Course Brief Description Elective

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Slide 1

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      Courses Brief Description
      Level 4 Level 5 Level 6 Level 7 Level 8 Level 9 Elective

       

      Elective

      Code & No : BMTS 485

      Course : Reverse Engineering for Medical Equipment

      Credits : 2 lecture+1 lab

      Pre-requisite : None

      This course deals with reverse engineering which consist of design and development of existing biomedical instrument like ECG, heart pulse rate, oximeter, blood pressure measurement, pacemaker, defibrillators, etc. The student will replicate the instrument and test it.

       

      Code & No : BMTS 486

      Course : Molecular Sensors and Nano-devices

      Credits : 2 lecture+1 lab

      Pre-requisite : None

      The students will study the fundamental principles behind the operation of molecular sensors, nano-devices and biomedical microsystems elements; and major classes of molecular sensors, (or Micro-Electro-Mechanical Systems, MEMS). An application of molecular sensors, nano-devices and biomedical Microsystems is also covered.

       

      Code & No : BMTS592

      Course : Digital Equipment Design

      Credits : 2 lecture+1 lab

      Pre-requisite :

      This course covers both software and hardware aspects of an 8086/8088 microcomputer system, including the microprocessor structure, its operation and control, the organization and interface requirements for a microcomputer system, the structures and operations of standard hardware components associated with a microcomputer system, assembly language programming and structure of the machine codes. Lab experiments associated with this course involve assembly program development, digital circuit design, fabrication, and testing.

       

      Code & No : BMTS 593

      Course : Artificial Intelligence

      Credits : 2 lecture+1 lab

      Pre-requisite : None

      This course introduces representations, techniques, and architectures used to build applied systems and to account for intelligence from a computational point of view. This course also explores applications of rule chaining, heuristic search, logic, constraint propagation, constrained search, and other problem-solving paradigms. In addition, it covers applications of decision trees, neural nets, Genetic Algorithm, and other learning paradigms.

       

      Code & No : BMTS 594

      Course : Pattern Recognition

      Credits : 2 lecture+1 lab

      Pre-requisite : None

      This course focuses on an introduction about pattern recognition, feature extraction, Euclidian distance, parametric and nonparametric decision theoretic classification methods, statistical discrimination functions, medical applications of pattern recognition, detailed examples.

       

      Code & No : BMTS 595

      Course : Introduction to Telemedicine

      Credits : 2 lecture+1 lab

      Pre-requisite : None

      Introduction, motivation, and overview; clinical applications; data dimensionality, acquisition, and conversion; transmission methods (wired, wireless); networking; compression; measurement of quality and accuracy; reception and display considerations; data archiving and retrieval; store-and- forward vs. interactive; privacy and security issues; potential benefits of telemedicine, challenges in telemedicine, global telemedicine activities, Tele medicine results, commercial hardware and software; standards (including DICOM); economic issues; user-interface considerations; picture archiving and communication systems (PACS).