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About

Human Factors and Usability Engineering is a critical discipline that ensures medical devices are designed to be safe, effective, and easy to use by their intended users in real-world environments. By applying a systematic usability engineering process, manufacturers can identify and reduce use-related risks, improve user performance, and support regulatory compliance throughout the product lifecycle.
This Human Factors and Usability Engineering for Medical Devices Training Course & Certification provides comprehensive knowledge of human factors principles, usability engineering processes, user and use environment analysis, task analysis, use-related risk management, formative evaluations, user interface design, human factors validation studies, the Usability Engineering File, regulatory expectations, and post-market usability activities. Upon successful completion, learners receive a certification demonstrating their understanding of human factors engineering and medical device usability best practices.

Who Should Enrol?

  • Medical Device Design and Development Engineers
  • Human Factors and Usability Engineering Professionals
  • Quality Assurance and Quality Management Professionals
  • Regulatory Affairs and Compliance Professionals
  • Risk Management Specialists
  • Verification, Validation, and Testing Engineers
  • Medical Device Product Managers and Project Managers
  • Anyone involved in the design, development, evaluation, or regulatory compliance of medical devices
📢 Every purchase also includes our FREE companion Human Factors and Usability Engineering eBook, designed to help you apply principles in real-world clinical trial settings.

What you will learn

Understand the principles of human factors and usability engineering, applicable regulatory requirements, and the role of usability in ensuring the safety and effectiveness of medical devices.

Learn how to identify users, use environments, intended use, use scenarios, critical tasks, and use-related hazards throughout the medical device lifecycle.

Develop knowledge of task analysis, use-related risk analysis, formative evaluations, user interface design, and human factors validation studies in accordance with industry standards.

Gain practical understanding of usability engineering documentation, the Usability Engineering File, regulatory submissions, post-market feedback, and lifecycle management best practices.

Course Syllabus

  1. What human factors engineering is
  2. Use error is a leading safety concern
  3. Human capabilities and limitations — the map
  4. Perception and its limits
  5. Cognition and mental models
  6. Memory — working versus long-term
  7. Attention — selective, divided and vigilance
  8. Physical capability and anthropometry
  9. Fatigue and stress
  10. Usability, defined
  11. User experience (UX), defined
  12. Use-related safety, defined
  13. Usability vs UX vs use-related safety
  14. How the three concepts nest
  15. Why the terminology must be exact
  16. Use error
  17. Abnormal use
  18. Reasonably foreseeable misuse
  19. Close call
  20. Operational difficulty
  21. The five terms at a glance
  22. Design controls — the framework
  23. Design inputs and outputs
  24. Verification versus validation
  25. Where usability engineering sits
  26. Design review and the design file
  27. FDA QMSR — design controls, updated
  28. IEC 62366-1:2015 (+A1:2020) — overview
  29. The usability engineering process
  30. The use specification
  31. User interface and known use
  32. Hazard-related use scenarios
  33. Formative versus summative evaluation
  34. IEC/TR 62366-2:2016 — guidance
  35. ISO 14971:2019 and use-related risk
  36. ISO/TR 24971:2020 — guidance
  37. IEC 60601-1-6 — the usability collateral
  38. How the standards fit together
  39. FDA 2016 human factors guidance
  40. Critical tasks — a first look
  41. FDA submissions guidance — final 2026
  42. The three HF submission categories
  43. EU MDR — Regulation (EU) 2017/745
  44. MDR Annex I — usability and information for safety
  45. MDR technical documentation
  46. IEC 62366-1 in the EU — a nuance
  47. Human factors across the lifecycle
  48. Misconception — 'training fixes the interface'
  49. Misconception — 'labels eliminate risk'
  50. Misconception — 'one validation proves it forever'

  1. Why users, environments and the Use Specification come first
  2. Three terms people blur: indication, purpose, use
  3. Intended medical indication, defined
  4. Intended purpose, defined
  5. Intended use and the instructions for use
  6. Who counts as a user?
  7. User groups and subgroups
  8. Healthcare professionals as users
  9. Patients and lay users
  10. Lay caregivers
  11. Maintenance, service and reprocessing personnel
  12. Template T002 — the User Group Profile
  13. Why user characteristics matter
  14. Knowledge, experience and training level
  15. Language, literacy and numeracy
  16. Sensory ability, including low vision
  17. Physical ability, including limited dexterity
  18. Cognitive ability, health and emotional state
  19. Design for the range, not the average user
  20. Why the use environment matters
  21. Hospital and clinic environments
  22. The home use environment
  23. Ambulance, transport and emergency settings
  24. Laboratory and public settings
  25. Environmental factors — lighting, noise, space
  26. Environmental factors — stress, interruptions, PPE
  27. Environmental factors — connectivity and cleaning
  28. Template T003 — the Use Environment Profile
  29. The operating principle
  30. User-interface elements
  31. Accessories
  32. Connected systems and interoperability
  33. Use scenarios in the Use Specification
  34. Frequency, duration and sequence of use
  35. Normal use and reasonably foreseeable scenarios
  36. Training assumptions in the Use Specification
  37. The risk of excessive reliance on training
  38. What is a Use Specification?
  39. Structure of a Use Specification (template T001)
  40. Traceability to design inputs
  41. The Use Specification as the foundation
  42. What a good Use Specification contains
  43. Where the Use Specification sits — IEC 62366-1
  44. Worked example — infusion device
  45. Worked example — auto-injector
  46. Worked example — diagnostic system (IVD)
  47. Worked example — Software as a Medical Device (SaMD)
  48. Worked example — home-use monitoring device
  49. A peer-review checklist for the Use Specification

  1. Why known use problems come before new risk analysis
  2. The sources landscape for known use problems
  3. Source 1 — complaints and CAPA records
  4. Source 2 — recalls and field safety corrective actions
  5. Source 3 — adverse-event databases
  6. Source 4 — published and grey literature
  7. Source 5 — analogous and predicate devices
  8. Source 6 — service, maintenance and post-market signals
  9. Building a search strategy
  10. Appraising relevance and reliability
  11. The Known Use Problems Search Log — template T004
  12. Logging discipline and traceability
  13. What task analysis is, and why it matters
  14. Hierarchical task analysis (HTA)
  15. Cognitive task analysis (CTA)
  16. Choosing and combining HTA and CTA
  17. Decomposing a task: subtasks, decisions, feedback, error opportunities
  18. The perception-action cycle
  19. Information flow: displays, controls and the user
  20. Do not analyse only normal use
  21. Normal-use and emergency-use tasks
  22. Maintenance, cleaning, installation and disposal tasks
  23. Reasonably foreseeable use scenarios
  24. Edge cases and the worst credible scenario
  25. The Use Scenario Catalogue — template T006
  26. Sequence diagrams: showing the interaction over time
  27. Journey maps: the user's experience end to end
  28. User-interface flow models
  29. From task failure to hazardous situation
  30. Task failures caused by labels and instructions
  31. Task failures caused by controls
  32. Task failures caused by displays and alarms
  33. Task failures caused by software navigation and physical layout
  34. Common failures in known-problem gathering and task analysis
  35. From task analysis into use-related risk
  36. Slips, lapses and mistakes
  37. Use error, close call and operational difficulty
  38. Harvesting close calls and operational difficulties
  39. Mental models and user expectation
  40. Interruptions, workload and attention
  41. Methods for eliciting task information
  42. Mode confusion in connected devices
  43. Linking known problems to user groups and environments
  44. Prioritising which tasks to analyse in depth

  1. What use-related risk analysis is
  2. Integrating with ISO 14971 hazard analysis
  3. The use-related risk chain
  4. Sharpening the terminology of use
  5. Potential use errors: where to look
  6. Contributing design factors
  7. User-interface characteristics related to safety
  8. Primary operating functions
  9. What makes a task critical
  10. Determining critical tasks — a risk-based decision
  11. The Critical Task Register — template T008
  12. Why probability of a use error cannot be meaningfully estimated
  13. Prioritise on severity
  14. The software-risk parallel
  15. Risk controls: the order of precedence
  16. Tier 1 — inherent safety by design
  17. Tier 2 — protective measures
  18. Tier 3 — information for safety is the weakest control
  19. Strong versus weak controls, compared
  20. From risk control to user-interface requirement
  21. The User-Interface Requirements template — T009
  22. Residual risk and overall residual risk
  23. Benefit-risk considerations
  24. The traceability thread
  25. The Use-Related Risk Analysis template — T007
  26. Common failures in use-related risk analysis
  27. Use-related hazard versus its cause
  28. Reasonably foreseeable misuse in the risk analysis
  29. Categories of use error
  30. Error-producing conditions
  31. Mapping errors to perception, cognition and action
  32. Primary operating function versus critical task
  33. Grouping and documenting critical tasks
  34. Severity scales and harm categories
  35. Judge on worst credible harm
  36. Detectability does not rescue a use-related risk
  37. Defence in depth: combining controls
  38. New risks introduced by risk controls
  39. Verifying that a control is effective
  40. Using information for safety well
  41. Writing verifiable user-interface requirements
  42. Linking requirements to design controls
  43. Production and post-production information
  44. The risk-management report and human factors
  45. Connected, combination and home-use considerations

  1. What formative evaluation is
  2. When to run formative evaluation: early and often
  3. Formative evaluation across the development lifecycle
  4. The value of finding problems early
  5. Formative versus summative — the central distinction
  6. Danger — never present formative work as validation
  7. What each evaluation can and cannot tell you
  8. The formative methods toolkit
  9. Heuristic review and expert review
  10. Cognitive walkthrough
  11. Interviews and contextual inquiry
  12. Simulated-use formative testing
  13. Choosing a method to fit the stage and question
  14. Representative participants — why it matters
  15. Defining participant characteristics
  16. How many participants for a formative study?
  17. Prototype fidelity — low, medium and high
  18. Low- and medium-fidelity prototypes
  19. High-fidelity prototypes and matching fidelity to the question
  20. The formative evaluation plan (template T010)
  21. Writing formative scenarios and tasks
  22. Designing data collection
  23. Moderator behaviour — do not lead or coach
  24. Think-aloud and probing without steering
  25. Three kinds of formative data
  26. Observational data
  27. Performance and subjective data
  28. Root-cause analysis of use errors and close calls
  29. Distinguishing use error, close call and difficulty
  30. The root-cause interview (template T015)
  31. Design iteration on the evidence
  32. Documenting design decisions — why a change was made
  33. Knowing when not to change
  34. Re-testing after a change
  35. Formative evidence and risk controls
  36. What formative evidence can and cannot support
  37. Remote and unmoderated formative studies
  38. Software and app prototype testing
  39. Accessibility in formative studies
  40. Formative Evaluation Plan — template T010 in full
  41. Formative Evaluation Report — template T011
  42. Common failures in formative evaluation
  43. From formative to a stable, validatable design
  44. Setting clear formative objectives
  45. Simulating the use environment in formative work
  46. Recruiting and screening participants
  47. Consent and ethics in formative studies
  48. Piloting the session before you run it
  49. Triangulating the three data types
  50. Prioritising findings for iteration
  51. Comparative formative testing of design options
  52. Formative testing of connectivity and stale data (KUP-05)
  53. Turning formative findings into UI requirements
  54. How many rounds, and when to stop
  55. Team roles in a formative study
  56. Formative work for connected, combination and home-use devices

  1. What human factors validation is
  2. Validation is part of design validation
  3. Validation versus verification
  4. Formative and summative — the boundary restated
  5. What validation must demonstrate
  6. Validation readiness — are you ready to validate?
  7. The stable, frozen user interface
  8. Danger — do not validate a moving target
  9. Validation focuses on the critical tasks
  10. Selecting validation scenarios
  11. Developing realistic use scenarios
  12. Including reasonably foreseeable misuse
  13. Combining tasks into realistic sequences
  14. Representative users for validation
  15. Distinct user groups and subgroup coverage
  16. Sample size is a risk-based rationale, not a universal number
  17. On FDA's '15 per group' convention
  18. Building the sample-size rationale
  19. Use environments in validation
  20. Simulated-use fidelity
  21. Actual-use considerations
  22. Training conditions in validation
  23. Realistic training, not over-training
  24. Training decay periods
  25. The moderator script
  26. Preventing coaching in validation
  27. Data-collection forms (template T014)
  28. Predefine the definitions before the study
  29. Capturing data for later root-cause analysis
  30. Study controls and avoiding confounds
  31. Safety controls during the study
  32. Study stopping rules
  33. Ethics and oversight
  34. Pilot study and protocol refinement
  35. Acceptance rests on analysis of use-related risk
  36. Why a pass percentage is the wrong criterion
  37. A residual use error is analysed, not an automatic fail
  38. A clean run is not an automatic pass
  39. The acceptance reasoning
  40. Residual risk and benefit-risk in the conclusion
  41. The human factors validation protocol (template T012)
  42. What the protocol fixes in detail
  43. Defining task success and assists precisely
  44. Predefining the analysis approach
  45. Protocol review and roles
  46. Mapping scenarios to critical tasks
  47. FDA submission expectations
  48. Preview — the three HF Submission Categories
  49. Organising the study documentation
  50. A note on EU technical documentation
  51. Common failures in validation planning
  52. What good validation planning delivers
  53. Think-aloud in validation — retrospective only
  54. Recording and observation logistics
  55. Counterbalancing scenario order
  56. Non-critical tasks and overall realism
  57. Using formative results to inform the plan
  58. Test sites and environment set-up

  1. From plan to execution
  2. The execution mindset
  3. The execution-to-report workflow
  4. Setting up and controlling the test site
  5. Equipment control and configuration management
  6. Confirming the exact UI version under test
  7. Recording and observation set-up
  8. Recruitment and screening confirmation
  9. Informed consent
  10. Confidentiality and data protection
  11. The moderator role during execution
  12. Observational discipline - no coaching, no leading
  13. Standardised task instructions and prompts
  14. When a participant asks for help
  15. Handling deviations from the protocol
  16. Unexpected events during a session
  17. Equipment failure mid-session
  18. Documenting deviations and their impact
  19. What to capture in each session
  20. Recording task outcomes precisely
  21. Identifying use errors in the moment
  22. Close calls and operational difficulties
  23. Capturing participant comments
  24. Comprehension methods
  25. The purpose of root-cause interviews
  26. Interview without leading - ask why, do not suggest
  27. Good and poor interview questions
  28. Probing perception, cognition and action
  29. Coding and categorising the data
  30. Inter-rater consistency
  31. Traceability of every observation
  32. Managing the raw dataset
  33. The analysis approach
  34. Analysis by task
  35. Analysis by user group
  36. Analysis by scenario
  37. Analysis by potential harm
  38. Aggregating and finding patterns
  39. Determining whether a design change is needed
  40. The risk-control hierarchy revisited
  41. Additional controls versus redesign
  42. Residual use-related risk conclusions
  43. Benefit-risk in the conclusion
  44. Updating the risk-management file
  45. The Human Factors Validation Report (T016)
  46. The report contents in detail
  47. Writing the conclusion honestly
  48. Inadequate conclusions and unsupported claims
  49. 'No use errors, therefore safe' - why it is wrong
  50. More unsupported claims to avoid
  51. Common failures in execution, analysis and reporting
  52. What good execution and reporting delivers
  53. Handover to the file and submission

  1. From the validation report to the file
  2. The usability engineering process at a glance
  3. The Usability Engineering File structure (T017)
  4. What goes in the file - and what does not
  5. Traceability across the file
  6. Traceability to design inputs
  7. Traceability to risk management
  8. Traceability to verification and validation
  9. EU technical documentation under the MDR
  10. Design-history evidence under the MDR
  11. FDA marketing submissions and human factors
  12. The final submissions guidance (29 May 2026)
  13. The risk-based framework - overview
  14. The three HF Submission Categories
  15. Choosing the category - a decision tree
  16. From 1 August 2026 - templates prompt the category
  17. Summarising the evidence (checklist T018)
  18. Summarising users, environments and known problems
  19. Summarising critical tasks, formative and validation
  20. Legacy user-interface evaluation
  21. How to evaluate a legacy interface
  22. Changes to user interfaces and software
  23. Changes to labels, accessories and training
  24. When a change re-opens usability work
  25. Assessing the impact of a change
  26. Post-market surveillance and usability
  27. Use-related signal detection (T019)
  28. Distinguishing use error from device malfunction
  29. CAPA and usability
  30. Field-action implications
  31. Home-use device considerations
  32. Connected and software-driven devices
  33. AI-enabled device considerations
  34. Combination-product considerations
  35. Maintaining usability evidence over the lifecycle
  36. Audit and inspection readiness
  37. What auditors and reviewers look for
  38. Common failures in files and submissions
  39. What good file and submission management delivers
  40. The traceability matrix in practice
  41. FDA and EU - two homes for the same evidence
  42. Marketing submission types and where HF fits
  43. Complaints handling and use-related coding
  44. Keeping the file and the submission consistent
  45. Human factors across the total product lifecycle

  1. 📘 Bonus: Human Factors and Usability Engineering eBook (Free with purchase)

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