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islamabad,
pakistan
Aktualisht është 8:55 m.d. këtu
U bashkua janar 4, 2016
2
Rekomandime
Imran A.
@imranahmadquresh
4,2
4,2
94%
94%
islamabad,
pakistan
95%
Punët e Plotësuara
98%
Brenda Buxhetit
100%
Në Kohë
17%
Shpeshtësia e Rimarrjes në Punë
Image Processing and Machine Learning Expert
Kontaktoni Imran A. për punën tuaj
Identifikohu për të diskutuar çdo detaj gjatë bisedës.
Portfolio
Portfolio
![An electromyography (EMG) is used to evaluate the physical health of muscles. Each muscle in a human body transmits signals which are produced when a muscle makes different movements. The EMG sensor receives signal containing 235 samples from forearm muscle of person in time span of 30 seconds. RMS (Root Mean Square) value of recorded samples is calculated. Experiments show that RMS value increases with increase in BMI (Body Mass Index), hence threshold level of fatigue also increases as BMI tells the muscle strength, as more the strength, lesser will be the fatigue. The system is trained with ranges of (0.25, 0.35], (0.35, 0.45], 0.45+ and (0.37, 0.48], (0.48, 0.65], 0.65+ for low, medium and high
fatigue using corresponding positions of fingers of hand for class1 (underweight or normal weight person) and class2 (overweight person) respectively. After training, BMI class is entered using keypad by entering either 1 for class1 or 2 for class2 and LCD shows fatigue level of a person.](https://cdn3.f-cdn.com/files/download/202040439/Fatigue%20Level%20Measurement%20Result.jpg?fit=crop&height=285&image-optimizer=force&format=webply&width=760)
Fatigue Level Measurement Using Arduino
Attendance Management System through Image Recognition
OMR Scanner for Counting Marks with Tick Cross in Matlab
Clustering fingerprint Images using K-means in Python
Brain Tumor Segmentation using morphological ops in Matlab
Blind Source Separation of fMRI Images using DL in Matlab
Fatigue Level Measurement Using Arduino
Attendance Management System through Image Recognition
OMR Scanner for Counting Marks with Tick Cross in Matlab
Clustering fingerprint Images using K-means in Python
Brain Tumor Segmentation using morphological ops in Matlab
Blind Source Separation of fMRI Images using DL in Matlab
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Manager R&D
jan 2014 - E tashme
End Technologies is a high technology multi-field engineering concern company, specialized in Research & Development, designing and manufacturing of a top class Science & Engineering equipment. The main purpose of the Company is to give economical solutions with Innovation and commercialization of new ideas. End Technologies currently engaged in fields relating to robotics, image processing, embedded system designing, FPGA`s and other security applications.
Arsimi
MS Electrical Engineering
(3 years)
Botime
Arduino Based Fatigue Level Measurement in Muscular Activity using RMS Technique
2020 International Conference on e-Health and Bioengineering (EHB)
Human fatigue reduces ability to work for some time as a result of abnormal or prolonged workloads. For this problem, an electromyography (EMG) is used to evaluate the physical health of muscles. Each muscle in a human body transmits signals which are produced when a muscle makes different movements. In this paper, forearm muscle is investigated using MyoWare EMG sensor (AT-04-001), an Arduino Uno, keypad and LCD.
Non negative matrix factorization, sparse coding & dictionary learning techniques on fMRI images
Recent Advances in Electrical Engineering (RAEE), 2017 International Symposium on IEEE.
Recent developments in Matrix factorization techniques have led to sparse representation of signals using learned dictionaries. In this research we have applied Alternating Least Square Non-Negative Matrix Factorization (ALSNMF) and Dictionary Learning (DL) technique for sparse representation to simulated and real Functional Magnetic Resonance Images (fMRI) to extract corresponding sources and time courses.
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