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The ANNE Limb Sensor is a pulse oximeter intended for continuous monitoring of functional oxygen saturation of arterial hemoglobin (SpO2), pulse rate, and skin temperature. The ANNE Limb Sensor is not intended to monitor or measure SpO2 or pulse rate while the patient undergoes significant motion or is active. The ANNE Limb Sensor communicates with compatible software applications for the display, storage, and analysis of data. The device is indicated for use as an aid to diagnosis and treatment by healthcare professionals in general care patients who are 12 years of age or older in clinical and home environments. The device is not intended for use on critical care patients.

The ANNE Limb sensor is a wearable, bio-integrated sensor that collects real-time biosignals including photoplethysmography (PPG) and temperature. The ANNE Limb sensor has on-device processing of raw data for the calculation of SpO2 and pulse rate. The sensor communicates via Bluetooth to the Sibel SDK, which may be integrated within software applications for the display and storage of data.

The provided text describes the acceptance criteria and study proving the ANNE Limb device meets these criteria, specifically for SpO2 accuracy.

1. Table of acceptance criteria and reported device performance

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

• Sample Size: n=12 healthy subjects.
• Data Provenance: The text does not explicitly state the country of origin but implies a clinical study, which is typically prospective. It mentions "Enrolled subjects had skin tones varying from Fitzpatrick 2-5, with two subjects having darker skin pigmentation (Fitzpatrick 5)", indicating a controlled and prospective enrollment.

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

Not applicable for this study. The ground truth for SpO2 accuracy was established through blood gas analysis, a direct physiological measurement, not expert consensus reading of images or other data.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

Not applicable. Ground truth was established by blood gas analysis.

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. This study focused on the ANNE Limb device's standalone performance for physiological measurements (SpO2, pulse rate, skin temperature) rather than AI assistance to human readers for interpretation.

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

Yes, the study described in section "VII. Clinical Studies" on page 4 evaluates the "SpO2 Accuracy" of the ANNE Limb device as a standalone measurement, comparing it to blood gas analysis.

7. The type of ground truth used

The ground truth for SpO2 accuracy was established by blood gas analysis.

8. The sample size for the training set

The document does not specify a training set for the current device's SpO2 accuracy evaluation. The clinical study described appears to be a validation study for the device's performance, not a training phase for a learning algorithm.

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

Not applicable, as a training set for a learning algorithm is not mentioned in the context of this specific SpO2 accuracy study. The device's SpO2 and pulse rate calculations involve on-device processing of raw PPG data, suggesting a more traditional signal processing and algorithmic approach as opposed to a deep learning model requiring a large labeled training dataset. The device leverages the "same sensor and algorithms for the calculation of SpO2, pulse rate, and skin temperature as the Limb Sensor of the predicate device, ANNE One," implying that any model training would have occurred during the development of the predicate device and is not detailed here.

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