K Number
K033135
Manufacturer
Date Cleared
2004-08-09

(314 days)

Product Code
Regulation Number
876.4300
Panel
GU
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Stryker Wireless Universal Footswitch System (SWUFS) is indicated for use with compatible endoscopic and general surgery devices. It will utilize a single footswitch to selectively control multiple devices, which typically each have their own dedicated footswitch. The system includes a wireless footswitch and receiver. The SWUFS will be an accessory to and provide footswitch input control for the Stryker Total Performance System, the SERFAS (Stryker Endoscopy Radio Frequency Ablation System) consoles, and the Valleylab Electrosurgical Generator.

Device Description

The Stryker Wireless Universal Footswitch System (SWUFS) is indicated for use with compatible endoscopic and general surgery devices. It will utilize a single footswitch to selectively control multiple devices, which typically each have their own dedicated footswitch. The system includes a wireless footswitch and receiver. The SWUFS will be an accessory to and provide footswitch input control for the Stryker Total Performance System, the SERFAS (Stryker Endoscopy Radio Frequency Ablation System) consoles, and the Valleylab Electrosurgical Generator.

AI/ML Overview

This document is a 510(k) Summary of Safety and Effectiveness for the Stryker Wireless Universal Footswitch System (SWUFS). It focuses on establishing substantial equivalence to predicate devices, rather than presenting a study with specific acceptance criteria and detailed performance metrics as one might find for a novel diagnostic AI device.

Therefore, many of the requested sections regarding acceptance criteria, study design, ground truth establishment, sample sizes for test/training sets, expert adjudication, and MRMC studies are not applicable or cannot be extracted from this type of regulatory submission. The document primarily highlights adherence to voluntary safety standards and functional equivalence.

Here's an attempt to answer the questions based on the provided text, with clarifications where information is not available or relevant to a 510(k) for an accessory device:

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

This document does not present a table of specific quantitative acceptance criteria and corresponding performance metrics in the way one would for a diagnostic accuracy study. Instead, it demonstrates compliance with recognized safety and electrical standards and functional equivalence to predicate devices. The "performance" is implicitly meeting these standards and functioning as intended.

Acceptance Criteria Category (Derived from document)Reported Device Performance (Derived from document)
Electrical SafetyMeets IEC 60601-1:1988, A1:1991, A2:1995 (General Requirements for Safety)
Meets IEC 60601-1-1:2000 (Safety Requirements for Medical Electrical Systems)
Meets IEC 60601-1-2:2001 (Electromagnetic Compatibility ~ Requirements and Tests)
Meets IEC 60601-2-2:1998 (Particular Requirements for the Safety of High Frequency Surgical Equipment)
Functional EquivalenceSubstantially equivalent in safety and efficacy to Stryker Sidne™ System (K022393), Stryker SERFAS System (K991960), and Stryker Total Performance System (K991703).
Intended UseUtilizes a single footswitch to selectively control multiple compatible endoscopic and general surgery devices (Stryker Total Performance System, SERFAS consoles, Valleylab Electrosurgical Generator).
Safety ImprovementsElimination of numerous wires and multiple footswitches to improve safety and efficiency by centralizing controls, uncluttering the OR floor, and reducing set-up/clean-up time.

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

Not applicable. This is a 510(k) submission for a non-diagnostic accessory device establishing substantial equivalence, not a clinical study on a "test set" of patient data. The evaluation focused on engineering compliance and functional testing, not data-driven performance metrics on patient samples.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. Ground truth as typically defined in diagnostic AI studies (e.g., confirmed diagnosis, pathology) is not relevant for this type of device. The "ground truth" here is adherence to engineering standards and successful operation.

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

Not applicable. There was no "test set" in the context of patient data that would require expert adjudication.

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. An MRMC study is relevant for diagnostic AI devices where human readers interpret medical images or data. The SWUFS is a hardware accessory (wireless footswitch) and does not involve AI or human "readers" interpreting medical cases.

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

Not applicable. The SWUFS is a hardware device; it does not have a "standalone algorithm" performance to evaluate. Its function is to facilitate human operators' control of other medical devices.

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

Not applicable. The "ground truth" for this device's regulatory clearance is compliance with recognized voluntary standards related to electrical safety, electromagnetic compatibility, and functional equivalence to existing legally marketed devices. Its performance is verified through engineering tests to ensure it meets these standards and accurately controls the intended surgical devices.

8. The sample size for the training set

Not applicable. The SWUFS is a hardware device; it does not involve machine learning or a "training set" of data.

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

Not applicable. As there is no training set for a machine learning algorithm, there is no ground truth to establish for it.

§ 876.4300 Endoscopic electrosurgical unit and accessories.

(a)
Identification. An endoscopic electrosurgical unit and accessories is a device used to perform electrosurgical procedures through an endoscope. This generic type of device includes the electrosurgical generator, patient plate, electric biopsy forceps, electrode, flexible snare, electrosurgical alarm system, electrosurgical power supply unit, electrical clamp, self-opening rigid snare, flexible suction coagulator electrode, patient return wristlet, contact jelly, adaptor to the cord for transurethral surgical instruments, the electric cord for transurethral surgical instruments, and the transurethral desiccator.(b)
Classification. Class II (performance standards).