Search Results

3D-SPINE has the same intended use as a predicate device called the CA-6000 Spine Motion Analyzer. 3D-SPINE however, uses a different technological methodology to achieve the same results as the CA-6000. The technology used in the 3D-SPINE is the same as that used in a second predicate device called the CP-2000 Compu-Plotter, a 3D contour plotting and data gathering device. 3D-SPINE combines and produces the desired indications of the CA-6000 by using the superior features of the electromagnetic tracking principle used in the CP-2000.

3D-SPINE™ has been developed by Skill Technologies, Inc. as a motion measuring device. 3D-SPINE™ is a real-time three-dimensional motion analysis system that tracks, quantifies, displays and documents the motion of the spine, dynamically, accurately, instantaneously and in three-dimensions. The dynamic tests performed are; extension/flexion, lateral bending and rotation, of the cervical, thoracic, thoracolumbar and lumbar spine.

It has been designed to measure and monitor the three-dimensional angular movement of the human spine. It uses a transmitter to set up a low frequency electromagnetic field, up to a radius of 5 feet from the transmitter. Passive receivers, when brought into range of the transmitter will detect the orientation of the field and the field strength. The receivers will then report x, y and z coordinates, and pitch, yaw and roll angles at a rate of 60 samples per second to a PC computer then displays the information in the form of 3D models of the head and spine and the anqular data in the form of graphs and tables.

Here's an analysis of the provided text regarding the 3D-SPINE device's acceptance criteria and study information:

Acceptance Criteria and Device Performance

The document doesn't explicitly state quantitative acceptance criteria in a dedicated section with thresholds. Instead, it frames "equivalence" by comparing the 3D-SPINE's features and capabilities to a predicate device, the CA-6000 Spine Motion Analyzer. The primary "acceptance" is implicitly tied to demonstrating substantial equivalence.

Table of Acceptance Criteria (Inferred from Substantial Equivalence Comparison) and Reported Device Performance

Note: The device is considered substantially equivalent despite not having acceleration, velocity, or EMG tracking, implying these were not "critical" acceptance criteria for this specific substantial equivalence claim, or that its other superior features (electromagnetic tracking) compensated.

Study Information

The document describes a validation study, but much of the specific detail commonly found in clinical studies is not present.

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

   • Sample Size: Not explicitly stated. The document mentions "the system produces reliable and accurate measurements of the head during three cervical spine tests" but does not give the number of subjects or tests.
   • Data Provenance: Not explicitly stated (e.g., country of origin). It's implied to be internal testing by Skill Technologies, Inc.
   • Retrospective or Prospective: Not explicitly stated, but the nature of testing a new device would typically imply a prospective study for validation.

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

   • Number of experts: Not mentioned.
   • Qualifications of experts: Not mentioned.
   • Adjudication method: Not mentioned (e.g., 2+1, 3+1, none). The text only says "The document, 'Validation of the 3D-SPINE Motion Analysis System for the Spine' confirmed that the system produces reliable and accurate measurements..."

3. 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 was not done. This device is a measurement system, not an AI-powered diagnostic tool requiring human interpretation. The study evaluates the device's accuracy in measuring motion, not how humans interact with an AI's output.

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

   • Yes, implicitly. The validation described is for the device (algorithm/system) itself in measuring motion. The statement "the system produces reliable and accurate measurements" suggests a standalone evaluation of the device's measurement capabilities.

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

   • Implied Ground Truth: The document states that "Test procedures and requirements were defined using the AMA guidelines as outlined in the American Medical Association -- Guides to the Evaluation of Permanent Impairment, Version 4.0 guide." This suggests that the ground truth for "accurate measurements" would be based on established biomechanical principles and potentially reference measurements or a "gold standard" system, in conformance with these AMA guidelines. However, the exact nature of this "ground truth" (e.g., mechanical jig, another highly accurate sensor) is not specified.

6. Sample size for the training set:

   • Not applicable / Not mentioned. This device is a motion analysis system, not a machine learning model that requires a "training set" in the conventional sense. Its "training" would be more akin to calibration and design validation.

7. How the ground truth for the training set was established:

   • Not applicable / Not mentioned. As this is not a machine learning model, the concept of establishing ground truth for a training set does not apply here. The device's functionality is based on electromagnetic tracking principles and mathematical calculations. "Validation" involved testing its measurement accuracy against pre-defined requirements or potentially a known standard.

Ask a specific question about this device