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510(k) Data Aggregation
(297 days)
NEUROVISION MEDICAL MOTION SENSOR
The Neurovision Medical Motion Sensor is intended to detect, monitor and/or record limb movements on a physiological recorder, in adult patient sleep disorder studies, in a clinical setting.
The Neurovision Medical Motion Sensor is a disposable, multipurpose piezo accelerometer sensor configured to be self-powered (by "watch" type battery), disposable, and capable of being read by a small signal electrophysiologic monitor.
Here's a summary of the acceptance criteria and study information for the Neurovision Medical Motion Sensor, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Ability to signal gross motor movement with 2 different model EMG units | Demonstrated |
| Ability to signal gross motor movement with a standard ECG unit | Demonstrated |
| Compliance with IEC 60601-1:1988 + A1:1991 + A2:1995; EN 60601-1:1990+A1+A2+A13, UL 60601-1:2003 R4.06, CAN/CSA-C22.2 | Demonstrated |
| Comparable sensitivity to the predicate device (Gereonics Ultra-Piezo Limb Movement Sensor) for typical patient movements expected under intended use conditions | Demonstrated (based on testing submitted by the predicate for 510k review) |
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). The testing described is "Bench testing," implying laboratory-based testing rather than patient-based clinical studies with human participants.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts
Information regarding the number and qualifications of experts used to establish ground truth for the test set is not provided in the document. The testing described focuses on technical performance and comparison to a predicate device, not on expert-adjudicated clinical outcomes.
4. Adjudication Method for the Test Set
An adjudication method is not applicable/not specified as the testing described is bench testing focusing on technical performance. It doesn't involve subjective interpretation that would require expert adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size
A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done for this device. The submission focuses on substantial equivalence through bench testing.
6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done
The device is a physical sensor, not an algorithm, so a "standalone algorithm only" study is not applicable. The performance testing described is inherent to the device's function.
7. The Type of Ground Truth Used
The ground truth for the performance testing appears to be based on physical movement and established electrical signal detection. For the sensitivity comparison, it relied on the "testing submitted by the predicate for 510k review," suggesting the predicate's established performance as a benchmark.
8. The Sample Size for the Training Set
This device is a hardware sensor, not an AI/ML algorithm that requires a training set. Therefore, information regarding a "training set sample size" is not applicable/not provided.
9. How the Ground Truth for the Training Set Was Established
As the device is a hardware sensor and not an AI/ML algorithm, a "training set" and its associated ground truth establishment are not applicable.
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