 𝑊d for size 5 against loads of 700 N, 950 N and 1200 N were 140.27 nm/cycle, 156.14 nm/cycle and 171.45 nm/cycle respectively. The 𝑊d for size 6 against loads of 700 N, 950 N and 1200 N were 23.060 nm/cycle, 28.193 nm/cycle and 33.307 nm/cycle respectively. Similarly, the wear depth was calculated for the remaining sizes. The results indicate that the maximum wear occurs in size 5 and the minimum wear occurs in size 6. The incorporation of Cobalt Chromium Molybdenum Alloy (CoCrMo) and Ultra High Molecular Weight Polyethylene Disk (UHMWPE) has greatly reduced the wear debris per cycle and allowed the knee joint to work properly which are quite evident from the results. 30cm.

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Design of Passive Controlled Iot Based Smart Cpm for Lower Limb /

By Shahnaz, Iram . . 42p. , Muscle strength and range of motion in the knee joint are impacted following total knee replacement and anterior cruciate ligament surgery. As a result, the goal of this research is to design a rehabilitative device to improve knee joint muscle strength and range of motion. The global population of people with mobility disorders is growing, which increases the demand for rehabilitation and physiotherapy devices. Automated assistive tools and devices have shown to be extremely effective and necessary in the treatment of physical injuries and impairments. Physiotherapists might use android technology to remotely set the degrees of flexion/extension, the pace of movement, and duration. The Android application will also save the patient's exercise history and can convey the patient's input about his condition's progress to the physiotherapist. The normal active knee range of motion is as follows: Knee Flexion ROM: 135 deg (completely bent), Knee Extension ROM: 0 degrees (totally straight). External Knee Rotation ROM: 30-40 deg, Internal Knee Rotation ROM: 10deg Normal passive knee ROM is as follows: Passive Knee Flexion ROM: up to 150deg, depending on leg size - the limit is the calf pushing towards the back of the thigh, Passive knee extension range of motion (ROM): up to 10deg hyperextension is deemed typical. 30cm.

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Analysis of post-COVID comorbidities in Pakistani population /

By Ansari, Sara. . 61p. , Introduction: Long-COVID, is the collective name given to denote persistence of symptoms for weeks or months in those who have recovered from SARS-COV-2 infection. If the relapsing symptoms are left undetected, can lead to chronic conditions. Still some work needs to be done to determine the correlation of the previous illnesses with the severity of post-COVID symptoms. Method: A questionnaire survey was spread amongst Pakistani population. About 83 COVID-19 survivors were included in the study, who were asked about any occurrence of symptoms at recovery, the experience and duration of the post-viral symptoms. Results: Out of 83 participants, 59(71.7%) experienced relapsing symptoms at 3 weeks from the onset of the viral infection, with 34(44.6%) having to face those symptoms for 3-4 weeks (postacute COVID). Females were significantly more likely to experience fatigue (p=0.014) and severity (p=0.032). The presence of symptoms was not associated with any therapy or activity. The presence of mild symptoms is common after the COVID-19 infection with those already suffering from anxiety, allergies, hypertension, and diabetes. Conclusion: This study highlights the importance of assessing those recovering from mild COVID-19 with acute-fatigue. Moreover, further longitudinal research in this area can help understand the management of chronic situations. 30cm.

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Emg-Based Force Estimation Using Deep Learning Models /

By Nayab, Maham . . 94p. , The estimation of force through electromyography (EMG) assumes paramount importance in diverse domains, including neurorehabilitation, myoelectric control, and neurofeedback systems. The intricate relationship between muscle contraction and force, characterized by linear associations in small muscles with narrow motor units and nonlinear relationships in larger muscles with wider motor units, underscores the complexity of this physiological interplay. Against the backdrop of a global demand for advanced technologies to address limb loss limitations, with an estimated 100 million individuals worldwide in need of prosthetics, there arises an urgent need for sophisticated solutions. Meeting the diverse needs of prosthetic users emphasizes the crucial role of EMG-based force prediction, striving to provide adaptive and personalized solutions for an inclusive and effective approach to limb rehabilitation. This comprehensive study explores the dynamic interplay between surface electromyography (sEMG) and intramuscular electromyography (iEMG) signals and force estimation. Leveraging a diverse set of machine learning and deep learning models, the research aims to predict forces in both healthy individuals and those with trans-radial amputations. Across sEMG and iEMG modalities, deep learning models, including Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN), and the hybrid LSTM-TCN, consistently exhibit remarkable efficacy. These models, boasting R² values surpassing 0.90 in force prediction, offer promising advancements in refining force estimation through electromyography. Notably, the TCN emerges as an exemplary performer, yielding R² values of 0.98 for able-bodied individuals and 0.87 for amputees in sEMG. Simultaneously, the hybrid TCN-LSTM model maintains strong performance with R² values of 0.98 for able-bodied individuals and 0.85 for amputees in sEMG. The LSTM model also upholds notable performance, showcasing R² values of 0.99 for able-bodied individuals and 0.80 for amputees in sEMG. Beyond unraveling the intricacies of EMG-based force estimation, this study sheds light on the unique challenges posed by amputations, contributing substantively to the ongoing quest for enhanced precision and effectiveness in rehabilitation interventions. 30cm.

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Classification of Activities of Daily Living (ADLs) Based Upper Limb Movements Using Machine Learning & Neural Network Classifiers /

By Anwer, Saba . . 68p. , Real time natural control of assistive, rehabilitation and prosthetic devices has gained significant importance over the last few decades for the people suffering from motor disabilities due to stroke, any spinal cord injury or amputation. Although surface electromyography (s-EMG) has been used as a viable controlling interface for several robotic devices specifically designed for post stroke therapeutic services. But these conventional controlling strategies are not feasible to design the rehabilitation or HMI systems based on simultaneous movements of multiple degrees of freedom (DOF). This paper presents a novel control strategy for HMIs which is based on the coupled use of EMG and inertial sensors. EMG and kinematic data of healthy and stroke subjects for commonly used daily life activities has been recorded. Multiple machine learning models including LDA, QDA, LSVM, QSVM, Fine KNN, Ensembled discriminant, and ensembled KNN have been applied. Besides this a tri-layered neural network classifier has also been implemented. A comparative analysis has been performed for the classification outcomes of all the applied models for EMG, IMU & EMG+IMU data. Overall, the KNN model performed well for all types of datasets with an average accuracy of 98.5% but results clearly demonstrated that average classification accuracies for all the applied models have significantly improved for EMG+IMU data which indicates that sensor fusion based control strategy for prosthesis can achieve higher performance than conventional control systems for each task. This study is an effort to provide a new EMG+IMU based technique for fast, efficient, and reliable control of robotic, rehabilitation and assistive devices for multiple movements with varying DOF. 30cm.

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Post-Discharge symptoms and analysis for COVID-19 patients /

By Shahjehan, Ayesha . . 65p. , Coronavirus was initially recognized as human COVID by researchers in 1965. Different strains of coronavirus appeared in the following years MERS, SARS-1. Thousands of cases were reported in individuals that to led many casualties, in 2019. New strains of coronavirus emerged, known as covid-19that started to spread from Wuhan, China. It was labeled a worldwide epidemic by the World Health Organization (WHO) in March 2020, the first since 2009. Patients with covid-19 experienced gentle to extreme indications like fever, cough, weariness, shortness of breath, migraine, loose bowels, nausea, and vomiting. As SARS cov-2 is a novel infection, initially the infected patients were treated in a single room along with the utilization of antiviral medication, including oseltamivir, ribavirin, and ganciclovir, lopinavir, and ritonavir to decrease the viral burden. Indications during the contamination may not resolve unexpectedly grumble about persistent side effects, even a long time after the disease. The research is based on observing the symptoms of COVID and postCOVID in patients who perform PCR tests at a hospital. Sample of 26 males and 34 females. Services were taken and their symptoms were noted during and after the quarantine. During the assessment of the covid-19 pandemic, it was seen that overall unexpected issues have gotten even after the onset of intensive covid-19. The prolonged aftereffect stays unexplained. The point of this examination is to represent the persistent symptoms in patients who were released from the health center and to explore the related element of danger. The impact of the study is fundamental in investigating the components and potential persistent post-COVID disorder. It presents a system of procedures for prognosis and handling of patients with suspected or affirmed persevering post-COVID conditions. 30cm.

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Classification of Reach and Grasp Motions from EEG Signals using Deep Convolutional Neural Networks (CNN) /

By Sultan, Hajrah . . 73p. , Classification of neural correlates of hand motions from EEG signals recently gained attention of researchers for the development of BCI systems for persons suffered from stroke, spinal cord injury who are not able to do voluntary movements or person with amputated arm or legs. Commonly LDA, SVM and K-NN models are used for the classification of hand motions, CNN and hybrid models are also used but most methods include the complex methods or preprocessing of EEG data and extraction of time or frequency domain features from the preprocessed signals which is a time consuming and lack flexibility because the EEG signals vary from human to human. In this thesis a Deep CNN model for end-to-end0learning of neural corelates for reach and grasp actions is introduced, aiming to increase rate of recognition & balanced classification0accuracy throughout all the subjects. A new model of CNN for movement classification is proposed that can also be used on the edge devices because of its smaller size for the development of BCI systems. In the proposed model separable convolutional blocks are used which reduce the number of parameters and hence the size of model also decreases. The dataset that is used for the testing of model is BNCI Horizon 2020 Reach and Grasp action dataset that is publicly available dataset. The dataset is also tested on 3 machine learning models LDA, SVM and K-NN are used, in which input is given in the form of time domain feature set the average accuracies achieved on these models are 60.77 (±3.80 STD), 66.73 (±2.86 STD), and 79.81 (±3.11 STD) respectively on the unseen dataset. Then the dataset is tasted on proposed Deep learning model along with DeepConvNet and EffNet models. The proposed model achieves the average classification accuracy of 92.44 (±4.13 STD), 92.9 (±4.23 STD) and 81.7(±5.68 STD). The model proposed achieves the same accuracy as DeepConvNet, but the size of proposed model is far smaller than the DeepConvNet model. Results shows that the proposed model shows the improved results with less variation of results within the subjects. Which will become helpful in the creation of real time BCI systems. 30cm.

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Human Placental-Derived Extracellular Matrix Sheets as Scaffolds for Cell Growth in Cornea Transplantation: A Promising Approach in Regenerative medicine /

By Khan, Unaiza Ali . . 121p. , Eye is a sensory organ designed for human vision. Its intricate components work together to make the process of sight possible. The cornea is a critical part of the eye responsible for clear vision, and corneal diseases or injuries can lead to visual impairment or blindness. However, the limited availability of suitable donor tissue poses a significant challenge. There is a significant influence on the quality of life when the visual acuity is reduced. In terms of the overall prevalence of blindness and visual impairment Pakistan ranks third position, following the India and Bangladesh across all age groups, totaling 21.78 million. Placenta-derived extracellular matrix (ECM) sheets have become an effective therapeutic approach due to their rich composition of bioactive molecules, growth factors, and supportive microenvironment for tissue regeneration. The unique composition of placental-derived ECM sheets can provide a favorable microenvironment for the growth of corneal cell and promote the regeneration of corneal tissue. In this study amniotic membrane sheets, have been prepared by decellularizing placental tissue and different characterization techniques have been used for a thorough examination of the human amniotic membrane. Scanning Electron Microscopy (SEM) reveals intricate surface features, while Hematoxylin and Eosin (H&E) staining provides insights into tissue architecture. Fourier Transform Infrared Spectroscopy (FTIR) offers a detailed examination of biochemical composition. Microbial activity testing provides valuable information of the membrane's antimicrobial properties. A p-value < 0.05 in the ANOVA analysis indicated a significant difference in antimicrobial activity among the three bacterial strains. The characterization approaches utilized in this study contribute to a betterxx knowledge of the biological characteristics of the human amniotic membrane, paving the path for advances in regenerative medicine and tissue engineering. In this study a human placental-derived extracellular matrix (ECM) sheets have been used to investigate the integration potential of the ECM sheets with host corneal tissue. The positive outcome was associated with a noticeable reduction in size of corneal defect due to the application of amniotic membrane transplant. The use of AM proved to be essential in reducing notable subjective symptoms like pain, as well as clinical signs such as redness and the size of corneal ulcers. 30cm.

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Decoding of Hand Motion Using State of Art Time Domain, Frequency Domain And Feature Extraction /

By Munawar, Sulaiman . . 69p. , Exoskeletons that are activated by the muscles and brain have been suggested to train the motor skills of stroke victims. Training can incorporate task variety since an exoskeleton allows for the execution of various movement types.Differentiating between movement types at the same time from brain activity is challenging, but it might be accessible from residual muscular activity that many patients retain regain.This study examines whether forearm EMG from five stroke patients can be used to decode seven distinct motion classes of the hand and forearm. This study evaluates classifiers like Support vector machine (SVM), Lineardiscriminant analysis (LDA) and K nearest neighbor (KNN). It investigated the relation of motor impairment with classification accuracy by the classifiers. During the following motion classes: Supination, Pronation, Hand Close, Hand Open, Wrist Extension, Wrist Flexion, and Pich, five surface EMG channels were recorded.Every motion was performed by patients three times repetition over the course of eight weeks.Support vector machines, k nearest neighbor, and linear discriminant analysis were used to classify decoding of hand moments for stroke patients. On average,73.69 ± 6.39%SVM,71.6 ± 5.09% KNNand 50±4.56 LDA of the movements were correctly classified.Seven motion classes were demonstrated to be decoded from residual EMG, and SVM proved to be the most effective classification method when compared to the other three classifiers for decoding of hand motion for stroke patients.The results of this study may have implications for the development of exoskeletons, suits, or gadgets, that are powered by EMG signals. These devices might be utilized in the comfort of the patient's home to assist stroke sufferers with their training activities. Therefore, the findings of this study may assist in improving the effectiveness and accessibility of these useful tools for stroke survivors. 30cm.

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