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This Handheld Pulse Oximeter is intended for measuring the functional oxygen saturation (SpO2) and pulse rate (PR). It is intended for spot check of SpO2, PR of adult patients in hospitals, clinics, or home. This device is not intended for continuous monitoring, use during motion or use with low perfusion.

The Handheld Pulse Oximeter is intended for use in measuring and displaying functional oxygen saturation of arterial hemoglobin (SpO2) and pulse rate (PR). The Handheld Pulse Oximeter works by applying a sensor to a pulsating arteriolar vascular bed. The sensor contains a dual light source and photo detector. The one wavelength of light source is 660 nm, which is red light; the other is 905 nm, which is Infrared light. Skin, bone, tissue, and venous vessels normally absorb a constant amount of light over time. The photodetector in finger sensor collects and converts the light into electronic signal which is proportional to the light intensity. The arteriolar bed normally pulsates and absorbs variable amounts of light during systole and diastole, as blood volume increases and decreases. The ratio of light absorbed at systole and diastole is translated into an oxygen saturation measurement. This measurement is referred to as SpO2. The Handheld Pulse Oximeter is powered by 3 AA batteries. The device mainly composed of PCB board, On/Off button, mode button, OLED&LED screen, battery compartment, and plastic shell. The Handheld Pulse Oximeter is compatible with S0010B-S sensor. The device is a spot-check Handheld Pulse Oximeter and does not include alarms. The device is not intended for life-supporting or life-sustaining.

The provided text describes the 510(k) summary for a Handheld Pulse Oximeter (WIT-S100, WIT-S300) and its substantial equivalence determination. The document primarily focuses on non-clinical and clinical performance data to support the device's accuracy and safety.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The core acceptance criteria for a pulse oximeter revolve around its accuracy in measuring functional oxygen saturation (SpO2) and pulse rate (PR). The standards cited provide these.

Note on SpO2 Accuracy Comparison: The subject device claims ±2% accuracy for SpO2 in the 70-100% range, which is better than the predicate device's ±3% for the same range. The document states this "does not raise any safety and effectiveness questions" and "conforms with ISO 80601-2-61 as the predicate."

Note on PR Accuracy Comparison: The subject device states ±3 bpm for PR accuracy, while the predicate device states ±2 bpm or ±2% (whichever is greater). The document acknowledges the "larger PR accuracy" of the subject device but states it "has been verified according to declared range and accuracy" and "does not raise any safety and effectiveness questions." This implies the declared ±3 bpm is acceptable and verified.

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

• Sample Size for Test Set: 12 human adult volunteers.
• Data Provenance: The text states, "Clinical hypoxia test results were obtained in 12 human adult volunteers..." and "The 12 subjects are health adult, and come from Africa(3), Caucasian(5)&Asian(4) which include Medium, light &dark race." This indicates the data is prospective and collected from a diverse group of subjects, likely within a clinical setting, though the specific country of origin is not explicitly stated beyond the racial/ethnic representation. It is a clinical study.

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

The text does not explicitly state the number of experts or their qualifications. However, for a pulse oximeter accuracy study, the "ground truth" for oxygen saturation (SaO2) is typically established by laboratory co-oximetry, which is considered the gold standard. The text mentions "arterial oxygen saturation (SaO2) as determined by co-oximetry," implying that the ground truth was established by this objective method, not by expert consensus readings of, for example, medical images.

4. Adjudication Method for the Test Set

Not applicable. This type of study for a pulse oximeter (clinical hypoxia study) does not involve human readers interpreting data that would require an adjudication method. The ground truth is established directly through objective measurements (co-oximetry).

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

No, an MRMC comparative effectiveness study was not done. This type of study is more common for diagnostic imaging AI devices where human readers interpret medical images. For a pulse oximeter, the study focuses on the device's accuracy against a known physiological standard.

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

While "algorithm only" isn't the precise term for a pulse oximeter's core function, the clinical study primarily assesses the device's accuracy in measuring SpO2 and PR independently against the co-oximetry standard. There isn't a human-in-the-loop component being evaluated in the same way as an AI diagnostic tool. The device itself performs the measurement. Therefore, in essence, the "standalone" performance of the hardware and its embedded algorithm is being assessed.

7. The Type of Ground Truth Used

The ground truth used was outcomes data / objective physiological measurements, specifically arterial oxygen saturation (SaO2) as determined by co-oximetry. Co-oximetry is considered the clinical gold standard for measuring oxygen saturation in blood.

8. The Sample Size for the Training Set

The document does not explicitly mention a training set sample size. This is common for traditional medical devices like pulse oximeters, which are based on established physiological principles and signal processing, rather than deep learning AI models that require large structured training datasets. The "development" and "calibration" process for such a device is typically part of engineering and testing, not a separate "training set" in the machine learning sense.

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

As no explicit "training set" is mentioned in the context of machine learning, the question of its ground truth establishment is not directly applicable. The device's underlying principles and calibration would be based on physiological studies and engineering benchmarks, but not a distinct "training set" with established ground truth as seen in AI/ML validation.

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