The entry of computer to many areas, such as medical field, led to develop new
technique that has led to the prosperity of these areas, and helped doctors to detect and
diagnose diseases accurately and credibility, where the experience of the docto
r in addition
to the accuracy of computer lead to access to the credibility of high patient and save
human lives.
A new approach for cardiac diseases detection and classification in ECG signals
images is proposed using Adaptive Neuro Fuzzy Inference System ANFIS.
The proposed approach is applied on database containing (147) ECG images,
each of them accompanied with its medical report. The medical reports were used to
validate the detection and classification.
The proposed method achieved a relatively high accuracy (97%) in detection and
classification processes.
The proposed approach is developed using MATLAB, and based on its libraries,
image processing, neural network and fuzzy logic.
The objective of this study was to model the Blood Flow into human arm’s
arteries in order to define velocity profile. All steps were based on
computational fluid dynamics .Simplified model for arm’s most important
arteries were made, while primar
y data such as length, diameter, and
velocity were collected for a healthy 40 years old, male , weight 64 Kg with
pulse rate 62 bpm ,and his arteries ranges from 1.6 to 2.6 mm by using
Doppler measurement.Bio dynami