Search Results

Traus SSG10 Surgical System is an electrical appliance intended to cut, shave, bone & tissue resection, grinding, and drilling in the cranium and spine. Shaver handpiece is not intended for use in neurosurgical procedures.

Traus SSG10 Surgical System is composed of a control box, micro motor and a foot controller as an electric bone surgery machine. A signal for operating a foot controller, a handpiece, etc.., is transmitted when a power source is inputted to a control box (main body) to control functions such as rotational speed, torque and water injection amount.

It is a mechanism for puncturing, and cutting bones and human tissues through rotation and reciprocating motion by connecting handpieces and attachments to a micro motor. Three modes (Drill, Saw, Shaver) can be set, and the handpiece and attachment for each mode can be used in many surgical areas.

The provided text is a Premarket Notification (510(k)) from the FDA for the Traus SSG10 Surgical System. This type of document is for demonstrating substantial equivalence to a predicate device, not typically a detailed study proving acceptance criteria for new or innovative device features.

Therefore, the document does not contain the detailed information requested for acceptance criteria or a study proving those criteria, particularly in the context of an AI/ML medical device. The device in question is an "Electric Cranial Drill Motor," which is a traditional hardware device, not an AI/ML powered one.

Here's a breakdown of why the requested information cannot be extracted from this document:

1. A table of acceptance criteria and the reported device performance: Not provided. The document focuses on demonstrating substantial equivalence to a predicate device based on general features and safety/EMC standards, not specific performance metrics against defined acceptance criteria.
2. Sample size used for the test set and the data provenance: Not provided. Performance testing mentioned is "bench testing" to assure operation within predefined design specifications, but no details on sample size, data origin, or retrospective/prospective nature are given.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as this is not an AI/ML device requiring expert ground truth for image interpretation or diagnosis.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable for the reasons above.
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: Not applicable, as this is not an AI/ML device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is not an AI/ML device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable, as this is not an AI/ML device. Performance is assessed against engineering specifications.
8. The sample size for the training set: Not applicable, as this is not an AI/ML device.
9. How the ground truth for the training set was established: Not applicable, as this is not an AI/ML device.

Information that can be extracted or inferred from the document regarding "acceptance" in a general sense:

The "acceptance criteria" for devices seeking 510(k) clearance are primarily about demonstrating substantial equivalence to a legally marketed predicate device regarding safety and effectiveness. This is achieved by showing conformance to recognized standards and comparable performance.

Implicit Acceptance Criteria (based on 510(k) process):

Study Proving Device Meets Acceptance Criteria (as described in the document):

The "study" or evidence provided is a collection of non-clinical tests and conformance to standards, rather than a single, formal "study" with specific statistical endpoints to prove new performance claims.

• Non-clinical Performance Data:
  • (1) Electrical Safety and Electromagnetic Compatibility (EMC): Conducted according to IEC 60601-1:2005/AMD2:2020 and IEC 60601-1:2015+A1:2021. This demonstrates adherence to recognized safety standards.
  • (2) Software Verification and Validation Testing: Conducted in accordance with FDA's "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" (May 11, 2005) and IEC 62304, for a "moderate level of concern." This ensures the software operates as intended and mitigates risks.
  • (3) Performance Testing (Bench Test): This testing was performed to "assure that the SSG10 operates safely and within the predefined design specifications." The report references "performance criteria such as RPM." Although the maximum RPM (40,000rpm) is lower than the predicate (80,000rpm), the testing results reportedly showed this difference "does not raise any problems in the safety and effectiveness."
  • (4) Sterilization: Validated in conformance to ISO 17665-1:2006.
  • Biocompatibility: Materials tested and confirmed safe per ISO 10993 series (1, 5, 10, 12).

Key Takeaway: The document outlines the evidence used to support a substantial equivalence determination, focusing on compliance with established safety and performance standards for a medical device that is not an AI/ML technology. It does not contain the specific AI/ML-related study details requested.

Ask a specific question about this device