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The pulse oximeter is a reusable device and intended for spot-checking of oxygen saturation and pulse rate for use with the finger of adult patients in healthcare environments. And it is not intended to be used under motion or low perfusion scenarios.

The oximeter consists of probe, electronic circuits, and display and plastic enclosures. And one side of probe is designed to locate light emitting diodes and a light detector (called a photo-detector). Red and Infrared lights are shone through the tissues from one side of the probe to the other. Then parts of the light emitted absorbed by blood and tissues. The light absorbed by the blood varies with the oxygen saturation of haemoglobin. After that, the photo-detector detects the light volume transmitted through the tissues which depends on blood pulse, Hereafter, the microprocessor calculates a value for the oxygen saturation (SpO2). The subject device is a reusable device, and need to reprocess as suggested in the user manual after each use. And the device is intended to be used on the finger, and powered by 2*1.5V AAA battery.

Here's a breakdown of the acceptance criteria and study information based on the provided text, focusing on what's available for this pulse oximeter:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

The document explicitly mentions a "Clinical testing is conducted per Annex EE Guideline for evaluating and documenting SpO2 ACCURACY in human subjects of ISO 80601-2-61:2011 Medical electrical equipment - Part 2-61: Particular requirements for basic safety and essential performance of pulse oximeter equipment."

However, the specific sample size for this clinical test set is not provided in the given text.

The data provenance (country of origin, retrospective/prospective) is not explicitly stated beyond stating it was "clinical testing... in human subjects."

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. For pulse oximetry, the "ground truth" (reference SpO2) is typically established by arterial blood gas analysis performed by trained medical personnel, but the specifics of who performed it or how many were involved in establishing the ground truth are not detailed.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not conducted or reported. This type of study is more relevant for diagnostic imaging interpretation where human readers are involved. For a pulse oximeter, the primary performance evaluation is a direct comparison to a reference standard (arterial blood gas) rather than comparing human interpretation with and without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, a standalone performance evaluation was done. The entire premise of a pulse oximeter's performance testing (as described by ISO 80601-2-61) is to assess the device's accuracy in measuring SpO2 and pulse rate independently. The "clinical testing... in human subjects" is a standalone performance evaluation against a reference standard.

7. The Type of Ground Truth Used

The ground truth used for the clinical testing of SpO2 accuracy is arterial blood gas analysis (ABG). This is inferred from the reference to "evaluating and documenting SpO2 ACCURACY in human subjects of ISO 80601-2-61:2011 Medical electrical equipment - Part 2-61," as this standard mandates ABG as the reference method for determining true arterial oxygen saturation for pulse oximeter accuracy studies.

8. The Sample Size for the Training Set

This information is not applicable and therefore not provided. Pulse oximeters are based on established biophysical principles (spectrophotometry) and do not typically use AI/machine learning models that require a "training set" in the conventional sense for their core SpO2 and pulse rate algorithms. The device's internal algorithms are based on physics and calibrated using empirical data, but this is distinct from "training data" for a machine learning model.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable as outlined in point 8.

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