(107 days)
The Proteus Patch is a miniaturized, wearable data-logger for ambulatory recording of physiological and behavioral metrics such as heart rate, activity, body angle relative to gravity, and time-stamped, patient-logged events, including events signaled by swallowing the Ingestible Sensor accessory. The Proteus Patch enables unattended data collection for clinical and research applications. The Proteus Patch may be used in any instance where quantifiable analysis of event-associated physiological and behavioral metrics is desirable.
The Proteus Patch is a body-worn sensor that collects physiological and behavioral metrics such as heart tate, activity, body angle relative to gravity, and time-stamped user-logged events generated by swallowing the Proteus Ingestible Sensor. The Ingestible Sensor is embedded inside an inactive tablet (the Pill) for ease of handling and swallowing. Once the Ingestible Sensor reaches the stomach, it activates and communicates its presence and unique identifier to the Patch stores and wirelessly sends the physiological, behavioral, event, and ingestion data to a general computing device for display.
Here's an analysis of the acceptance criteria and study information provided in the document:
1. Table of Acceptance Criteria and Reported Device Performance
The provided summary does not explicitly state formal "acceptance criteria" with specific thresholds for performance. Instead, it describes general methods for validation and testing. Therefore, the table below interprets the "acceptance criteria" as the method of validation itself rather than a numerical threshold, and the "reported device performance" as the statement of successful validation.
| Parameter | Acceptance Criteria (Method of Validation) | Reported Device Performance |
|---|---|---|
| Proteus Patch | ||
| Heart Rate | Biopotential low-frequency amplifier: Quantified by measuring R-wave frequency based on a modified Hamilton-Tompkins algorithm, tested using ANSI/AAMI EC 13 standard guidelines. | "The biopotential low-frequency amplifier was used to quantify heart rate... tested using guidelines set forth in the ANSI/AAMI EC 13 standard." (Implies successful testing). |
| Activity / Body Angle | Three-axis accelerometer: Validated against a known acceleration applied against each of its three axes. | "The three-axis accelerometer provided motion and angle relative to gravity data and was validated against a known acceleration applied against each of its three axes." (Implies successful validation). |
| Manual Event Logging | Patient activated button: Digital pulse. (No explicit validation method described beyond the mechanism). | (No explicit performance reported, but the mechanism is described). |
| Inter-electrode Impedance | Biopotential high-frequency amplifier: Digitized impedance from small auxiliary current. (No explicit validation method described beyond the mechanism). | (No explicit performance reported, but the mechanism is described). |
| Ingestible Sensor | ||
| Activation Time & Lifetime after Activation | Tested for activation time and lifetime after activation. | "The Ingestion Sensor was tested for activation time and lifetime after activation." (Implies successful testing). |
| Bio-galvanically powered ingestible circuit | Volume conduction communication. (No explicit validation method described beyond the mechanism). | (No explicit performance reported, but the mechanism is described). |
2. Sample Size Used for the Test Set and Data Provenance
The document does not provide specific sample sizes for test sets used for the individual performance validations. It mentions testing methods but not the number of subjects or items tested.
The data provenance is not specified (e.g., country of origin, retrospective/prospective). This is a non-clinical evaluation, so "patients" might not have been involved in all tests.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
This document describes technical device validation against standards or known inputs (e.g., "known acceleration"). It does not involve human expert interpretation of data to establish ground truth in the way a diagnostic AI system would. Therefore, this information is not applicable or provided.
4. Adjudication Method for the Test Set
Not applicable, as this is a technical validation against established standards and known physical inputs, not a subjective interpretation requiring expert adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size
No, an MRMC comparative effectiveness study was not done. The document states: "No additional clinical data were required to confirm substantial equivalence to predicate device." This indicates the device was cleared based on non-clinical performance and technological characteristics in comparison to a predicate, not through a study involving human readers or AI assistance.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
The performance data described (heart rate algorithm, accelerometer validation, ingestion sensor testing) are inherently "standalone" in the sense that they are assessing the device's technical capabilities without a human-in-the-loop for the primary validation. The device's overall intended use does involve data collection for clinical and research applications, implying potential future human interpretation, but the core performance described here is the device's ability to accurately log these metrics.
7. The Type of Ground Truth Used
The ground truth used for validation was primarily:
- Established industry standards: For heart rate, "guidelines set forth in the ANSI/AAMI EC 13 standard."
- Known physical inputs: For activity/body angle, "a known acceleration applied against each of its three axes."
- Device-specific measurements/specifications: For the ingestion sensor, "activation time and lifetime after activation" would be measured against the sensor's designed parameters.
8. The Sample Size for the Training Set
The document does not mention any "training set" in the context of machine learning. The device utilizes algorithms (e.g., modified Hamilton-Tompkins for R-wave frequency) that would have been developed and potentially trained previously, but the details of such training (including sample size) are not provided or relevant to this 510(k) summary, which focuses on validation rather than algorithm development.
9. How the Ground Truth for the Training Set Was Established
As no training set is discussed, this information is not provided.
§ 880.6305 Ingestible event marker.
(a)
Identification. An ingestible event marker is a prescription device used to record time-stamped, patient-logged events. The ingestible component links wirelessly through intrabody communication to an external recorder which records the date and time of ingestion as well as the unique serial number of the ingestible device.(b)
Classification. Class II (special controls). The special controls for this device are:(1) The device must be demonstrated to be biocompatible and non-toxic;
(2) Nonclinical, animal, and clinical testing must provide a reasonable assurance of safety and effectiveness, including device performance, durability, compatibility, usability (human factors testing), event recording, and proper excretion of the device;
(3) Appropriate analysis and nonclinical testing must validate electromagnetic compatibility performance, wireless performance, and electrical safety; and
(4) Labeling must include a detailed summary of the nonclinical and clinical testing pertinent to use of the device and the maximum number of daily device ingestions.