Search Results

The Maestro System is intended to hold and position laparoscopes and laparoscopic instruments during laparoscopic surgical procedures.

The Moon Maestro System is a 2-arm system which utilizes software and hardware to provide support to surgeons for manipulating and maintaining instrument position. Motors compensate for gravitational force applied to laparoscopic instruments, while surgeon control is not affected. Conventional laparoscopic tools are exclusively controlled and maneuvered by the surgeon, who grasps the handle of the surgical laparoscopic instrument and moves it freely until the instrument is brought to the desired position. Once surgeon hand force is removed, the Maestro system reverts to maintenance of the specified tool position and instrument tip location. This 510(k) is being submitted to implement design changes to the previously cleared Maestro System. The following modifications have been implemented to the Maestro System:

• · System Positioning Guidance
• · System Hold Status Indication
• Instrument Coupling
• · System Setup
• Bedside Setup Joint Control

The provided text describes a 510(k) premarket notification for the "Maestro System (REF100)". This document is an FDA clearance letter and a 510(k) summary, which outlines the device, its intended use, and a comparison to a predicate device. It also briefly mentions the types of testing performed (design verification and validation testing).

However, the document does not provide a detailed breakdown of acceptance criteria and the results of a study proving the device meets those criteria, especially in the context of an AI/human-in-the-loop system that would typically have specific performance metrics like sensitivity, specificity, or accuracy.

The Maestro System is described as a two-arm system that utilizes software and hardware to support surgeons by manipulating and maintaining instrument position in laparoscopic surgical procedures. The modifications made to the device relate to user interface, setup guidance, and instrument coupling, rather than an AI component that would perform diagnostic or interpretive tasks.

Therefore, many of the requested elements for an AI-powered device's acceptance criteria and study results (e.g., sample size for test set, data provenance, number of experts for ground truth, MRMC study, standalone performance, ground truth type, training set details) are not applicable or not present in this document, as the device is characterized as an operating table accessory with electromechanical functions, not an AI/ML diagnostic or assistive imaging system.

The document indicates that the device has undergone design verification and validation testing, which are standard for medical devices to ensure they meet their specified requirements and are safe and effective for their intended use. These tests typically focus on engineering and functional performance rather than AI-specific metrics.

Here's a breakdown based on the available information and an explanation of why other requested items are not provided:

Acceptance Criteria and Study for Maestro System (REF100)

Based on the provided 510(k) summary, the Maestro System is an electromechanical device designed to assist in laparoscopic surgery by holding and positioning instruments, effectively an accessory to an operating table. It does not appear to be an AI/ML-driven diagnostic or image analysis system. Therefore, the types of "acceptance criteria" and "study" details requested for AI systems (e.g., sensitivity, specificity, expert consensus for ground truth, MRMC studies) are not pertinent to this device's classification and described functionality.

The testing performed is primarily focused on the device's mechanical and software functions to ensure safety and effectiveness in its intended use.

1. Table of Acceptance Criteria and Reported Device Performance:

The document lists various "Testing Performed" which serve as the verification and validation activities against unstated, but implied, acceptance criteria related to engineering specifications and functional safety. It does not provide explicit numerical acceptance criteria or performance results in a table format typical for AI system performance.

2. Sample Size Used for the Test Set and Data Provenance:

• Not specified for discrete quantitative test sets in the provided summary. The testing appears to be functional and engineering-based rather than data-driven in the sense of AI model validation.
• Data Provenance: Not applicable in the context of clinical data for AI model training/testing. The "data" here refers to engineering test results.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

• Not applicable/Not specified. This device does not generate diagnostic outputs that require expert ground truth labeling in the way an AI diagnostic tool would. Testing likely involves engineers, usability experts, and potentially surgeons during cadaver or human factors testing, but not for "ground truth labeling" of imaging data.

4. Adjudication Method for the Test Set:

• Not applicable. No adjudication method for ground truth labeling is mentioned or expected for this type of device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No, not indicated. MRMC studies are typically performed for AI-assisted diagnostic tools (e.g., radiology AI) to assess the impact of AI on human reader performance. This is not pertinent to the Maestro System's described function.

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

• Partially applicable. For an electromechanical device with software, "standalone performance" refers to the device's functional operation independent of human interaction within its specified parameters (e.g., holding force, positioning accuracy). The various engineering and software verification tests (e.g., "Payload capacity," "Hold position accuracy," "Software verification") would assess various aspects of its standalone performance. The document states "Testing described in this 510(k) consisted of verification of all system input requirements and product specifications."

7. The Type of Ground Truth Used:

• Engineering specifications and functional requirements. For this type of device, "ground truth" equates to the pre-defined target values for forces, positions, response times, and the successful completion of intended actions (e.g., maintaining position, allowing easy manipulation). This is established through design validation against known physical principles and user requirements, not from clinical outcomes or expert consensus on clinical data.

8. The Sample Size for the Training Set:

• Not applicable. This device is not an AI/ML model trained on a dataset in the conventional sense. Its "training" is in the form of engineering design, calibration, and software programming.

9. How the Ground Truth for the Training Set was Established:

• Not applicable. As above, there is no "training set" for an AI model. The "ground truth" for the device's design and programming comes from engineering principles, user requirements, and clinical needs defined during the device development process.

Ask a specific question about this device

The Maestro System is intended to hold and position laparoscopic instruments during laparoscopic surgical procedures.

The Moon Maestro System utilizes software and hardware to provide support to surgeons for manipulating and maintaining instrument position. Motors compensate for gravitational force applied to laparoscopic instruments, while surgeon control is not affected. Conventional laparoscopic tools are exclusively controlled and maneuvered by the surgeon, who grasps the handle of the surgical laparoscopic instrument and moves it freely until the instrument is brought to the desired position. Once surgeon hand force is removed, the Maestro system reverts to maintenance of the specified tool position and instrument tip location.

The Moon Surgical Maestro System is a device designed to hold and position laparoscopic instruments during surgical procedures. The provided FDA 510(k) summary outlines its design, intended use, and comparison to a predicate device (ENDEX Endoscopic Positioning System K936308) to establish substantial equivalence.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list "acceptance criteria" with specific quantitative thresholds that are then directly matched with reported device performance in a single table. Instead, it describes various performance tests conducted. The "Performance Testing" section states that "All testing had passed in accordance with the pre-specified success criteria, international standards or FDA guidances." This implies that the acceptance criteria were internal to the company, based on these standards and guidances.

However, we can infer some performance aspects based on the comparison table and the performance testing section.

2. Sample Size Used for the Test Set and the Data Provenance

The document does not specify the sample size used for the various performance tests (e.g., how many units were tested for payload capacity, how many cadaver procedures were performed).

The data provenance is internal to Moon Surgical, described as "Design validation testing." No specific country of origin for the data is mentioned, nor is it explicitly stated whether the tests were retrospective or prospective, though "design validation testing" typically implies prospective testing of the device.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

The document does not specify the number of experts or their qualifications used to establish ground truth for the test set. It mentions "Cadaver testing" and "Human factors testing" which would implicitly involve experts (surgeons, medical professionals), but details are absent.

4. Adjudication Method for the Test Set

The document does not specify any formal adjudication method (e.g., 2+1, 3+1). The testing appears to be based on pre-specified success criteria and compliance with standards, implying that results were evaluated against these benchmarks.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The submission focuses on demonstrating substantial equivalence to a predicate device through technical comparison and performance testing, rather than a clinical effectiveness study involving human readers or operators and their performance with and without AI assistance. The device is a mechanical robotic assist system, not an AI diagnostic tool.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device is a system that supports surgeons, meaning it inherently has a "human-in-the-loop." Therefore, a "standalone algorithm only" performance evaluation is not applicable in the context of this device. The software's role is to maintain instrument position based on surgeon input (movements and release). Software validation was performed, but this is a component of the system's overall function, not a standalone diagnostic AI.

7. The Type of Ground Truth Used

For the performance testing, the "ground truth" would be defined by:

• Pre-specified success criteria: Internal benchmarks for how the device should perform.
• International standards or FDA guidances: Established metrics for device safety and performance.
• Engineering specifications: Design parameters for mechanical and electrical functions.
• Clinical feasibility (Cadaver testing): Demonstrating the device's ability to be used effectively in a simulated surgical environment.

8. The Sample Size for the Training Set

The document does not mention a training set in the context of machine learning or AI algorithm development. The "software validation" mentioned would refer to the validation of its control logic and functions, not typically a machine learning model trained on a dataset. The device's function as described (compensating for gravitational force, maintaining instrument position upon release) relies on electromechanical control and sensor feedback, not a learned model from a training set.

9. How the Ground Truth for the Training Set Was Established

Since a training set for machine learning is not applicable as per point 8, the method for establishing its ground truth is also not provided.

Ask a specific question about this device

The STERIS® 5085 SRT is a general surgical table with high patient weight capacity, extended width capability, and lower minimal table top elevation. The STERIS® 5085 SRT accommodates all general surgical procedures including but not limited to, cardiac and vascular, endoscopic, gynecology, urology, nephrectomy, neurology, ophthalmologic, orthopedics and other procedures requiring intraoperative fluoroscopic C-arm imaging and also supports laparoscopic surgical technique for the largest surgical patients.

The STERIS® 5085 SRT enables patient transport on hard level surfaces within the surgical suite (from pre-operative areas to the operating room and again from the operating room to post operative recovery).

The STERIS® 5085 SRT Surgical Table is a mobile, electro-hydraulically operated surgical table designed to support all general surgical procedures including cardiac and vascular, endoscopic, gynecology, urology, nephrectomy, neurology, ophthalmology and orthopedics with the addition of STERIS table accessories. The STERIS® 5085 SRT Surgical Table features powered lateral tilt, Trendelenburg / reverse Trendelenburg, Zip-Slide™ movable tabletop, and adjustable height functions. The STERIS® 5085 SRT has a patient transport feature that allows the user to transport patients to and from the surgical suite on hard level surfaces.

The provided text is a 510(k) summary for the STERIS® 5085 SRT Surgical Table, which is a medical device. This document focuses on demonstrating substantial equivalence to predicate devices and adherence to relevant safety and performance standards.

There is no study described in the provided text that defines acceptance criteria for a device's performance based on diagnostic metrics (like sensitivity, specificity, or accuracy) and then reports on how the device meets those criteria using clinical data or an AI-driven analysis.

Instead, the document primarily discusses:

• Device Name, Classification, and Predicate Devices: Identifies the device and its regulatory context.
• Description of Device and Intended Use: Explains what the device does and for whom it is intended.
• Safety and Substantial Equivalence: States that the device is substantially equivalent to predicate devices and complies with various voluntary safety standards (UL, IEC, EN/IEC, CAN/CSA). These standards relate to electrical safety, electromagnetic compatibility, usability, and specific requirements for operating tables.

The "acceptance criteria" presented are in the form of compliance with these safety and performance standards, and the "study that proves the device meets the acceptance criteria" refers to testing conducted to ensure this compliance. However, this is not a study in the context of evaluating a diagnostic or AI-powered medical device's performance against clinical ground truth.

Therefore, I cannot provide the requested information about acceptance criteria and device performance in the format of diagnostic metrics because this type of study is not presented in the provided text. The document describes compliance with engineering and safety standards, not a clinical performance study using ground truth and diagnostic metrics.

None of the specific subsections (1-9) of your request can be directly addressed from this document, as they pertain to clinical performance studies, ground truth establishment, expert adjudication, or AI performance, which are not detailed here.

Ask a specific question about this device

The OPT 80 Mobile Operating Table is designed for use during diagnostic examinations or surgical procedures to support and position a patient. It is made up of a column, movable tabletops and trolley. The tabletops allow trendelenburg, and reverse trendelenburg positioning, lateral tilting as well as back, leg and head plate movement. It has side rails for fitting additional accessories as may be required by a particular procedure. The table system is designed to hold a patient of 180 Kg. (400 Lbs.) in the positions described in the Instruction Manual and the attached Standard Equivalency Table.

The OPT 80 Mobile Operating Table is designed for use during diagnostic examinations or surgical procedures to support and position a patient. It is made up of a column, movable tabletops and trolley. The tabletops allow trendelenburg, and reverse trendelenburg positioning, lateral tilting as well as back, leg and head plate movement. It has side rails for fitting additional accessories as may be required by a particular procedure. The table system is designed to hold a patient of 180 Kg. (400 Lbs.) in the positions described in the Instruction Manual and the attached Standard Equivalency Table. There are secondary back-up operating devices to allow operation of the table should the primary control or power supply fail.

This 510(k) summary describes a mobile operating table, the OPT 80, and asserts its substantial equivalence to a predicate device (AMSCO Quantum 3080 SP, K930493). This type of submission relies on demonstrating that the new device is as safe and effective as a legally marketed predicate device, rather than requiring clinical trials to establish new performance metrics. Therefore, many of the requested details regarding acceptance criteria and study design for performance are not typically included in these types of submissions, especially for Class I devices like operating tables.

However, based on the provided text, here's what can be extracted and inferred:

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

For a Class I device like an operating table, "acceptance criteria" primarily revolve around meeting recognized industry standards and demonstrating functional equivalence to a predicate device. Performance is largely described by its features and adherence to these standards.

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

This information is not provided in the 510(k) summary. For a device like an operating table, especially a Class I device seeking substantial equivalence, formal test sets with statistical sample sizes in the clinical sense are not typically required. The "testing" primarily refers to engineering verification and validation against design specifications and relevant standards, often using a limited number of prototypes or production units. The focus is on demonstrating that the physical device functions as intended and meets the technical characteristics of the predicate, not on a clinical performance study with human subjects.

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)

This information is not provided and is not applicable in the context of this 510(k) submission for an operating table. "Ground truth" from expert panels is relevant for diagnostic or screening devices where expert judgment is needed to validate algorithm outputs. For an operating table, functionality is verified against engineering specifications and industry standards by engineers and quality control personnel.

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

This information is not provided and is not applicable. Adjudication methods are typically used in clinical studies or performance evaluations involving human interpretation (e.g., medical image analysis) where there might be disagreement among experts. For an operating table, functional tests have defined pass/fail criteria, not subjective adjudication among experts.

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

This information is not provided and is not applicable. MRMC studies are used for evaluating the impact of AI-assisted diagnostic tools on human reader performance. An operating table is a mechanical device, not an AI-powered diagnostic or assistive tool for human readers.

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

This information is not provided and is not applicable. "Standalone performance" refers to the performance of an algorithm or AI system by itself. An operating table does not have an "algorithm" in this sense.

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

The "ground truth" for an operating table's performance is its adherence to engineering specifications, recognized safety and quality standards (e.g., IEC 601-1, VDE 0750 IMQ), and direct comparison of functional and safety features to a legally marketed predicate device. There is no "ground truth" derived from expert consensus, pathology, or outcomes data in the clinical sense for this device.

8. The sample size for the training set

This information is not provided and is not applicable. "Training set" refers to data used to train AI/ML models. Since this is a mechanical operating table, it does not involve AI or machine learning, and therefore no training set is used.

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

This information is not provided and is not applicable, as there is no training set for an operating table.

Ask a specific question about this device

Devices are intended to attach boot stirrups to operating revm table rail or cysto table rail during surgical or diagnostic procedures requiring positioning and support of the patient's legs.

Not Found

The provided document is a 510(k) clearance letter from the FDA for the "Allen®, Ultra™ and SMART Sockets" devices. This document does not contain information about specific acceptance criteria or a study proving the device meets them.

The letter explicitly states:
"We have reviewed your Section 510(k) notification of intent to market the devices referenced above and we have determined these devices are substantially equivalent (for the indications for use stated in the enclosure) to devices marketed in interstate commerce prior to May 28, 1976..."

This indicates that the clearance was based on substantial equivalence to a predicate device, rather than a new study demonstrating performance against a set of acceptance criteria. For devices cleared through the 510(k) pathway via substantial equivalence, the rigorous performance studies you've requested are often not submitted to the FDA in the same way they would be for a Pre-Market Approval (PMA) pathway or a de novo classification.

Therefore, I cannot populate the table or answer the specific questions about acceptance criteria, study details, sample sizes, expert qualifications, or ground truth establishment based on the provided text. This information would typically be found in the 510(k) summary or the full submission, which is not included here.

Ask a specific question about this device

The AMSCO® Surgical Table is a mobile, electro-hydraulically operated general surgical table that provides flexible articulation and image amplification of the surgical patient.

mobile, electro-hydraulically operated general surgical table

I am sorry, but based on the provided document, I cannot answer your request. The document is an FDA 510(k) clearance letter for a surgical table and does not contain information about the acceptance criteria, study data, or performance metrics of a device, especially not those related to an AI/ML powered device. It merely states that the device is substantially equivalent to a predicate device.

Ask a specific question about this device

Ask a specific question about this device

Drager Gemina System is a nonpowered piece of durable The equipment intended to provide wall mounted physical support for medical/surgical monitoring and related equipment, storage space, and wall mounted dispensing of medical gases and electrical power required in patient care clinical settings, emergency rooms, intensive care, procedure rooms and operating rooms.

The Gemina System will be used in the same indications as other systems which provide overhead or wall mounted physical support and storage of equipment for dispensing of medical gases and electrical power.

The Gemina System is a wall mounted supply system of modular design. The individual components of this modular system are wall fixture, horizontal element, column, support tube, and equipment carrier (shelf).

column contains two large terminal plates that can be The outfitted according to the individual need with various outlets for gas supply, electricity, vacuum, communications, etc.

The provided text is a summary of safety and effectiveness for the Drager Gemina Wall-Mounted Workplace System, a non-powered device intended to provide physical support for medical equipment, storage, and dispensing of medical gases and electrical power. It does not contain information about acceptance criteria or a study proving the device meets those criteria in the way typically expected for a medical device that generates diagnostic or prognostic outputs, or measures a physiological parameter.

The document focuses on demonstrating substantial equivalence to predicate devices rather than proving specific performance metrics through a clinical study. Substantial equivalence is a regulatory pathway for class II devices in the US, where a new device is shown to be as safe and effective as a legally marketed predicate device.

Therefore, many of the requested categories (e.g., sample size, ground truth, expert qualifications, MRMC study, standalone performance) are not applicable or cannot be extracted from this type of regulatory submission.

However, I can extract information related to what constitutes "performance" and "safety" in the context of this device's intended use and the provided comparison.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of this submission as a substantial equivalence claim for a physical support system, the "acceptance criteria" are implicitly met by demonstrating equivalence to predicate devices in design, materials, function, and safety features. Performance is described in terms of its features and comparability to other marketed devices.

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. This is not a study involving a test set with patient data or performance metrics that would require a sample size. The "test" here is a comparison against predicate devices' specifications and functional descriptions. The data provenance is a regulatory filing for a device manufactured in the Federal Republic of Germany, distributed in the United States.

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" in the context of evaluating a physical support apparatus's equivalence to existing products does not involve clinical experts establishing a diagnosis or outcome. The "truth" is established by comparing the device's design, materials, and functional specifications to those of legally marketed predicate devices, which is part of the regulatory review process.

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

Not applicable. There is no test set in the conventional sense of a clinical or performance study that would require an adjudication method.

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. This device is a physical support system and does not involve AI or human readers for diagnostic interpretation.

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

Not applicable. This device does not have an "algorithm" or standalone performance in the context of diagnostic or therapeutic functions. Its "performance" is its ability to physically support equipment, deliver gases/electricity, and its safety features.

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

The "ground truth" for this regulatory submission is the specifications, features, and safety profiles of legally marketed predicate devices (DVE 4000 and Horizon Headwall System). The Gemina System's "truth" is established by demonstrating that its characteristics are substantially equivalent to these predicates.

8. The sample size for the training set

Not applicable. This is not a machine learning or data-driven device that requires a training set.

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

Not applicable. There is no training set for this type of device submission.

Ask a specific question about this device

8080 System is a piece of durable equipment The Drager DVE intended to provide ceiling mounted overhead physical support anaesthesia machines, medical/surgical monitoring and for and ceiling mounted related equipment, storage space, dispensing of medical gases and electrical power required in clinical settings, emergency rooms, intensive care, procedure rooms and operating rooms.

8080 will be used in the same indications as the DVE The DVE 4000 System and the DVE 8000/1/2 System and the Drager 8032E which provide physical support, storage space, and overhead, ceiling mounted dispensing of medical gases and electrical The DVE 4000 has previously been reviewed by FDA power. (K921297). The Drager 8000/1/2 Series System and the combined DVE 8000/1/2 with DVE 4002 have been previously reviewed by FDA (K942043). The new DVE 8080 Series will be used in indications which are the same as indications for the DVE 4000, DVE 8000, for other pendant systems currently offered for DVE 8032E and commercial distribution in the United States.

The DVE 8080 Series System is a ceiling mounted overhead supply system of modular design. The individual components of any modular system are divided into four categories: ceiling fixture, support systems, pendant head or column, and equipment carrier. The pendant column contains four terminal plates that can be outfitted according to the individual need with various outlets for gas supply, electricity, vacuum, communications, etc. Add-on terminal boxes are available. The support system consists of either a fixed vertical support tube (DVE 8080 basic version of the series) or a single (DVE 8081) support arm or two (DVE 8082) support arms. The support arms are equipped with pneumatic brakes and are available in three combinable lengths. The DVE 8080 Series System rotates laterally and is powered for up and down adjustment. The motor used in the DVE 8080 is an induction motor manufactured by Gefeg GmbH & Co KG. An equipment shelf provides for better positioning of the medical devices required and can be installed at time of purchase or added-on afterwards. Shelves are available in one standard size: 620 mm (width) by 400 mm.

This document (K961742) is a 510(k) premarket notification for a medical device called the Drager DVE 8080 System. It describes a ceiling-mounted overhead support system for medical equipment in clinical settings. The purpose of this type of submission is to demonstrate substantial equivalence to a predicate device, not to present a detailed study on performance against acceptance criteria in the way a clinical trial for a diagnostic algorithm would.

Therefore, the provided text does not contain the specific information requested about acceptance criteria, device performance studies, sample sizes, expert involvement, or statistical methods typically associated with evaluating AI/software performance.

Instead, the submission focuses on comparing the features and technical specifications of the Drager DVE 8080 Series System to existing predicate devices (DVE 8032E and ORBITER system) to demonstrate that it is substantially equivalent in terms of materials, design, and function.

Here's an analysis based on the provided text, addressing your points where possible and noting where information is absent:

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

This information is not present in the provided text. The submission focuses on demonstrating substantial equivalence to predicate devices, not on meeting specific, quantifiable acceptance criteria with a performance study. The tables provided (Table I and Table II) compare features and technical specifications of the DVE 8080 with its predicate devices, rather than showing performance against pre-defined acceptance criteria.

For example, the load-bearing capacity is mentioned: "Maximum load-bearing capacities have been established for all possible numbers and lengths of carrying arm combinations. These numbers have been derived from both UL testing and in-house testing." However, the specific numerical acceptance criteria (e.g., "must support X kg") and the exact reported performance against those criteria are not provided in a table format.

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

This information is not applicable/not present. The submission is for a physical medical device (a support system), not a diagnostic algorithm or a device that processes data in a "test set" in the computational sense. The "test set" would typically refer to data used to evaluate an algorithm's performance.

The text mentions "UL testing and in-house testing" for load-bearing capacities and electrical safety (in accordance with National Electrical Code, ANSI/NFPA), which implies physical product testing. However, details about the sample sizes for these physical tests, their origin country, or whether they were retrospective/prospective, are not provided.

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)

This information is not applicable/not present. "Ground truth" and "experts" in this context typically refer to establishing definitive diagnoses or classifications for an algorithm's evaluation data. For a physical support system, the "ground truth" would be engineering specifications and safety standards. The testing mentioned (UL, in-house) would be conducted by qualified engineers and technicians, not medical experts establishing ground truth for diagnostic images.

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

This information is not applicable/not present. Adjudication methods like 2+1 or 3+1 are used in studies involving human interpretation (e.g., interpreting medical images) where multiple readers' opinions need to be reconciled to establish a ground truth. This is not relevant for the physical device 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

This information is not applicable/not present. MRMC studies and the concept of "human readers improving with AI assistance" are relevant for performance evaluation of AI-driven diagnostic or assistive technologies. The Drager DVE 8080 System is a physical support system; it does not involve AI or human readers for diagnostic purposes.

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

This information is not applicable/not present. "Standalone" performance refers to an algorithm's performance without human intervention. As this is a physical medical device, not a software algorithm, this concept does not apply.

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

This information is not applicable in the typical sense for an AI device. For this device, the "ground truth" for safety and performance would be engineering specifications, safety standards (e.g., UL, National Electrical Code), and established functional requirements (e.g., load-bearing capacity, electrical parameters, rotational capabilities). The product's compliance with these standards and specifications is demonstrated through specific tests by organizations like UL and internal company testing.

8. The sample size for the training set

This information is not applicable/not present. "Training set" refers to data used to train a machine learning model. This device is a physical product and does not involve machine learning or AI.

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

This information is not applicable/not present. As there is no training set for an AI model, there is no ground truth established for one.

Summary regarding K961742:

The provided document describes a physical medical device (a ceiling-mounted support system for medical equipment). The information is presented as a 510(k) premarket notification, which aims to demonstrate that the new device is substantially equivalent to legally marketed predicate devices.

The type of "study" detailed is a comparison of features and technical specifications between the new device and its predicates, along with a general statement about meeting safety standards (UL testing, National Electrical Code compliance) and in-house testing for load capacity. This is distinctly different from the type of performance study (e.g., clinical trials, AI algorithm evaluation) that would generate the specific data points requested in your prompt regarding acceptance criteria, sample sizes for data, ground truth establishment, or human-in-the-loop performance.

Ask a specific question about this device

Ask a specific question about this device