Performance and Bench Verification Guide

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Summary

The Performance and Bench Verification Guide provides a systematic framework for planning and executing non-clinical testing that verifies your medical device meets design specifications (verification) and validates it fulfills user needs (validation). This guide focuses on mechanical and functional performance testing that can be conducted in laboratory settings.

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Why is Performance and Bench Verification important?

Performance and bench verification is essential because it provides objective evidence that your device functions as intended before human testing or market release. This testing identifies design flaws, validates engineering assumptions, and demonstrates compliance with performance requirements in controlled laboratory conditions.

Bench testing is often more cost-effective and faster than clinical testing while providing precise, repeatable measurements of device performance. It allows you to optimize device design, validate manufacturing processes, and build confidence in device performance before proceeding to more expensive validation activities like clinical studies or usability testing.

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Regulatory Context

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Guide

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Understanding Verification vs. Validation Testing

Verification testing confirms that your design outputs meet design inputs by testing against specific technical requirements. This includes testing individual subsystems and components to ensure they perform according to specifications.

Validation testing confirms that your complete device meets user needs and intended use requirements. This involves testing the integrated system under realistic use conditions to demonstrate it solves the clinical problem it was designed to address.

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Planning Your Performance Testing Strategy

Your performance testing strategy should address all critical device functions identified in your user needs and system requirements. Prioritize testing based on risk analysis, focusing on functions that could impact patient safety or device effectiveness if they fail.

Test method selection should follow established standards when available, as this provides regulatory credibility and enables comparison with other devices. When standards don’t exist, develop test methods based on scientific principles and justify your approach.

Test environment design should represent realistic use conditions while maintaining sufficient control for repeatable measurements. Consider factors like temperature, humidity, vibration, electromagnetic interference, and user variability that could affect device performance.

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Developing Verification Test Plans

Subsystem requirement testing verifies that individual device components meet their specified performance criteria. Each subsystem requirement should be traceable to specific test cases that objectively measure compliance.

Test case development should specify test procedures, sample sizes, acceptance criteria, and statistical analysis methods. Include both normal operating conditions and edge cases that represent the limits of acceptable performance.

Measurement system validation ensures your test methods are capable of detecting meaningful differences in device performance. Consider measurement accuracy, precision, and repeatability when designing test protocols.

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Developing Validation Test Plans

User need validation demonstrates that your device successfully addresses the clinical problems identified in your user needs analysis. These tests should simulate realistic use scenarios and measure outcomes that matter to users.

Integrated system testing evaluates how well different device components work together to deliver the intended clinical benefit. This testing often reveals interface issues or system-level performance limitations not apparent in component testing.

Use case scenario testing validates device performance across the range of intended use conditions, user types, and clinical scenarios. Include testing with different patient populations, use environments, and operator skill levels as appropriate.

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Statistical Considerations and Sample Sizing

Sample size determination should provide adequate statistical power to detect meaningful differences while considering practical constraints like cost and timeline. Use your Statistical Methods SOP to guide sample size calculations based on expected effect sizes and measurement variability.

Statistical analysis planning should be defined before testing begins to avoid bias in data interpretation. Specify primary endpoints, statistical tests, and criteria for statistical significance.

Acceptance criteria definition should be based on clinical relevance, not just statistical significance. Consider what level of performance difference would be meaningful to users and patients when setting acceptance thresholds.

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Managing Test Execution and Documentation

Test protocol adherence is critical for generating reliable, defensible data. Train test operators on proper procedures and implement quality controls to ensure consistent test execution.

Data integrity requires careful documentation of test conditions, raw data, calculations, and any deviations from planned procedures. Use electronic data capture systems when possible to reduce transcription errors.

Change control ensures that protocol modifications are properly documented and justified. Significant protocol changes may require retesting to maintain data integrity.

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Example

Scenario: You are developing a wearable heart rate monitor that provides continuous monitoring and alerts for abnormal rhythms. The device includes optical sensors, signal processing algorithms, and wireless connectivity for data transmission to a smartphone app.

Your performance verification plan tests sensor accuracy against reference ECG devices across different heart rate ranges, validates algorithm performance for detecting arrhythmias using known test signals, and verifies wireless transmission reliability under various interference conditions. Validation testing demonstrates that the complete system can accurately detect clinically significant arrhythmias in realistic use scenarios and provides appropriate user notifications.

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Performance and Bench Verification Guide

Document ID: PBVG-001
Version: 1.0

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1. Purpose

This guide provides a structured approach to plan, execute, and document non-clinical performance testing of the CardioWatch wearable heart rate monitor to verify design requirements and validate user needs.

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2. Scope

This guide covers mechanical and functional performance testing of the CardioWatch system, excluding packaging, shelf-life, electrical safety, and biocompatibility testing which are addressed in separate protocols.

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3. Verification Testing

Subsystem ID	Subsystem Requirement	Test ID	Testing Required	Acceptance Criteria
SS-001	Heart rate accuracy ±3 bpm (60-180 bpm range)	VT-001	Optical sensor accuracy testing against reference ECG	Measured HR within ±3 bpm of reference for 95% of measurements
SS-002	Arrhythmia detection sensitivity ≥95%	VT-002	Algorithm testing with known arrhythmia signals	Detect ≥95% of atrial fibrillation episodes in test dataset
SS-003	Battery life ≥7 days continuous monitoring	VT-003	Power consumption measurement under continuous use	Average power consumption ≤5mW during monitoring mode
SS-004	Wireless range ≥10 meters line-of-sight	VT-004	Bluetooth transmission range testing	Maintain connection at 10m distance with <1% packet loss
SS-005	Water resistance IPX7 rating	VT-005	Immersion testing per IEC 60529	No water ingress after 30 minutes at 1m depth

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4. Validation Testing

UN ID	User Need	Test ID	Testing Required	Acceptance Criteria
UN-001	Accurately monitor heart rate during daily activities	VL-001	Real-world activity simulation testing	HR accuracy maintained during walking, running, and stationary activities
UN-002	Detect irregular heart rhythms and alert user	VL-002	Integrated arrhythmia detection validation	System detects AF episodes and delivers alerts within 30 seconds
UN-003	Provide continuous monitoring without frequent charging	VL-003	Extended wear testing simulation	Device operates ≥7 days with typical usage patterns
UN-004	Sync data reliably with smartphone app	VL-004	End-to-end data transmission validation	≥99% successful data synchronization under normal use conditions

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5. Test Methods and Procedures

5.1 Heart Rate Accuracy Testing (VT-001)

• Reference Standard: 12-lead ECG with validated heart rate calculation
• Test Conditions: Controlled laboratory environment, multiple subjects
• Procedure: Simultaneous measurement with CardioWatch and reference ECG
• Sample Size: 30 subjects, 5 measurements per subject across HR range
• Analysis: Bland-Altman analysis of agreement between methods

5.2 Arrhythmia Detection Testing (VT-002)

• Test Signals: MIT-BIH Arrhythmia Database with known AF episodes
• Procedure: Process test signals through CardioWatch algorithm
• Metrics: Sensitivity, specificity, positive predictive value
• Sample Size: 100 AF episodes, 100 normal rhythm segments

5.3 Battery Life Testing (VT-003)

• Test Setup: Continuous monitoring mode with periodic data transmission
• Measurement: Current consumption using precision power analyzer
• Duration: 168 hours (7 days) continuous operation
• Conditions: 25°C ambient temperature, typical usage profile

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6. Statistical Analysis Plan

Primary Analysis: Descriptive statistics for all measured parameters with 95% confidence intervals. Comparison of measured values to acceptance criteria using appropriate statistical tests.

Sample Size Justification: Sample sizes calculated to detect clinically meaningful differences with 80% power and α=0.05. Minimum 30 subjects for accuracy testing based on FDA guidance for heart rate monitors.

Acceptance Criteria: All primary endpoints must meet specified criteria. Secondary endpoints provide supporting evidence but don’t determine pass/fail status.

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7. Test Report Requirements

Data Documentation: Raw data, calculated results, statistical analysis, and graphical summaries for all test activities.

Deviation Reporting: Any deviations from planned procedures must be documented with justification and impact assessment.

Conclusion: Clear statement of whether device meets all verification and validation criteria with supporting evidence.

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Q&A