K Number
K080261
Date Cleared
2008-04-11

(70 days)

Product Code
Regulation Number
N/A
Panel
PM
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Impulse iQ Adjusting Instrument is intended for chiropractic adjustment, mobilization, or manipulation of the musculoskeletal joints of the spine and/or extremities, or for soft-tissue musculoskeletal mobilization by a licensed health care professional only. For external use only.

Device Description

The Impulse iQ Adjusting Instrument is a hand-held electromechanical chiropractic adjusting instrument. The device has three force settings (low, medium, high), a preload-control indicator light that turns from red to green upon achieving the proper preload, and an internal accelerometer to provide closed-loop feedback controlling thrust pulse rate. The device is only intended for use from a health care professional licensed by the law of the state that he or she practices.

AI/ML Overview

The provided text describes a 510(k) summary for the "Impulse iQ Adjusting Instrument" and the FDA's clearance letter. This document focuses on demonstrating substantial equivalence to predicate devices for regulatory clearance, not on providing a detailed clinical study demonstrating the device's efficacy against specific acceptance criteria.

Therefore, the information required to populate most of the requested sections (e.g., acceptance criteria, test set details, ground truth, MRMC study, training set) is not present in the provided text.

Here's what can be extracted based on the given document:

1. A table of acceptance criteria and the reported device performance

Acceptance Criteria (Explicitly stated)Reported Device Performance
Not explicitly stated in the document.Produces approximately 100 N, 200 N, and 400 N on its low, medium, and high force settings, respectively.
Pulse rate varies between 4-12 Hz.

Note: The document states "Performance Standards: None known established." This indicates that the device was not evaluated against predefined formal performance standards or acceptance criteria. The performance data provided are descriptive measurements of the device's output.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable/Not provided. The document describes mechanical testing of the device's force and pulse rate, not a study involving a test set of data (e.g., patient data or images).

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

Not applicable/Not provided. Ground truth establishment by experts for a test set is not relevant to the mechanical testing described.

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

Not applicable/Not provided. Adjudication methods are not relevant to the mechanical testing described.

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 device is a chiropractic adjusting instrument, not an AI-powered diagnostic or assistive technology. Therefore, an MRMC study related to human readers and AI assistance is not relevant and was not performed.

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

Not applicable. This is a mechanical chiropractic adjusting instrument, not an algorithm.

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

Not applicable/Not provided. For the mechanical performance data, the "ground truth" would be the direct measurement of force and pulse rate using calibrated equipment, not expert consensus or clinical outcomes.

8. The sample size for the training set

Not applicable/Not provided. This device does not involve machine learning or a training set.

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

Not applicable/Not provided. This device does not involve machine learning or a training set.

N/A