Search Results

The Philips disposable SpO2 sensor M1134A is indicated for use by health care professionals whenever there is a need for acquiring non-invasively the arterial oxygen sturation a support the measurement of oxygen saturation. Intended for monitoring, recording, and alarming of the physiological parameters arterial oxygen saturation (SpO2) and pulse rate of adults, infants, and neonates in a healthcare environment and during transport inside and outside of healthcare environments.

The modified device uses adhesive-free material (adhesive-free skins) which covers the optical parts of the sensor and which comes into contact with the patient. Such a modified SpO2 sensor can be applied to patients whenever skin sensitivity is a concern. The new disposable SpO2 sensors M1134A are for single use, when continuous non-invasive arterial oxygen saturation and pulse rate monitoring are required. The measurement method is based on the absorption of light, which is sent through human tissue (for example through the index finger). The light is emitted from two sources with different wavelengths and is received by a photodiode. Through interference with the human tissue the two distinct wavelengths will be differently absorbed. Out of this different absorption behavior a so-called Ratio can be calculated. Based on calibration curves, the Ratio can be related to a SpO2 value.

Here's a breakdown of the acceptance criteria and the study details for the Philips disposable SpO2 sensor M1134A, based on the provided text:

1. A table of acceptance criteria and the reported device performance

2. Sample sized used for the test set and the data provenance

• Test Set Sample Size: 12 volunteers (6 male, 6 female).
• Data Provenance: The study was conducted in a controlled environment as a "desaturation study." The country of origin is not explicitly stated, but the manufacturer is based in Germany, and the submission is to the FDA in the USA. This was a prospective study, as it involved actively collecting new data from volunteers.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not explicitly state the number of experts used or their qualifications for establishing ground truth. The primary ground truth for SpO2 accuracy was established by a CO-Oximeter as a reference, which is a gold standard for blood oxygen measurement.

4. Adjudication method for the test set

The document does not describe an adjudication method involving multiple human readers for the test set. The validation appears to rely on a direct comparison between the device's readings and the reference CO-Oximeter.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This device is a sensor for direct physiological measurement, and the study focuses on its accuracy against a reference device, not on diagnostic image interpretation by humans with or without AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, the study described is a standalone performance study of the sensor. The device itself (the SpO2 sensor) is an "algorithm only" in the sense that it mechanically measures and calculates SpO2 and pulse rate. The study assesses the accuracy of these measurements against a gold standard (CO-Oximeter) without human interpretation being the primary variable.

7. The type of ground truth used

The type of ground truth used was CO-Oximeter measurements. This is a highly accurate, direct measurement of arterial oxygen saturation and serves as the reference standard to which the SpO2 sensor's readings were compared.

8. The sample size for the training set

The document does not mention a separate "training set" in the context of machine learning. The device's accuracy is based on its fundamental measurement principle and calibration curves, which would have been developed during the device's design phase. The mentioned "more than 300 blood samples" were part of the validation study (test set) to confirm the accuracy, not for training a model.

9. How the ground truth for the training set was established

As there's no explicitly mentioned "training set" in the context of machine learning, the establishment of "ground truth for the training set" is not applicable in this document. The device's underlying principle relies on light absorption and pre-established calibration curves, which would have been developed using known SpO2 values and corresponding light absorption ratios during the initial design and development of oximetry technology. The presented study focuses on validating the final device's performance.

Ask a specific question about this device