Novel Experimental Validation of A Critical Care Ventilator Using Real-time Simulated Patient Clinical Models and Stringent Automated Data Verification, First Time in India

INTRODUCTION: Based on the perceived urgency during the COVID pandemic, a completely indigenous ICU ventilator was developed in Pune, India. There was a critical need to establish accurate validation tests before clinical use. At the time, India lacked validation methods meeting international standards. This paper presents a novel approach to validating the performance of a critical care ventilator through real-time patient simulations using the ASL5000 lung simulator and automated data interpretation tools like MS Excel. The ventilator was tested stringently under various respiratory conditions, including standard, obstructive, and restrictive patterns, simulated with the ASL5000 lung simulator. An automated interpretation tool ensured precise validation by comparing set and monitored parameters with measured and Fluke VT650 on ASL5000. OBJECTIVES: To introduce a comprehensive testing protocol for critical care ventilators using various real-time simulated clinical models. To validate key ventilator performance metrics, including tidal volume accuracy, trigger response time, and patient-ventilator asynchrony. MATERIALS AND METHODS: 1. Simulated Lung Mechanics: a. Phase 1: Standard conditions (Standard, Obstructive, Restrictive) simulated for compliance and resistance variations. b. Phase 2: Expanded scenarios, including mixed obstructive and restrictive conditions and varying inspiratory muscle efforts. 2. Experimental Setup: a. The ventilator circuit was connected to a Fluke VT650 gas analyzer and the ASL5000 lung simulator. Data from the ASL5000 was processed using MS Excel for automated interpretation. 3. Measurement Parameters: a. Key metrics included tidal volume accuracy, trigger response time, pressure-time product, and patient-ventilator asynchrony. RESULTS: 1. Parameter Accuracy: a. Tidal volume, PIP, and PEEP were delivered within tolerance limits (10% of set values). 2. Trigger Response: a. Trigger responses were under 200 ms for low effort intensities, except in COPD conditions (212 ms). 3. Pressurization Capacity: a. Noccarc V730i consistently delivered satisfactory pressurization across all test scenarios. 4. Patient-Ventilator Synchrony: a. Asynchrony events were minimal, with effective adjustments for flow triggering and pressure sensitivity. CONCLUSIONS: This study demonstrates the successful validation of the Noccarc V730i ventilator. The integration of real-time simulations and automated data verification provides a scalable framework for ventilator testing. These methods ensure clinical safety and reliability across diverse patient scenarios, addressing a critical gap in validation techniques in India and setting new benchmarks for ventilator performance evaluation.