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510(k) Data Aggregation
(169 days)
The 6203 is indicated for use to conserve oxygen for patients prescribed 1 to 6 liters per minute of supplemental oxygen and use nasal cannulas and USP bottled oxygen.
The Wave Conserver Model 6203 is indicated for use to conserve oxygen for patients prescribed 1 to 6 liters per minute of supplemental oxygen and use of a nasal cannula and USP bottled oxygen.
The 6203 with integrated pressure regulator is intended to be used as an accessory to an oxygen supply system to reduce or conserve the amount of oxygen used by the patient. The 6203 is a battery operated electronic device that is microprocessor controlled and contains a breath sensor and a normally closed valve. When installed between the oxygen supply and patient's nasal cannula, the device detects the patient's inhalation, opens the valve according to the flow rate set on the device and delivers a preset bolus of oxygen to the patient as determined by the device flow rate algorithm. The valve closes and conserves the oxygen that would have been wasted during the end of inhalation and during exhalation.
This device is an oxygen conserver and its performance is described in terms of its functional capabilities, alarm system, and environmental robustness, rather than diagnostic accuracy. As such, the typical acceptance criteria and study components requested for AI/ML devices (like sample size for test sets, expert ground truth, MRMC studies, or standalone performance) are not applicable or provided in this 510(k) summary.
Here's an analysis based on the provided text, focusing on what is relevant for this type of medical device:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Specific Criteria/Tests Performed | Reported Device Performance |
|---|---|---|
| Functional Performance | Delivering appropriate bolus size for given liter flow settings (1-6 lpm) | Met performance objectives; Chart 1 details bolus sizes delivered (e.g., 1 lpm: 15 ml, 6 lpm: 81 ml). |
| Alarm System | Detect insufficient negative pressure (apnea) within 45 seconds | Produces audible alarm tone if no sufficient negative pressure detected within 45 seconds. |
| Detect microprocessor failure | Flow/apnea light lights steady red if microprocessor fails. | |
| Environmental Robustness | Impact/drop testing | Demonstrated that it meets its performance objectives. |
| Storage temperature testing | Demonstrated that it meets its performance objectives. | |
| Electromagnetic interference testing | Demonstrated that it meets its performance objectives. | |
| Electrostatic discharge testing | Demonstrated that it meets its performance objectives. | |
| Surface temperature testing | Demonstrated that it meets its performance objectives. | |
| Power Supply | Battery life testing | Demonstrated that it meets its performance objectives. |
| Low power indicator testing | Battery LED winks every 2 seconds (3 hours remaining), every 1 second (30 minutes remaining), then lights steady (unit shut down). |
2. Sample Size Used for the Test Set and Data Provenance
- Not Applicable. The submission describes "Extensive functional testing" and testing under "various environmental conditions" for device performance. There is no mention of a human-centric or data-driven "test set" in the context of an AI/ML diagnostic device. The testing appears to be engineering and design validation on the physical device itself.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts
- Not Applicable. See point 2. The "ground truth" here is the device's adherence to its design specifications and safety standards, validated through engineering tests, not expert consensus on medical images or patient data.
4. Adjudication Method for the Test Set
- Not Applicable. See point 2 and 3.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
- Not Applicable. This is a demand oxygen conserving device, not an AI/ML diagnostic or assistive tool for human readers.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not Applicable. This is a physical electronic device, not a standalone algorithm. Its performance is inherent to its design and function. The device's operation is "algorithm only" in the sense that its microprocessor controls the valve based on its internal programming (e.g., the bolus size chart).
7. The Type of Ground Truth Used
- The "ground truth" for this device's performance is its engineering specifications and design requirements. This includes:
- Validated bolus delivery volumes corresponding to specified liter flow settings (Chart 1).
- Accurate detection of pressure changes indicating inhalation.
- Reliable alarm activation for apnea/disconnection and microprocessor failure.
- Durability and resilience to environmental factors (impact, temperature, EMI/ESD).
- Correct indication of battery status and low power.
8. The Sample Size for the Training Set
- Not Applicable. As a hardware device with embedded software (not a machine learning model), there is no concept of a "training set" in the conventional AI/ML sense. The device's software logic is developed based on engineering principles and validated through testing.
9. How the Ground Truth for the Training Set Was Established
- Not Applicable. See point 8. The "ground truth" for the device's design would be derived from clinical requirements for oxygen delivery, respiratory physiology, and safety standards for medical devices, which informed the device's engineering specifications.
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