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The Raisin™ Personal Monitor is a miniaturized, wearable data-logger for ambulatory recording of heart rate, activity, body angle relatively to gravity, and time-stamped, patient-logged events. The Raisin™ Personal Monitor enables unattended data collection for clinical and research applications. The Raisin™ Personal Monitor may be used in any instance where quantifiable analysis of eventassociated heart rate, activity, and body position is desirable.

The Raisin100 Personal Monitor (RPM) is a miniaturized, ambulatory, battery-operated datalogging device that is worn on the torso to record heart rate, activity, and patient-logged events. Patient-logged events can be extrinsic (e.g., dosing of a medication) or intrinsic (e.g., a symptom) and are time-stamped using a manual button on the device, in order to contextualize the physiologic measures. Subjective meaning of these events is assigned by the user. In addition to quantification of physical motion, signals from the device's accelerometer are used to determine body position relative to gravity. Electrode-to-electrode impedance is also measured to assess whether the device is attached properly to the user. RPM recorded data are transferred via Bluetooth telemetry to a general computing device for display and conversion for export to other programs. The RPM is available in two form factors to accommodate individual comfort preferences: one-piece and two-piece. The functionality, intended use, duration and location of wear, and fundamental scientific technologies are exactly the same between the two RPM form factors.

Here's a breakdown of the acceptance criteria and study information for the Raisin™ Personal Monitor, based on the provided text:

Acceptance Criteria and Device Performance

Study Information

1. Sample size used for the test set and the data provenance:

   • Heart Rate R-wave Detection (Arrhythmia Database): All 48 test files from the MIT-BIH arrhythmia database.
   • Heart Rate R-wave Detection (Clinical Setting - Various Body Locations): Data from 4 subjects (Subject 1, Subject 2, Subject 4, Subject 5) across different body locations. The provenance is not explicitly stated but implies prospective clinical data collection for these subjects.
   • Accelerometer (Clinical Validation): Data from a "representative walking test" and "a representative subject." The exact number of subjects or tests is not explicitly stated.
   • Accelerometer (Bench Validation): Not applicable for test set size as it's a bench validation with known inputs.
   • Data Provenance: The MIT-BIH arrhythmia database is a publicly available, retrospective database. Clinical data for the heart rate and accelerometer validation appears to be prospectively collected (e.g., "representative walking test," "subject 1, chest location, sitting").

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

   • Heart Rate R-wave Detection (Arrhythmia Database): Not specified in the provided text. The MIT-BIH arrhythmia database has widely accepted expert annotations, but the number and qualifications of the original annotators are not detailed here.
   • Heart Rate R-wave Detection (Clinical Setting - Various Body Locations): Not specified. The reference is to "automatically identified R-waves highlighted" against the captured ECG waveform, implying a comparison against the raw ECG, but the method for establishing the true R-wave locations for accuracy calculation (e.g., manual expert review) is not detailed.
   • Accelerometer (Bench Validation): Not applicable, as ground truth is the "known acceleration applied."
   • Accelerometer (Clinical Validation): Not specified. The "expected features" of walking would likely derive from general biomechanical understanding, not specific expert annotations for each test.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not specified in the provided text for any of the studies.

4. 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, an MRMC comparative effectiveness study involving human readers with and without AI assistance was not performed or reported. This device is primarily a data logger and not an AI-assisted diagnostic tool for human readers.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Yes, the reported performance metrics (e.g., R-wave detection accuracy, false positive rate, accelerometer linearity) are all indicative of standalone algorithm performance. The device is described as an "unattended data collection" system.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

   • Heart Rate R-wave Detection (Arrhythmia Database): R-wave locations were "annotated R-wave locations" from the MIT-BIH arrhythmia database, which typically involves expert-reviewed annotations.
   • Heart Rate R-wave Detection (Bench Testing): "Expected Results (bpm)" based on the ANSV/AAMI EC 13 standard, implying predefined reference values for specific ECG waveforms.
   • Heart Rate R-wave Detection (Clinical Setting - Various Body Locations): "Automatically identified R-waves highlighted" implies comparison against captured ECG, but the true ground truth for accuracy calculation is not explicitly stated (e.g., manual expert annotation of raw ECG).
   • Accelerometer (Bench Validation): "Known acceleration applied" (physical inputs).
   • Accelerometer (Clinical Validation): "Expected features" of movement (e.g., walking), based on general physiological understanding of movement patterns.

7. The sample size for the training set: Not specified. The studies describe validation testing but do not provide details on the training set used for developing the device's algorithms.

8. How the ground truth for the training set was established: Not specified, as training set details are not provided.

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