(587 days)
The BrainPulse is intended for use on a patient's head to non-invasively detect, amplify and capture the skull motion caused by pulsatile flow from the cardiac cvcle. The BrainPulse is not indicated to aid in the diagnosis of neurological conditions, diseases, or disorders.
As described above, the BrainPulse, Model 1100 (BrainPulse) is designed to measure skull motion caused by pulsatile blood flow. The BrainPulse measures these cranial pulsatile movements via an array of accelerometers placed on the scalp. The system consists of three main components: a headset, data collector, and computer.
The headset contains a forehead photoplethysmograph (PPG) sensor that measures the patient's pulse rate, a Sound Pressure Level (SPL) sensor for detecting ambient environment noise, and six accelerometers to detect the acceleration of the skull at six selected locations. These acceleration measurements typically fall in the range of 0.001 - 0.03 g.
The data collector converts the analog signals from the headset sensors and provides a digital data stream via Ethernet cable to the computer. The computer is loaded with software that allows for the user to initiate and end recordings and to manage saved data files. The BrainPulse software is not capable of displaying the recorded data from the headset; rather the data are saved in multiple file formats that can be readily displayed using other third-party software for post-hoc review.
Here's an analysis of the acceptance criteria and the study that proves the BrainPulse, Model 1100 meets these criteria, based on the provided text.
Based on the provided text, the BrainPulse, Model 1100 is a Class II device intended to non-invasively detect, amplify, and capture skull motion caused by pulsatile flow from the cardiac cycle. It is not intended for diagnostic purposes. Therefore, the "acceptance criteria" for this device are primarily focused on its ability to accurately, precisely, stably, and repeatably measure cranial motion, and its safety, rather than diagnostic performance metrics like sensitivity, specificity, or AUC.
The information provided describes the assessment of the device against a set of standards and performance expectations, rather than a single "study" with a specific test set, ground truth, and expert adjudication as might be seen for a diagnostic AI algorithm.
1. Table of Acceptance Criteria and Reported Device Performance
Given the nature of this device (a measurement tool, not a diagnostic one), the "acceptance criteria" are derived from the "Special Controls" and the objectives of the various non-clinical and clinical performance tests.
| Acceptance Criteria Category | Specific Acceptance Criteria (from Special Controls/Test Purpose) | Reported Device Performance / Study Finding |
|---|---|---|
| I. Biocompatibility | Patient-contacting components must be demonstrated to be biocompatible (Special Control #2). | Passed: Cytotoxicity Evaluation (Non-cytotoxic), Kligman Maximization Test (Sensitization rate = 0%, grade "Weak"), Primary Skin Irritation Test (No signs of erythema or edema, Negligible Irritant), Intracutaneous Injection Test (No difference between test and control). Biocompatibility evaluation deemed adequate. |
| II. Electrical/Thermal/Mechanical Safety & EMC | Device must be designed and tested for electrical, thermal, and mechanical safety and electromagnetic compatibility (EMC) (Special Control #3). | Passed: Complied with IEC60601-1: 2005 +AM1: 2012 (Medical Electrical Equipment; Part 1: General Requirements for Safety) and IEC60601-1-2: 2007 (EMC). |
| III. Software Performance | Software hardware specifications must be provided, with V&V and hazard analysis. Software must be described in SRS/SDS, with V&V and hazard analysis (Special Control #1a, 1b). | Passed: Software consistent with 'MODERATE' level of concern. Appropriate documentation (V&V, hazard analysis) provided as part of de novo request. |
| IV. Performance Testing (Bench) | Accelerometer Measurement Stability and Repeatability: Measurements are stable within a typical recording session and repeatable across multiple sessions/operators. | Passed: All within-session recording segments demonstrated stable correlation with a baseline recording. ANOVA results did not demonstrate variation across multiple sessions or operators. |
| Accelerometer Resolution: Expected changes in acceleration are adequately resolved and above the observed noise floor. | Passed: Frequency analysis and visual inspection demonstrate signals of interest are resolved above the observed noise floor, confirming accelerometer specifications. | |
| PPG Sensor Accuracy and Precision: Device accurately and precisely measures heart rate based on changes in blood flow. | Passed: Visual comparison to concurrent SpO2 sensor recordings demonstrate adequate PPG sensor performance. | |
| Hardware Verification: Accelerometers adequately measure across the range of expected values; SPL sensor adequately measures ambient noise; Data Collector battery charges/discharges; Tablet interfaces with Data Collector and records sensor data. | Passed: Accelerometer calibration confirmed operation. Successful SPL measurement of test signals. Battery operates according to specification. Tablet passed all functional requirements. | |
| V. Clinical Performance | Clinical performance testing must demonstrate accuracy, precision, stability, and repeatability of measuring cranial motion per intended use in the intended environment (Special Control #4). | Demonstrated: 616 successful recordings from 273 patients across 6 clinical studies (4 completed/terminated, 2 ongoing). All studies demonstrated the measured skull motion correlated with a regular pulse related to the cardiac cycle. No major variations in within-patient recordings reported. Supports stability and repeatability. |
| VI. Labeling | Labeling must include intended use, instruction for technicians, and information on variability (Special Control #5). | Confirmed: User manual consistent with performance data, covers hazards and clinical information. Satisfies 21 CFR § 801.109. Includes intended use, technician instructions, and information allowing clinicians to understand potential sources of variability. |
| VII. Risk Mitigation | Risks (Adverse Tissue Reaction, Equipment Malfunction, Inaccurate Measurement, Use Error) must be mitigated. | Mitigated: Biocompatibility, Electrical/Mechanical/Thermal Safety, EMC, Clinical Performance Testing, Hardware/Software V&V, Hazard Analysis, and Labeling were used to mitigate identified risks. Probability of adverse events deemed low. |
2. Sample Size Used for the Test Set and Data Provenance
As this device is a measurement tool and not a diagnostic AI, there isn't a dedicated "test set" in the sense of a validation dataset for a diagnostic algorithm. Instead, its performance was assessed through various bench and clinical evaluations.
- Clinical Performance Data: 616 successful recordings from 273 patients across six clinical studies.
- Data Provenance: Studies were conducted "both at centers within and outside the United States." The text also mentions that summaries of these studies were "supplied to support a determination of a reasonable assurance of the safety and effectiveness." It is not specified whether these were specifically prospective or retrospective studies for the purpose of regulatory submission, but rather they appear to be existing clinical studies from which data was leveraged.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
For a device like BrainPulse, which measures a physical phenomenon (skull motion due to pulsatile flow), the concept of "ground truth" for a diagnostic outcome established by human experts is not directly applicable.
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Ground Truth for Measurement Performance: The "ground truth" for evaluating the measurement capabilities of the accelerometers and PPG sensor would have been established by:
- Reference Measurement Devices: For accelerometer resolution and SPL sensor accuracy tests, comparison to "reference measurement device" was used.
- Known Physical Inputs/Conditions: Accelerometer stability/repeatability and hardware verification would likely involve known mechanical inputs or environmental conditions to test the device's output.
- Physiological Correlation: For the PPG sensor, performance was evaluated by "visual comparison to concurrent SpO2 (blood oxygen saturation) sensor recordings." The "ground truth" here is the expected physiological correlation between blood flow and pulse.
- Clinical Correlation: In clinical studies, the "ground truth" for the device's intended function was the correlation of measured skull motion with a regular pulse related to the cardiac cycle. This is an observable physiological phenomenon.
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Experts: No specific number or qualifications of "experts" are mentioned for establishing this type of ground truth, as it relies on physical and physiological principles and comparisons to established reference measurements.
4. Adjudication Method for the Test Set
Not applicable in the context of this device's performance evaluation. Adjudication methods (e.g., 2+1, 3+1) are typically used in studies where human experts are making qualitative or subjective assessments that need to be aggregated into a "ground truth" for a diagnostic label. Here, the performance is based on quantifiable physical measurements and their correlation with physiological events.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done
No, an MRMC comparative effectiveness study was not conducted and was not necessary for this device.
- Reasoning: An MRMC study assesses the impact of AI assistance on human reader performance, typically for diagnostic tasks (e.g., radiologists reading images with or without AI). The BrainPulse is a measurement device, not a diagnostic aid that assists a human reader in interpreting complex clinical data. Its output (skull motion data) is intended to be incorporated into a clinician's overall assessment paradigm, but the device itself doesn't offer a diagnostic interpretation or classification that a human "reader" would be evaluating. The submission explicitly states: "Consequently, a demonstration of clinical diagnostic utility in specific patient populations was not required."
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was done
Yes, the core of the performance evaluation for BrainPulse, Model 1100, is essentially its standalone (algorithm/hardware-only) performance in measuring cranial motion.
- Measurement Accuracy and Reliability: The bench performance tests (accelerometer stability, repeatability, resolution, PPG accuracy, hardware verification) evaluate the device's ability to accurately and reliably capture the intended data independently.
- Clinical Correlation: The clinical studies confirmed that the device's measurements (algorithm's output) correlated with the cardiac cycle, which is its primary intended function. While clinicians use the data, the device is evaluated on its ability to produce the measurement correctly, not on a human's ability to interpret that measurement for a specific diagnostic outcome.
7. The Type of Ground Truth Used
The "ground truth" for the BrainPulse's evaluation was primarily:
- Physical/Engineering Specifications: For bench testing, this often meant comparing the device's output to known physical inputs or outputs from calibrated reference instruments (e.g., "reference measurement device" for SPL sensor, "accelerometer specifications" for resolution).
- Physiological Correlation: For the PPG sensor, the ground truth was the expected physiological correlation with SpO2 readings (though "visual comparison" suggests a qualitative assessment of this correlation rather than quantitative comparison to a gold standard).
- Observable Physiological Events: In clinical studies, the ground truth for validating the device's intended use was the "regular pulse related to the cardiac cycle," an established physiological event which the device's skull motion measurements were expected to correlate with.
- Absence of Adverse Events: Safety ground truth relied on patient reporting of discomfort or adverse events.
This is distinct from "expert consensus" or "pathology" which are typically ground truths for diagnostic tasks. Outcomes data might be relevant for clinical utility, which was explicitly not assessed.
8. The Sample Size for the Training Set
The document does not mention a training set or any machine learning (ML) or Artificial Intelligence (AI) model that would require a distinct training set. The device appears to be based on direct physical measurements using accelerometers and a PPG sensor. Its "software" is described as managing recordings and saving data, consistent with traditional software, not an ML/AI algorithm that learns from data.
If there were internal algorithms for signal processing or noise reduction, the document does not specify if these were "trained" on data or if they were designed based on known physics and engineering principles. Given the de novo nature from 2014, it's highly likely that any signal processing would be deterministic rather than AI/ML-based.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as no training set or specific ML/AI model is described.
§ 882.1630 Cranial motion measurement device.
(a)
Identification. A cranial motion measurement device is a prescription device that utilizes accelerometers to measure the motion or acceleration of the skull. These measurements are not to be used for diagnostic purposes.(b)
Classification. Class II (special controls). The special controls for this device are:(1) The technical parameters of the device, hardware and software, must be fully characterized and include the following information:
(i) Hardware specifications must be provided. Additionally, verification and validation testing as well as a hazard analysis must be performed.
(ii) Software must be described in detail in the Software Requirements Specification (SRS) and Software Design Specification (SDS). Additionally, software verification and validation testing as well as a hazard analysis must be performed.
(2) The device parts that contact the patient must be demonstrated to be biocompatible.
(3) The device must be designed and tested for electrical, thermal, and mechanical safety, and electromagnetic compatibility (EMC).
(4) Clinical performance testing must demonstrate the accuracy, precision, stability, and repeatability of measuring cranial motion per the intended use in the intended use environment.
(5) The labeling must include:
(i) The intended use population and the intended use environment.
(ii) Instructions for technicians to convey to patients regarding the collection of cranial acceleration data to ensure device measurement accuracy, precision, stability, and repeatability.
(iii) Information allowing clinicians to understand potential sources of variability in the measurement to help recognize and identify changes in the measurement.