Grow as a biomedical engineer and incorporate into your professional practice the latest advances in this booming area, delving into issues such as bionanomaterials”

Biomedical Engineering is the next big leap in the healthcare world. This discipline takes advantage of a series of technological and computer tools that have emerged in recent years and applies them to the medical field to achieve more precise diagnoses and treatments. Therefore, it has numerous applications such as micro-implants, nuclear medicine, regenerative tissue growth, artificial vision and robotics. For this reason, it is one of the fields with the greatest present and future, and which requires more qualified professionals.

This Professional master’s degree in Biomedical Engineering is, therefore, presented as the answer to this situation, since it provides engineers and computer scientists with the latest knowledge in this area. Accordingly, the program will cover aspects such as Tissue Engineering, Nanomedicine, types of biomaterials and their applications, biomedical signals, Digital Radiology or relational databases and their applications in digital health, among many others.

All with the support of a high-level teaching staff, made up of experts in the different areas of Biomedical Engineering, and through a 100% online teaching system that allows students to balance their professional life with their studies.

urthermore, students will benefit from numerous multimedia resources such as practical exercises, interactive summaries, explanatory videos or master classes. On the other hand, the itinerary counts with the participation of a renowned International Guest Director, who will give 10 exhaustive Masterclasses to delve into the latest trends in the field of Biomedical Engineering.

A prestigious International Guest Director will offer 10 rigorous Masterclasses on the latest advances in the field of Biomedical Engineering”

This Professional master’s degree in Biomedical Engineering contains the most complete and up-to-date program on the market. The most important features include: 

• The development of case studies presented by experts in Biomedical Engineering
• The graphic, schematic and eminently practical contents with which it is conceived gather scientific and practical information on those disciplines that are indispensable for professional practice
• Practical exercises where self-assessment can be used to improve learning.
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

This program will allow you to get in touch with the most recent scientific and informatics developments in this area, especially in fields such as Biomechanics or biodevices and biosensors"

The program’s teaching staff includes professionals from the field who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the course. For this purpose, students will be assisted by an innovative interactive video system created by renowned experts in the field of educational coaching with extensive experience.

Delve into biomedical signals and their applications, and position yourself as an engineer in high demand by numerous health services"

You will be able to balance your professional career with your studies thanks to TECH's innovative 100% online teaching methodology, since it can be adapted to meet your personal circumstances"

The contents of this Professional master’s degree in Biomedical Engineering have been organized in 10 specialized modules, which will allow students to delve into issues such as gene therapy, different biomaterials, biomaterials applied to Neuroengineering, the capture, analysis and measurement of biomedical signals, fluid mechanics, computation in Medical Biology or the use of the R programming language for data analysis, among many others.

The most up-to-date contents in biomedical engineering are here. Enter the future with this specialized program"

Module 1. Tissue Engineering

1.1. Histology

1.1.1. Cellular Organization in Higher Structures: Tissues and Organs
1.1.2. Cell Cycle: Tissue Regeneration
1.1.3. Regulation: Interaction with the Extracellular Matrix
1.1.4. Importance of Histology in Tissue Engineering

1.2. Tissue Engineering

1.2.1. Tissue Engineering
1.2.2. Scaffolding

1.2.2.1. Properties
1.2.2.2. The Ideal Scaffolding

1.2.3. Biomaterials for Tissue Engineering
1.2.4. Bioactive Materials
1.2.5. Cells

1.3. Stem Cells

1.3.1. Stem Cells

1.3.1.1. Potentiality
1.3.1.2. Tests to Evaluate Potentiality

1.3.2. Regulation: Niche
1.3.3. Types of Stem Cells

1.3.3.1. Embryonic
1.3.3.2. IPS
1.3.3.3. Adult Stem Cells

1.4. Nanoparticles

1.4.1. Nanomedicine: Nanoparticles
1.4.2. Types of Nanoparticles
1.4.3. Methods of Obtaining
1.4.4. Bionanomaterials in Tissue Engineering

1.5. Genetic Therapy

1.5.1. Genetic Therapy
1.5.2. Uses: Gene Supplementation, Cell Replacement, Cellular Reprogramming
1.5.3. Vectors for the Introduction of Genetic Material

1.5.3.1. Viral Vectors

1.6. Biomedical Applications of Tissue Engineering Products Regeneration, Grafts and Replacements

1.6.1. Cell Sheet Engineering
1.6.2. Cartilage Regeneration: Joint Repair
1.6.3. Corneal Regeneration
1.6.4. Skin Grafting for Major Burn Injuries
1.6.5. Oncology
1.6.6. Bone Replacement

1.7. Biomedical Applications of Tissue Engineering Products. Circulatory, Respiratory and Reproductive System

1.7.1. Cardiac Tissue Engineering
1.7.2. Hepatic Tissue Engineering
1.7.3. Lung Tissue Engineering
1.7.4. Reproductive Organs and Tissue Engineering

1.8. Quality Control and Biosecurity

1.8.1. NCF Applied to Advanced Therapy Drugs
1.8.2. Quality Control
1.8.3. Aseptic Processing: Viral and Microbiological Safety
1.8.4. Cell Production Unit: Characteristics and Design

1.9. Legislation and Regulation

1.9.1. Current Legislation
1.9.2. Authorization
1.9.3. Regulation of Advanced Therapies

1.10. Future Perspectives

1.10.1. Current Status of Tissue Engineering
1.10.2. Clinical Needs
1.10.3. Main Challenges at Present
1.10.4. Focus and Future Challenges

Module 2. Biomaterials in Biomedical Engineering

2.1. Biomaterials

2.1.1. Biomaterials
2.1.2. Types of Biomaterials and Application
2.1.3. Biomaterial Selection

2.2. Metallic Biomaterials

2.2.1. Types of Metallic Biomaterials
2.2.2. Properties and Current Challenges
2.2.3. Applications

2.3. Ceramic Biomaterials

2.3.1. Types of Ceramic Biomaterials
2.3.2. Properties and Current Challenges
2.3.3. Applications

2.4. Natural Polymeric Biomaterials

2.4.1. Interaction of Cells With Their Environment
2.4.2. Types of Biomaterials of Biological Origin
2.4.3. Applications

2.5. Synthetic Polymeric Biomaterials: In Vivo Behavior

2.5.1. Biological Response to Foreign Bodies (FBR)
2.5.2. In Vivo Behavior of Biomaterials
2.5.3. Biodegradation of Polymers Hydrolysis

2.5.3.1. Biodegradation Mechanisms
2.5.3.2. Degradation by Diffusion and Erosion
2.5.3.3. Hydrolysis Rate

2.5.4.  Specific Applications

2.6. Synthetic Polymeric Biomaterials: Hydrogels

2.6.1. Hydrogels
2.6.2. Classification of Hydrogels
2.6.3. Hydrogel Properties
2.6.4. Hydrogel Synthesis

2.6.4.1. Physical Cross-Linking
2.6.4.2. Enzymatic Cross-Linking
2.6.4.3. Physical Cross-Linking

2.6.5. Structure and Swelling of Hydrogels
2.6.6. Specific Applications

2.7. Advanced Biomaterials: Intelligent Materials

2.7.1. Shape Memory Materials
2.7.2. Intelligent Hydrogels

2.7.2.1. Thermo-Responsive Hydrogels
2.7.2.2. PH Sensitive Hydrogels
2.7.2.3. Electrically Actuated Hydrogels

2.7.3. Electroactive Materials

2.8. Advanced Biomaterials: Nanomaterials

2.8.1. Properties
2.8.2. Biomedical Applications

2.8.2.1. Biomedical Images
2.8.2.2. Coatings
2.8.2.3. Focused Ligands
2.8.2.4. Stimulus-Sensitive Connections
2.8.2.5. Biomarkers

2.9. Specific Applications: Neuroengineering

2.9.1. The Nervous System
2.9.2. New Approaches to Standard Biomaterials

2.9.2.1. Soft Biomaterials
2.9.2.2. Bioabsorbable Materials
2.9.2.3. Implantable Materials

2.9.3. Emerging Biomaterials Tissue Interaction

2.10. Specific Applications: Biomedical Micromachines

2.10.1. Artificial Micronadators
2.10.2. Contractile Microactuators
2.10.3. Small Scale Manipulation
2.10.4. Biological Machines

Module 3. Biomedical Signals

3.1. Biomedical Signals

3.1.1. Origin of Biomedical Signals
3.1.2. Biomedical Signals

3.1.2.1. Amplitude
3.1.2.2. Period
3.1.2.3. Frequency (F)
3.1.2.4. Wave Length
3.1.2.5. Phase

3.1.3. Classification and Examples of Biomedical Signals

3.2. Types of Biomedical Signals. Electrocardiography, Electroencephalography and Magnetoencephalography

3.2.1. Electrocardiography (ECG)
3.2.2. Electroencephalography (EEG)
3.2.3. Magnetoencephalography (MEG)

3.3. Types of Biomedical Signals. Electroneurography and Electromyography

3.3.1. Electroneurography (ENG)
3.3.2. Electromyography (EMG)
3.3.3. Event-Related Potentials (ERPs)
3.3.4. Other Types

3.4. Signals and Systems

3.4.1. Signals and Systems
3.4.2. Continuous and Discrete Signals: Analog vs. Digital
3.4.3. Systems in the Time Domain
3.4.4. Systems in Frequency Domain. Spectral Method

3.5. Fundamentals of Signals and Systems

3.5.1. Sampling: Nyquist
3.5.2. The Fourier Transform. DFT
3.5.3. Stochastic Processes

3.5.3.1. Deterministic vs. Random Signals
3.5.3.2. Types of Stochastic Processes
3.5.3.3. Stationarity
3.5.3.4. Ergodicity
3.5.3.5. Relationships Between Signals

3.5.4. Power Spectral Density

3.6. Processing of Biomedical Signals

3.6.1. Processing of Signals
3.6.2. Objectives and Processing Steps
3.6.3. Key Elements of a Digital Processing System
3.6.4. Applications. Trends

3.7. Filtering: Removal of Artifacts

3.7.1. Motivation. Types of Filtering
3.7.2. Time Domain Filtering
3.7.3. Frequency Domain Filtering
3.7.4. Applications and Examples

3.8. Time-Frequency Analysis

3.8.1. Motivation
3.8.2. Time-Frequency Plane
3.8.3. Short Time Fourier Transform (STFT)
3.8.4. Wavelet Transform
3.8.5. Applications and Examples

3.9. Event Detection

3.9.1. Study Case I: ECG
3.9.2. Study Case II: EEG
3.9.3. Evaluation of Detection

3.10. Software for Biomedical Signal Processing

3.10.1. Applications, Environments and Programming Languages
3.10.2. Libraries and Tools
3.10.3. Practical Application: Basic Biomedical Signal Processing System

Module 4. Biomechanics

4.1. Biomechanics

4.1.1. Biomechanics
4.1.2. Qualitative and Quantitative Analysis

4.2. Basic Mechanics

4.2.1. Functional Mechanisms
4.2.2. Basic Units
4.2.3. The Nine Fundamentals of Biomechanics

4.3. Mechanical Fundamentals. Linear and Angular Kinematics

4.3.1. Linear Movement
4.3.2. Relative Movement
4.3.3. Angular Movement

4.4. Mechanical Fundamentals. Linear Kinetics

4.4.1. Newton’s Law
4.4.2. Principle of Inertia
4.4.3. Energy and Work
4.4.4. Stress Angle Analysis

4.5. Mechanical Fundamentals. Angular Kinetics

4.5.1. Torque
4.5.2. Angular Momentum
4.5.3. Newton's Angles
4.5.4. Balance and Gravity

4.6. Fluid Mechanics

4.6.1. Fluid
4.6.2. Flows

4.6.2.1. Laminar Flow
4.6.2.2. Turbulent Flow
4.6.2.3. Pressure-Velocity: the Venturi Effect

4.6.3. Forces in Fluids

4.7. Human Anatomy: Limitation

4.7.1. Human Anatomy
4.7.2. Muscles: Active and Passive Tension
4.7.3. Mobility Range
4.7.4. Mobility-Strength Principles
4.7.5. Limitations in the Analysis

4.8. Mechanisms of the Motor System. Bone, Muscle-Tendon and Ligament Mechanics

4.8.1. Tissue Functioning
4.8.2. Biomechanics of Bones
4.8.3. Biomechanics of the Muscle-Tendon Unit
4.8.4. Biomechanics of Ligaments

4.9. Mechanisms of the Motor System. Mechanics of Muscles

4.9.1. Mechanical Characteristics of Muscles

4.9.1.1. Force-Speed Relationship
4.9.1.2. Force-Distance Relationship
4.9.1.3. Force-Time Relationship
4.9.1.4. Traction-Compression Cycles
4.9.1.5. Neuromuscular Control
4.9.1.6. The Spine and Backbone

4.10. Mechanics of Biofluids

4.10.1.  Mechanics of Biofluids

4.10.1.1. Transport, Stress and Pressure
4.10.1.2. The Circulatory System
4.10.1.3. Blood Characteristics

4.10.2. General Problems in Biomechanics

4.10.2.1. Problems in Nonlinear Mechanical Systems
4.10.2.2. Problems in Biofluidics
4.10.2.3. Solid-Liquid Problems

Module 5. Medical Bioinformatics

5.1. Medical Bioinformatics

5.1.1. Computing in Medical Biology
5.1.2. Medical Bioinformatics

5.1.2.1. Bioinformatic Applications
5.1.2.2. Computer Systems, Networks and Medical Databases
5.1.2.3. Applications of Medical Bioinformatics in Human Health

5.2.  Computer Equipment and Software Required in Bioinformatics

5.2.1. Scientific Computing in Biological Sciences
5.2.3. The Computer
5.2.4. Hardware, Software and Operating Systems
5.2.5. Workstations and Personal Computers
5.2.6. High-Performance Computing Platforms and Virtual Environments
5.2.7. Linux Operating System

5.2.7.1. Linux Installation
5.2.7.2. Using the Linux Command Line Interface

5.3. Data Analysis Using R Programming Language

5.3.1. Language R Statistical Programming
5.3.2. Installation and Uses of R
5.3.3. Data Analysis Methods With R
5.3.4. R Applications in Medical Bioinformatics

5.4. Data Analysis Using R Programming Language

5.4.1. Multipurpose Programming Language Python
5.4.2. Installation and Uses of Python
5.4.3. Data Analysis Methods With Python
5.4.4. Python Applications in Medical Bioinformatics

5.5. Methods of Human Genetic Sequence Analysis

5.5.1. Human Genetics
5.5.2. Techniques and Methods for Sequencing Analysis of Genomic Data
5.5.3. Sequence Alignments
5.5.4. Tools for Detection, Comparison and Modeling of Genomes

5.6. Data Mining in Bioinformatics

5.6.1. Phases of Knowledge Discovery in Databases, KDD
5.6.2. Processing Techniques
5.6.3. Knowledge Discovery in Biomedical Databases
5.6.4. Human Genomics Data Analysis

5.7. Artificial Intelligence and Big Data Techniques in Medical Bioinformatics

5.7.1. Machine Learning for Medical Bioinformatics

5.7.1.1. Supervised Learning: Regression and Classification
5.7.1.2. Unsupervised Learning: Clustering and Association Rules

5.7.2. Big Data
5.7.3. Computing Platforms and Development Environments

5.8. Applications of Bioinformatics for Prevention, Diagnosis and Clinical Therapies

5.8.1. Disease-Causing Gene Identification Procedures
5.8.2. Procedure to Analyze and Interpret the Genome for Medical Therapies
5.8.3. Procedures to Assess Genetic Predispositions of Patients for Prevention and Early Diagnosis

5.9. Medical Bioinformatics Workflow and Methodology

5.9.1. Creation of Workflows to Analyze Data
5.9.2. Application Programming Interfaces, APIs

5.9.2.1. R and Python Libraries for Bioinformatics Analysis
5.9.2.2. Bioconductor: Installation and Uses

5.9.3. Uses of Bioinformatics Workflows in Cloud Services

5.10. Factors Associated with Sustainable Bioinformatics Applications and Future Trends

5.10.1. Legal and Regulatory Framework
5.10.2. Best Practices in the Development of Medical Bioinformatics Projects
5.10.3. Future Trends in Bioinformatics Applications

Module 6. Human-Machine Interface Applied to Biomedical Engineering

6.1. Human-Machine Interface

6.1.1. Human-Machine Interface
6.1.2. Model, System, User, Interface and Interaction
6.1.3. Interface, Interaction and Experience

6.2. Human-Machine Interaction

6.2.1. Human-Machine Interaction
6.2.2. Principles and Laws of Interaction Design
6.2.3. Human Factors

6.2.3.1. Importance of the Human Factor in the Interaction Process
6.2.3.2. Psychological-Cognitive Perspective: Information Processing, Cognitive Architecture, User Perception, Memory, Cognitive Ergonomics and Mental Models

6.2.4. Technological Factors
6.2.5. Basis of Interaction: Levels and Styles of Interaction
6.2.6. At the Forefront of Interaction

6.3. Interface Design (I): Design Process

6.3.1. Design Process
6.3.2. Value Proposition and Differentiation
6.3.3. Requirements Analysis and Briefing
6.3.4. Collection, Analysis and Interpretation of Information
6.3.5. The Importance of UX and UI in the Design Process

6.4. Interface Design (II): Prototyping and Evaluation

6.4.1. Interface Prototyping and Evaluation
6.4.2. Methods for the Conceptual Design Process
6.4.3. Techniques for Idea Organization
6.4.4. Prototyping Tools and Process
6.4.5. Evaluation Methods
6.4.6. Evaluation Methods with Users: Interaction Diagrams, Modular Design, Heuristic Evaluation
6.4.7. User-Free Evaluation Methods: Surveys and Interviews, Card Sorting, A/B Testing and Design of Experiments
6.4.8. Applicable ISO Norms and Standards

6.5. User Interfaces (I): Interaction Methods in Today's Technologies

6.5.1. User Interface (UI)
6.5.2. Classical User Interfaces: Graphical User Interfaces (GUIs), Web, Touch, Voice, etc.
6.5.3. Human Interfaces and Limitations: Visual, Hearing, Motor and Cognitive Diversity
6.5.4. Innovative User Interfaces: Virtual Reality, Augmented Reality, Collaborative

6.6. User Interfaces (II): Interaction Design

6.6.1. The Importance of Graphic Design
6.6.2. Design Theory
6.6.3. Design Rules: Morphological Elements, Wireframes, Use and Theory of Color, Graphic Design Techniques, Iconography, Typography
6.6.4. Semiotics Applied to Interfaces

6.7. User Experience (I): Methodologies and Design Fundamentals

6.7.1. User Experience(UX)
6.7.2. Evolution of Usability Effort-to-Benefit Ratio
6.7.3. Perception, Cognition and Communication

6.7.3.1. Mental Models

6.7.4. User Focused Design Methodology
6.7.5. Methodology of Design Thinking

6.8. The User Experience (II): User Experience Principles

6.8.1. UX Principles
6.8.2. UX Hierarchy: Strategy, Scope, Structure, Skeleton and Visual Component
6.8.3. Usability and Accessibility
6.8.4. Information Architecture: Classification, Labeling, Navigation, and Search Systems
6.8.5. Affordances & Signifiers
6.8.6. Heuristics: Heuristics of Understanding, Interaction and Feedback

6.9. Interfaces in the Field of Biomedicine (I): the Interaction of the Health Care Worker

6.9.1. Usability in the Intrahospital Context
6.9.2. Interaction Processes in Healthcare Technology
6.9.3. Health Care Provider and Patient Perception
6.9.4. Healthcare Ecosystem: Primary Care Physician vs. Operating Room Surgeon
6.9.5. Interaction of the Healthcare Worker in a Context of Stress

6.9.5.1. ICU Cases
6.9.5.2. The Case of Extreme Circumstances and Emergencies
6.9.5.3. The Case of the Operating Rooms

6.9.6. Open Innovation
6.9.7. Persuasive Design

6.10. Interfaces in the Field of Biomedicine (II): Current Outlook and Future Trends

6.10.1. Classical Biomedical Interfaces in Healthcare Technologies
6.10.2. Innovative Biomedical Interfaces in Healthcare Technologies
6.10.3. The Role of Nanomedicine
6.10.4. Biochips
6.10.5. Electronic Implants
6.10.6. Brain-Computer Interfaces (BCI)

Module 7. Biomedical Images

7.1. Biomedical Images

7.1.1. Medical Images
7.1.2. Objectives of Imaging Systems in Medicine
7.1.3. Types of Images

7.2. Radiology

7.2.1. Radiology
7.2.2. Conventional Radiology
7.2.3. Digital Radiology

7.3. Ultrasound

7.3.1. Medical Images With Ultrasound
7.3.2. Training and Image Quality
7.3.3. Doppler Ultrasound
7.3.4.  mplementation and New Technologies

7.4. Computerized Tomography

7.4.1. CT Imaging Systems
7.4.2. Reconstruction and CT Image Quality
7.4.3. Clinical Applications

7.5. Magnetic Resonance

7.5.1. Magnetic Resonance Imaging (MRI)
7.5.2. Resonance and Nuclear Magnetic Resonance
7.5.3. Nuclear Relaxation
7.5.4. Tissue Contrast and Clinical Applications

7.6. Nuclear Medicine

7.6.1. Generation and Image Detection
7.6.2. Image Quality
7.6.3. Clinical Applications

7.7. Image Processing

7.7.1. Noise
7.7.2. Intensification
7.7.3. Histograms
7.7.4. Magnification
7.7.5. Processing

7.8. Analysis and Image Segmentation

7.8.1. Segmentation
7.8.2. Segmentation by Regions
7.8.3. Edge Detection Segmentation
7.8.4. Generation of Biomodels From Images

7.9. Image-Guided Interventions

7.9.1. Visualization Methods
7.9.2. Image-Guided Surgeries

7.9.2.1. Planning and Simulation
7.9.2.2. Surgical Visualization
7.9.2.3. Virtual Reality

7.9.3. Robotic Vision

7.10. Deep Learning and Machine Learning in Medical Imaging

7.10.1. Types of Recognition
7.10.2. Supervised Techniques
7.10.3. Unsupervised Techniques

Module 8. Digital Health Applications in Biomedical Engineering

8.1. Digital Health Applications

8.1.1. Medical Hardware and Software Applications
8.1.2. Software Applications: Digital Health Systems
8.1.3. Usability of Digital Health Systems

8.2. Medical Image Storage and Transmission Systems

8.2.1. Image Transmission Protocol: DICOM
8.2.2. Medical Image Storage and Transmission Server Installation: PAC System

8.3. Relational Database Management for Digital Health Applications

8.3.1. Relational Database, Concept and Examples
8.3.2. Database Language
8.3.3. Database With MySQL and PostgreSQL
8.3.4. Applications: Connection and Uses in Web Programming Language

8.4. Digital Health Applications Based on Web Development

8.4.1. Web Application Development
8.4.2. Web Development Model, Infrastructure, Programming Languages and Working Environments
8.4.3. Examples of Web Applications With the Languages: PHP, HTML, AJAX, CSS Javascript, AngularJS, NodeJS
8.4.4. Development of Applications in Web Frameworks: Symfony and Laravel
8.4.5. Development of Applications in Content Management Systems (CMS): Joomla and WordPress

8.5. WEB Applications in a Hospital Environment or Clinical Center

8.5.1. Applications for Patient Management: Reception, Scheduling, and Billing
8.5.2. Applications for Medical Professionals: Consultations or Medical Care, Medical History, Reports, etc.
8.5.3. Web and Mobile Applications for Patients: Scheduling Requests, Monitoring, etc.

8.6. Telemedicine Applications

8.6.1. Service Architecture Models
8.6.2. Telemedicine Applications: Teleradiology, Telecardiology and Teledermatology
8.6.3. Rural Telemedicine

8.7. Applications With the Internet of Medical Things, IoMT

8.7.1. Models and Architectures
8.7.2. Medical Data Acquisition Equipment and Protocols
8.7.3. Applications: Patient Monitoring

8.8. Digital Health Applications Using Artificial Intelligence Techniques

8.8.1. Machine Learning
8.8.2. Computing Platforms and Development Environments
8.8.3. Examples

8.9. Digital Health Applications with Big Data

8.9.1. Digital Health Applications with Big Data
8.9.2. Technologies Used in Big Data
8.9.3. Use Cases of Big Data in Digital Health

8.10. Factors Associated With Sustainable Digital Health Applications and Future Trends

8.10.1. Legal and Regulatory Framework
8.10.2. Best Practices in the Development of Digital Health Application Projects
8.10.3. Future Trends in Digital Health Applications

Module 9. Biomedical Technologies: Biodevices and Biosensors

9.1. Medical Devices

9.1.1. Product Development Methodology
9.1.2. Innovation and Creativity
9.1.3. CAD Technologies

9.2. Nanotechnology

9.2.1. Medical Nanotechnology
9.2.2. Nanostructured Materials
9.2.3. Nano-Biomedical Engineering

9.3. Micro and Nanofabrication

9.3.1. Design of Micro and Nano Products
9.3.2. Techniques
9.3.3. Tools for Manufacturing

9.4. Prototypes

9.4.1. Additive Manufacturing
9.4.2. Rapid Prototyping
9.4.3. Classification
9.4.4. Applications
9.4.5. Study Cases
9.4.6. Conclusions

9.5. Diagnostic and Surgical Devices

9.5.1. Development of Diagnostic Methods
9.5.2. Surgical Planning
9.5.3. Biomodels and Instruments Made With 3D Printing
9.5.4. Device-Assisted Surgery

9.6. Biomechanic Devices

9.6.1. Prosthetists
9.6.2. Intelligent Materials
9.6.3. Orthotics

9.7. Biosensors

9.7.1. Biosensor
9.7.2. Sensing and Transduction
9.7.3. Medical Instrumentation for Biosensors

9.8. Types of Bio-Sensors (I): Optic Sensors

9.8.1. Reflectometry
9.8.2. Interferometry and Polarimetry
9.8.3. Evanescent Field
9.8.4. Fiber Optic Probes and Guides

9.9. Types of Bio-Sensors (II): Physical, Electrochemical and Acoustic Sensors

9.9.1. Physical Sensors
9.9.2. Electrochemical Sensors
9.9.3. Acoustic Sensors

9.10. Integrated Systems

9.10.1. Lab-On-A-Chip
9.10.2. Microfluidics
9.10.3. Medical Application

Module 10. Biomedical and Healthcare Databases

10.1. Hospital Databases

10.1.1. Data Bases
10.1.2. The Importance of Data
10.1.3. Data in a Clinical Context

10.2. Conceptual Modeling

10.2.1. Data Structure
10.2.2. Systematic Data Model
10.2.3. Data Standardization

10.3. Relational Data Model

10.3.1. Advantages and Disadvantages
10.3.2. Formal Languages

10.4. Designing from Relational Databases

10.4.1. Functional Dependence
10.4.2. Relational Forms
10.4.3. Standardization

10.5. SQL Language

10.5.1. Relational Model
10.5.2. Object-Relationship Model
10.5.3. XML- Object-Relationship Model

10.6. NoSQL

10.6.1. JSON
10.6.2. NoSQL
10.6.3. Differential Amplifiers
10.6.4. Integrators and Differentiators

10.7. MongoDB

10.7.1. ODMS Architecture
10.7.2. NodeJS
10.7.3. Mongoose
10.7.4. Aggregation

10.8. Data Analysis

10.8.1. Data Analysis
10.8.2. Qualitative Analysis
10.8.3. Quantitative Analysis

10.9. Legal Bases and Regulatory Standards

10.9.1. General Data Protection Regulation
10.9.2. Cybersecurity Considerations
10.9.3. Regulations Applied to Health Data

10.10. Integration of Databases in Medical Records

10.10.1. Medical History
10.10.2. HIS Systems
10.10.3. HIS Data

This academic itinerary is exclusive to TECH and you will be able to develop it at your own pace thanks to its 100% online Relearning methodology"