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"It is a motor driven, indoor and outdoor transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position."

The product is a Mobility Scooter which provides transport for the disabled and the elderly and to be used both indoors and outdoors.

This scooter is a battery powered four wheeled vehicle. It consists two Lead-acid batteries (in the battery box) with an off-board battery charger, frame, a seat, a back support, control panel (including the key switch, throttle control lever, horn button, speed adjustment dial, and the battery condition meter), two foldable handles, two rear drive wheels with motor/ e-magnetic brake components, two front wheels, anti-tip devices, an external battery charger, a control panel and a motor controller. For convenience of transportation and reduction of possible damage, the battery and the seat unit can be dismantled and separately packaged.

The front wheels of the scooter are 8 inches and the rear wheels are 9 inches.
The motor of the scooter is 24VDC,150W,4200RPM; the Lead-acid Battery is 12 V, 22 Ah, 18.7 Ah; the charger is 24V/2A.
Max. loading cannot be over than 180kg.
The maximum distance travelled with a fully charged battery is 17.5km and the maximum forward speed is 1.6m/s(5.8km/h).
Braking time is less than 2 seconds, braking distance is ≤1.0 meters.

This document is an FDA 510(k) Clearance Letter for a Mobility Scooter (MS160C). It is not an AI/ML medical device, and therefore does not contain the information typically associated with studies proving the performance of an AI/ML algorithm.

The request asks for details like "sample size used for the test set," "number of experts used to establish ground truth," "adjudication method," "MRMC comparative effectiveness study," and "standalone performance," which are specific to the evaluation of AI/ML software. This information is irrelevant to a physical device like a mobility scooter.

Therefore, I cannot provide the requested information as it is not present in the provided document. The document focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance and safety testing against established standards (ISO, IEC).

Here's why each point in your request cannot be answered based on the provided text:

1. A table of acceptance criteria and the reported device performance: While the document lists performance characteristics in "Table 2 - Performance Comparison", these are not presented as "acceptance criteria" in the sense of accuracy/sensitivity/specificity targets for an AI algorithm. Instead, they are comparisons to a predicate device and compliance with established ISO standards. I can extract performance characteristics, but not "acceptance criteria" for an AI model.
2. Sample sized used for the test set and the data provenance: Not applicable. This refers to data for an AI model. The mobility scooter underwent physical product testing.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth and expert review are for AI model validation.
4. Adjudication method: Not applicable. Adjudication is for resolving discrepancies in AI model output or expert readings.
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. MRMC studies are for evaluating AI's impact on human performance in diagnostic tasks.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This device is a physical product, not an algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable. "Ground truth" is a concept for AI model training and validation.
8. The sample size for the training set: Not applicable. This refers to data for an AI model.
9. How the ground truth for the training set was established: Not applicable. This refers to data for an AI model.

However, I can extract information related to the device's performance testing based on the provided document:

Study that proves the device meets requirements (Non-Clinical Testing):

The study was a series of non-clinical tests conducted to verify that the proposed device (Mobility Scooter MS160C) met all design specifications and was substantially equivalent (SE) to the predicate device (Mobility Scooter Model: W3468, K220207).

1. Table of Acceptance Criteria (as reported performance against standards, not AI-specific criteria) and the Reported Device Performance:

The document describes compliance with various ISO and IEC standards as the basis for demonstrating safety and effectiveness. The "acceptance criteria" are implied by adherence to these standards, and the "reported performance" is demonstrated by the test results confirming this compliance.

Key Performance Characteristics (from Table 2 - Performance Comparison):

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

• Sample Size: The document does not specify the number of units tested. For physical device performance testing against standards, it's common to test a representative number of units, but this specific number is not provided in the summary.
• Data Provenance: The tests are non-clinical, meaning they were conducted in a laboratory or controlled setting, presumably as part of the manufacturer's (Suzhou Master Machinery Manufacturing Co., Ltd., China) quality assurance and regulatory submission process. There is no mention of data from human subjects or specific geographical origin for "data provenance" in the sense of patient data.

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 a physical device, not an AI/ML algorithm requiring expert ground truth for diagnostic or similar tasks. The "ground truth" for the device's performance is established by objective measurements against international standards.

4. Adjudication method:

• Not applicable for a physical medical device.

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 type of study is specific to AI/ML devices interacting with human interpreters.

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

• Not applicable. This is a physical mobility scooter, not an algorithm.

7. The type of ground truth used:

• The "ground truth" for the mobility scooter's performance is established by objective measurements and conformance to international performance, safety, and quality standards (e.g., ISO 7176 series, IEC 60601-1-2, ISO 10993 series). This is not an "expert consensus" or "pathology" in the AI/ML context.

8. The sample size for the training set:

• Not applicable. This device is not an AI/ML algorithm that requires a training set.

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

• Not applicable.

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It is a motor driven, indoor and outdoor transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position.

The subject device, Model MS160A scooter is mainly battery-powered and driven by a DC motor, with the speed adjusted by a user-controlled panel.

The motor is driven, and the speed is adjusted by a user-controlled panel and speed knob.

The scooter consists of two folding armrests, a seat cushion, a folding frame, two front wheels, two rear drive wheels with a motor/electromagnetic brake assembly, a rechargeable lithium-ion battery, an off-board battery charger, a control panel, and a motor controller.

The MS160A scooter is designed to provide mobility for people limited to those who walk unchanged or for the elderly.

Folding design: Pull out the seat and backrest fixing pins, push the backrest forward, the seat and backrest fold into each other, release the handlebar locking knob, push the handlebar backward, the handlebar folds down, the whole scooter is folded.

Control panel: Includes speed knob, battery gauge, power key switch, horn button, throttle control lever, headlight switch, charger port, fuse.

Wheel and frame connection method: the motor is connected to the differential, the differential is connected to the frame, the wheels are mounted on both ends of the differential, the motor rotates with the differential, thus driving the scooter.

Frame design:

1. The frame of MS160A is aluminum alloy.
2. The folding mechanism is operated in two ways:
   a. In the non-riding state, pull out the seat fixing pin, push the backrest forward, the seat and backrest can be folded.
   b. Loosen the handlebar locking knob, push the handlebar forward, the handlebar will fold down.

The front wheels of the scooter are 7 inches and the rear wheels are 10 inches.

The motor of the scooter is ST-62D24-120W; the lithium-ion battery is 25.55V 10.4AH; the charger is 24V/2A.

Max. loading cannot be over than 125kg.

The maximum distance travelled with a fully charged battery is 8.2km and the maximum forward speed is 1.8m/s.

Braking time is about 2 seconds, braking distance is ≤1.5 meters.

The provided document (K242982 510(k) Summary for the Mobility Scooter (MS160A)) is a premarket notification to the FDA for a Mobility Scooter. This type of device is a physical product and not typically associated with AI/ML software or studies involving ground truth establishment by experts, multi-reader multi-case (MRMC) comparative effectiveness studies, or standalone algorithm performance.

Therefore, this document does not contain the information requested regarding acceptance criteria and study proving device meets acceptance criteria related to AI/ML product performance. The studies mentioned primarily confirm the device's compliance with physical safety and performance standards (e.g., ISO 7176 series for wheelchairs, biocompatibility).

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

• Device Type: A mobility scooter is a mechanical device, not imaging or diagnostic software that would rely on AI/ML algorithms to generate results requiring expert consensus or ground truth establishment.
• Study Types: The "non-clinical testing" section details adherence to established ISO standards for physical characteristics like stability, braking, dimensions, and biocompatibility. There is explicitly "No clinical study implemented for the scooter."
• Acceptance Criteria: The "acceptance criteria" for this device are its ability to meet the performance specifications outlined in the ISO standards, and to be "substantially equivalent" to a predicate device based on physical and functional comparisons. These are not acceptance criteria for AI model performance metrics like sensitivity, specificity, or AUC, which would be relevant for devices that interpret data or images.
• Ground Truth, Experts, Sample Sizes (for AI/ML): These concepts are entirely absent because they are not applicable to the type of device being submitted.

In summary, the provided document is for a physical medical device (mobility scooter) and does not involve AI/ML components or related performance studies that would utilize the concepts of ground truth, expert review, or statistical metrics like sensitivity/specificity for algorithm output.

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The SDJMASTERVISION (fluoroxyfocon A) Rigid Gas Permeable Contact Lenses are indicated for daily wear for the correction of refractive error (myopia, hyperopia, presbyopia and/or astigmatism) in aphakic and non-aphakic persons with non-diseased eyes. The lenses may be prescribed for daily wear in otherwise non-diseased eyes that require a rigid contact lens for the management of irregular corneal conditions such as keratoconus, pellucid marginal degeneration, or following penetrating keratoplasty or refractive (e.g., LASIK) surgery.

The SDJMASTERVISION (fluoroxyfocon A) Rigid Gas Permeable Contact Lenses are also indicated for therapeutic use in eyes with ocular surface disease (e.g. ocular Graft-versus-Host disease, Sjögren's syndrome, dry eye syndrome and Filamentary Keratitis), limbal stem cell deficiency (e.g. Stevens-Johnson syndrome, chemical radiation and thermal burns), disorders of the skin (e.g. atopy, ectodermal dysplasia), neurotrophic keratitis (e.g. Herpes simplex, Herpes zoster, Familial Dysautonomia), and corneal exposure (e.g. anatomic, paralytic) that might benefit from the presence of an expanded tear reservoir and protection against an adverse environment. When prescribed for therapeutic use for a distorted cornea or ocular surface disease, the lens may concurrently provide correction of refractive error.

The SDJMASTERVISION (fluoroxyfocon A) Rigid Gas Permeable Contact Lenses may be cleaned and disinfected using a chemical (not heat) lens care system.

The SDJMASTERVISION (fluoroxyfocon A) Rigid Gas Permeable Contact Lenses are manufactured from machine latheable rigid gas permeable materials composed of siloxanyl fluoromethacrylate copolymers that are tinted for visibility and available with or without an ultraviolet (UV) light absorber.

The SDJMASTERVISION (fluoroxyfocon A) Rigid Gas Permeable Contact Lenses for daily wear are made available in spherical, toric, multifocal, scleral and aspheric designs in the following lens parameters:

This is an FDA 510(k) summary for a rigid gas permeable contact lens. The document focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than proving performance against predefined acceptance criteria for a novel device through clinical trials. Therefore, much of the information you requested regarding acceptance criteria and study details (like sample size for test sets, expert ground truth, MRMC studies, training set details) is not applicable to this type of submission.

Here's a breakdown of what is available in the document related to acceptance criteria and performance, and why other elements are absent:

Context: This 510(k) submission is for the SDJMASTERVISION (fluoroxyfocon A) Rigid Gas Permeable Contact Lenses. The manufacturer is not introducing a new type of device or technology but is demonstrating that their product is "substantially equivalent" to existing, legally marketed predicate devices. For this type of submission, extensive clinical studies and a complex acceptance criteria framework (as would be seen for a novel AI device, for example) are generally not required. The focus is on demonstrating that the new device has the same intended use, technological characteristics, and performs as safely and effectively as the predicate devices.

Acceptance Criteria and Device Performance (as evident from the document):

The acceptance criteria are implicitly based on demonstrating that the device's physical properties and manufacturing quality fall within acceptable ranges and meet the standards set by the predicate devices and relevant industry standards (like ANSI Z80.20 for lens specifications).

1. In-Vitro Cytotoxicity
2. Systemic Toxicity
3. Acute Ocular Irritation | 1. In-Vitro Cytotoxicity: Per ISO 10993-5, results indicated that the finished lenses are not cytotoxic.
4. Systemic Toxicity: Per ISO 10993-11, the finished lenses met the requirements of the systemic injection test, and extracts did not induce acute systemic toxicity.
5. Acute Ocular Irritation: Per ISO 10993-23, extracts did not induce ocular irritation. |
   | Physical Properties (Matching Predicate and Industry Standards) | Specific values are listed, demonstrating they are within typical ranges for such lenses and comparable to predicate devices:

• Refractive Index: 1.430
• Modulus (MPa): 1194
• Hardness (Shore D): 78
• Specific Gravity: 1.18
• Oxygen Permeability (Dk): 200 x 10-11 (cm²/sec) (ml O₂/ml x mm Hg @ 35°C)
• Water Content:

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It is a motor driven, indoor and outdoor transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position.

This Electric Wheelchairs, modes!: MP201C, is a motor driven, indoor and outdoor transportation vehicle, which a device for assisting action handicapped people and disabled people to move. It is suitable for disabled people with mobility difficulties and elderly people.

The device consists of front wheel, drive wheel, frame, controller, motor, armrest, backrest, seat cushion, seatbelt, pedal, battery box and charger.

The device is powered by Li-ion Battery pack with 24 Km range, which can be recharged by an offboard battery charger that can be plugged into an AC socket outlet (100-240V. 50/60Hz) when the device is not in use.

The patient can activate the controller handle (joystick) to control the speed and direction of the wheelchair movement. In addition, when the patient releases the joystick, the joystick will return back to the central position and the wheelchair will be automatically stopped soon due to automatic electromagnetic brake system. Once the joystick is activated again move to other position, the wheelchair will be re-energized.

This document details the 510(k) premarket notification for an Electric Wheelchair (models MP201C, MP201L), asserting its substantial equivalence to a predicate device (K220747). The acceptance criteria and the study proving the device meets these criteria are primarily based on non-clinical testing against a series of ISO 7176, ISO 10993, and IEC 60601 standards.

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

The acceptance criteria are established by the adherence to various international standards for wheelchairs and medical devices. The reported device performance is indicated by the statement that the test results "meet its design specification" or "comply with the following standards."

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

The document does not explicitly state the sample size for non-clinical tests. It refers to various ISO and IEC standards, implying that the test samples and methods prescribed by these standards were followed. The provenance of the data is not specified in terms of country of origin but is implicitly derived from tests conducted by the manufacturer, Suzhou Master Machinery Manufacturing Co., Ltd. (China). The tests outlined are non-clinical, likely prospective in nature as they involve testing the physical device against performance standards.

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. The ground truth for performance is established by the defined parameters and methodologies within the cited ISO and IEC standards, which are internationally recognized. The compliance of the device with these standards is verified through testing.

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

This information is not applicable to non-clinical device performance testing against established standards. The tests are designed to objectively measure specific parameters.

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 such study was conducted, as this is a physical medical device (electric wheelchair) and not an AI-assisted diagnostic or interpretative tool that would involve human readers.

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

This question is not applicable. The device is an electric wheelchair, not an algorithm.

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

The ground truth for the non-clinical tests is based on pre-defined specifications and international performance standards (ISO, IEC). These standards establish objective metrics and test methods for evaluating the safety and effectiveness of wheelchairs. For example, for "Braking distance $\leq$ 1.5 m," the ground truth is the specified maximum allowed distance according to relevant standards.

8. The sample size for the training set

This is not applicable as this is a physical medical device, not a machine learning or AI model that requires a training set.

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

This is not applicable, as there is no training set for this device.

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It is a motor driven, indoor and outdoor transportation vehicle with the intended use to provide mobility to a disabled or elderly person limited to a seated position.

The subject device, Model HS186B Mobility Scooter, is an indoor/outdoor electric scooter that is intended to be used by individuals that are able to walk but suffer from mobility limitations. It has a base with frame, two front wheels, two rear wheels, two anti-tip wheels, a seat, a tiller, a control panel, an electric motor, an electromagnetic brake, a rechargeable Lithium-lon Battery with a charger. The movement of the scooter is controlled by the rider who operates the throttle Control Lever, speed knob and hand grips. The device is installed with an electromagnetic brake that will engage automatically when the scooter is not in use and the brake cannot be used manually. The Scooter is suitable for use indoors and on flat roads near buildings.

The provided text is a 510(k) summary for a medical device (HS186B Scooter) and an FDA clearance letter. It details a comparison between the proposed device and a predicate device, focusing on non-clinical testing and safety features to demonstrate substantial equivalence. However, it does not describe acceptance criteria for an AI device or a study involving AI performance metrics.

Therefore, I cannot fulfill your request for:

• A table of acceptance criteria and reported device performance for an AI device.
• Sample size used for the test set and data provenance for an AI device.
• Number of experts and their qualifications for establishing ground truth for an AI test set.
• Adjudication method for an AI test set.
• MRMC comparative effectiveness study results (AI improvement vs. without AI assistance).
• Standalone AI performance.
• Type of ground truth used for AI.
• Sample size for AI training set.
• How ground truth for AI training set was established.

This document pertains to a physical medical device (a motorized scooter) and its performance is evaluated against ISO standards and through comparison with a predicate device, not through AI-specific metrics. The "Non-Clinical Testing" section describes adherence to various ISO standards relevant to wheelchairs and scooters, and a "Biocompatibility" assessment. The document explicitly states "No clinical study implemented for the scooter." It does not mention any AI components or related studies.

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Disposable Powder Free Polyethylene Examination Gloves are powder free and non-sterile disposable devices intended for medical purposes that are worn on the examiner's hand or finger to prevent contamination between patient and examiner.

The Disposable Powder Free Polyethylene Examination Gloves are non-sterile disposable patient examination glove. The gloves are made of translucent (clear), low density polyethylene material and are powder free. The Disposable Powder Free Polyethylene Examination Gloves come in four sizes: Small, Medium, Large, X Large. The Disposable Powder Free Polyethylene Examination Gloves act as a barrier to prevent contamination between patient and examiner. The physical and performance characteristics of the device meets all requirements of ASTM D5250 and ASTM D5151.

This document is a 510(k) Premarket Notification for Disposable Powder Free Polyethylene Examination Gloves, seeking substantial equivalence to a predicate device. As such, the presented information pertains to the performance testing of these physical medical gloves, not an AI/software device. Therefore, many of the requested categories related to AI/software performance (e.g., ground truth, expert adjudication, MRMC studies) are not applicable.

Here's an analysis of the provided text in relation to the prompt:

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

2. Sample sizes used for the test set and the data provenance:

• The document does not explicitly state the exact sample sizes (number of gloves) used for each specific test (e.g., how many gloves were tested for pinholes, how many for tensile strength).
• The data provenance is from non-clinical tests performed by a qualified test center on the manufactured gloves. The country of origin of the data is not explicitly stated, but the applicant company is Mastermax Plastic (Huizhou) LTD in China. The tests are "retrospective" in the sense that they were performed on product samples, not a prospective clinical trial.

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

• This question is not applicable as the document describes performance testing for physical medical gloves, not an AI/software device that requires human expert interpretation or ground truth establishment in the traditional sense for a test set. The "ground truth" here is the physical measurement or biological response according to established international standards (ASTM, ISO).

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

• This question is not applicable. Adjudication methods are typically relevant for human interpretation or consensus in AI/software performance studies. The testing described involves objective measurements against predefined criteria.

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 question is not applicable. The device is a physical product (examination gloves), not an AI-assisted diagnostic tool.

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

• This question is not applicable. The device is a physical product.

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

• For this physical device, the "ground truth" is established by adherence to internationally recognized performance standards and their specified test methodologies. These standards (ASTM International, ISO) define precise measurements and acceptable ranges for physical properties (dimensions, tensile strength, elongation, powder residual, freedom from pinholes) and biocompatibility (cytotoxicity, irritation, sensitization).

8. The sample size for the training set:

• This question is not applicable. There is no "training set" as this is not an AI/machine learning device. The product undergoes manufacturing quality control and subsequent batch testing against established specifications.

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

• This question is not applicable for the same reason as point 8.

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The N95 Particulate Respirator (MF01) is single-use, disposable device, provided non-sterile, and are intended to be worn by operating room personnel or other healthcare workers to protect and operating room personnel from the transfer of microorganisms, body fluids, and particulate material.

The N95 particulate respirator (Model MF-01) is NIOSH certified (TC-84A-7697), pouched-shaped respirators when worn. The flat-folded respirator is composed of four layers-inner layer, filter (2 layers) and outer layer. The four layers are combined via ultrasonically welded. The respirator also contains a nose-piece enclosed in a binding tape welding the top edge to conform to the contours of the face. The respirator contains straps to secure the respirator in place on the wearer. The respirator is offered in white. The respirator is provided non-sterile and for single use only.

This document is a 510(k) Premarket Notification for a Master-Frank N95 Particulate Respirator. It focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a study of diagnostic AI. Thus, much of the requested information (like sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, standalone algorithm performance, and ground truth types for AI models) is not applicable or present in this document.

However, I can extract the acceptance criteria and reported device performance from the "Non-Clinical Performance Data" and "Performance testing" sections, which are focused on the physical performance and biocompatibility of the respirator.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

The document does not specify exact sample sizes for each of the biocompatibility and physical performance tests. It refers to established standards (e.g., ISO 10993, ASTM F1862, 16 CFR 1610, NIOSH certification), which would have their own specified sample sizes. The data provenance is from tests conducted on the Master-Frank N95 Particulate Respirator (Model MF-01) by accredited labs for NIOSH certification and other standards. The document doesn't specify the country of origin of the testing data itself, but the manufacturer is based in China. The data is prospective as it pertains to the device being submitted for clearance.

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

Not applicable in the context of this device clearance. The "ground truth" for these tests is defined by the objective measurement criteria within the specified international standards and NIOSH certification protocols. These tests are conducted by trained technicians in certified laboratories, following stringent procedures rather than subjective expert interpretation.

4. Adjudication method for the test set

Not applicable. The tests performed are objective, quantitative measurements following standardized protocols (e.g., measuring filter efficiency, fluid penetration, flame spread). There is no "adjudication" in the sense of reconciling differing expert opinions. The results are either "pass" or "fail" against defined thresholds.

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 document is for the clearance of an N95 particulate respirator, not an AI-powered diagnostic device. Therefore, no MRMC study involving human readers or AI assistance was performed or reported.

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

Not applicable. This device is a physical respirator, not an algorithm.

7. The type of ground truth used

The "ground truth" for the performance claims of the N95 respirator is based on objective, standardized physical and biocompatibility testing criteria. Examples include:

• Physical Measurements: Filtration efficiency (% of particles filtered), differential pressure (airflow resistance), fluid penetration (absence of synthetic blood penetration at a given pressure), and flame spread time.
• Biocompatibility Assessments: Observational and analytical results from in vitro cytotoxicity assays, irritation tests (e.g., skin irritation), and sensitization tests (e.g., skin sensitization) performed according to ISO 10993 standards.

These are verifiable, objective measures against international standards and regulatory requirements.

8. The sample size for the training set

Not applicable. There is no training set as this is not an AI/machine learning device. The device is a physical product designed and manufactured to meet specific performance standards.

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

Not applicable. As there is no training set for an AI model, the concept of establishing ground truth for a training set does not apply here. The device's performance is established through direct physical and biological testing against predefined standards.

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The Apex Dental Sensors is intended to be used for a radiographic examination by a dental professional to assist in the diagnosing of diseases of the teeth, jaw and oral structures.

The Apex Dental Sensors is an electronic medical device used to acquire intra-oral radiographic images. The sensor can be operated by Radiologists, Dental Assistants and other healthcare professionals, who are both trained and competent to take Dental X-ray radiographs. Intra-oral positioning of the sensor is accomplished by the use of dedicated intra-oral positioning devices that facilitate the accurate alignment of the x-ray beam. The sensor may also be aligned with the assistance of the patient. The Apex Dental Sensors is an indirect light converting digital x-ray detector. A scintillating device composed of Cesium Iodide (Csl) converts incident x-rays into visible light that is optically coupled to a light detection imager based on CMOS technology. The Apex Dental Sensors allow for automatic detection of such incident x-rays in order to generate data. Software interprets this data into images used for dental applications. The Apex Dental Sensors support USB 2.0 direct connectivity to personal computers and or laptops with dedicated electronics and a sensor software driver. The subject device does not control the generator, it is only a receiver. The X-ray system and the software used are not a part of this submission.

The provided document is a 510(k) premarket notification for a medical device called "Apex Dental Sensors". The purpose of this notification is to demonstrate substantial equivalence to a legally marketed predicate device, QuickRay HD Intraoral Sensor (K151926).

The document does not describe a study involving patient data, expert evaluation, or MRMC comparative effectiveness to establish the device's performance in a clinical context or against specific acceptance criteria related to diagnostic accuracy. Instead, the performance data presented focuses on engineering and safety standards to show that the new device performs equivalently to its predicate.

Therefore, many of the requested items (sample size, data provenance, number of experts, adjudication method, MRMC study, standalone performance, training set details) are not applicable or cannot be extracted from this specific 510(k) summary.

Here's a breakdown based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria provided are primarily based on equivalence to the predicate device and conformity to various engineering and safety standards. There are no clinical performance acceptance criteria (e.g., sensitivity, specificity for detecting a specific disease) reported in this document.

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

This document describes a premarket notification based on technical and performance equivalence to a predicate device and adherence to industry standards, not a clinical study with a test set of patient data. Therefore, this information is not applicable and 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)

Not applicable, as no clinical test set requiring expert ground truth establishment is described.

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

Not applicable, as no clinical test set is 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

Not applicable. This device is an intraoral digital x-ray sensor, a hardware component for image acquisition, not an AI-powered diagnostic software. Therefore, an MRMC study related to AI assistance for human readers is not relevant or described.

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

Not applicable. This is a hardware sensor, not an algorithm, so standalone AI performance is not relevant.

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

Not applicable, as no clinical study requiring ground truth is described. The "ground truth" in this context is the predicate device's established performance and the requirements of various engineering and safety standards.

8. The sample size for the training set

Not applicable. This is a hardware device; thus, there is no AI model requiring a training set.

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

Not applicable, as there is no training set for an AI model.

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The Easy•Touch disposable sterile insulin syringes are intended for injection of U100 insulin only.

The Easy.Touch insulin syringe consists of a calibrated hollow barrel which can contain the medication and the distal end of barrel is fixed with needle . The needle cannot be exchanged after assembling because needle is fixed in the barrel nozzle lumen. The plunger and gasket are the same shape as the conventional insulin syringes. The needle cap cover is intended to provide physical protection to the needle tube. The cap is color coded orange, same as equivalent insulin syringes. The syringes are available in 0.3 ml/cc, 0.5 ml/cc and 1 ml/cc sizes. They are supplied with a sterile fluid path, (EO), non-toxic, and non pyrogenic, for single use only, disposable. The devices operate on the principles of common piston syringes.

This 510(k) submission (K091474) for the Easy.Touch Insulin Syringe describes a device seeking substantial equivalence to a predicate device. The information provided focuses on the device's technical characteristics and bench testing, rather than a clinical study evaluating diagnostic performance. Therefore, many of the requested categories related to diagnostic study design or AI performance are not applicable.

Here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

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

This information is not provided in the submission. The submission references "bench tests," which typically do not involve human subjects or a "test set" in the context of diagnostic performance. These tests relate to the physical and biological properties of the device.

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

This information is not provided and is not applicable for this type of device and testing. Ground truth determination by experts is relevant for diagnostic accuracy studies.

4. Adjudication Method for the Test Set

This information is not provided and is not applicable. Adjudication methods are used in studies involving human interpretation or expert consensus for ground truth.

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. This device is an insulin syringe, not an AI-assisted diagnostic tool.

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. This device is not an algorithm or AI system.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

For the bench tests, the "ground truth" would be established by measurement standards and compliance with recognized industry standards and regulatory requirements for medical devices (e.g., ISO standards for sterility, biocompatibility, mechanical integrity). It's not based on expert consensus, pathology, or outcomes data in the typical sense of a diagnostic or therapeutic clinical study.

8. The Sample Size for the Training Set

This information is not provided and is not applicable. The device does not involve a "training set" as it's not a machine learning or AI algorithm.

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

This information is not provided and is not applicable.

Summary of the Study and Evidence:

The provided 510(k) summary for the Easy.Touch Insulin Syringe describes bench testing as the primary study performed to demonstrate substantial equivalence to a predicate device (Feel-ject Insulin Syringe K070917).

The study did not involve human subjects or clinical performance data in the typical sense of a diagnostic study. Instead, it focused on:

• Biocompatibility: Ensuring the materials are safe for human contact.
• Mechanical Testing: Verifying the syringe's functional integrity, such as plunger force, barrel integrity, and needle attachment.
• Sterility Testing: Confirming the device is sterile, non-toxic, and non-pyrogenic.
• EO Residues Testing: Ensuring no harmful ethylene oxide residues remain after sterilization.

The acceptance criteria for these tests would be defined by relevant national and international standards (e.g., ISO standards for medical devices) and FDA guidance for piston syringes. The reported performance is that these "tests demonstrated that the device is as safe, as effective, and performs in a substantially equivalent manner to the predicate device."

Therefore, the "study" that proves the device meets acceptance criteria is a series of bench tests evaluating the physical, chemical, and biological properties of the syringe against predetermined standards and in comparison to a legally marketed predicate device. The document implies compliance with these standards and equivalence based on the successful completion of these tests.

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1. Patients with disc protrusions.
2. Patients with mild disc herniations.
3. Patients with pinched nerves.
4. Patients with limited spinal flexibility.
5. Patients with muscle spasms.
6. Patients with spinal vertebral fixations.
7. Patients with spinal facet imbrication and fixation.
8. Patients with spinal nerve root radiculitis.
9. Patients with foraminal encroachment.

The Bass Antalgic-Trak is a multi-functional traction device. It is chair like in its appearance and The Dass Amargic Truk is a mark tull sit upon a chair or recliner. The chair/table can recline the patient 90 degrees. It maintains the patient's sitting posture during the recline. the patient 90 degrees: it maintains the parchies befores 24 inches wide by 20 inches tong by I it is seat bottom is a viry? covered assist as a seat bottom, at the knee joint, the 5 inches ticep backed by 74 men pry roomes as a calf support. The cushion continues 18 inches to support the calves. This seat-bottom section can manually rotate 80 degrees left or right, support the carves. This sout ootion socure, manually flex forward and backwards 45 degrees. manually facerary and 55 asglobal to backwards 6 inches by engaging an electric The chiller motor. This is to accommodate taller patients with longer thighs. There are 3 leather/vinyl straps that secure the patient to the seat bottom. Strap 1 securers over the iliac leather vinyl straps that secure the parent stup 3td secures over the shins. The seat back of the chair is viral 2 socures over the might is 20 inches tall and 18 inches wide and 3 inches deep Chan is villy covered done roam lead is vinyl covered dense foam. It is 12 inches tall by 8 backed with 74 men pry wood. It is mounted to the mounted to the upper portion of the chair's top frame. The headpiece has a vinyl strap to secure the forehead onto the headpiece. the chair o top the chair/table is 60 inches long. In the upright posture, the chair height is 60 which rechned, the seat-bottom is powered by an electric single-columned actuator motor. The headpiece cervical traction is powered by an electric single-columned actuator motor. The thigh extension of the seat bottom is powered by an electric single-columned actuator motor. The table/chair recline is powered by an electric single-columned actuator motor. The seat-I he table/enan footine is powered of as e cervical traction may be powered manually using foot pottom fulliour traction as foot pedal for each. The traction can be "auto" cycled using the control panel. The thigh adjustment length and table/chair recline must be engaged using the control panel. The clinician must set all functions.

This 510(k) premarket notification for the Bass Antalgic-Trak is a submission for a Class II medical device (Powered Traction Table) and as such, it focuses on demonstrating substantial equivalence to predicate devices rather than proving a device meets specific acceptance criteria through an independent study with detailed performance metrics.

Therefore, the document does not contain the information required to fill out the requested table regarding acceptance criteria and performance, nor does it describe a study that would meet the specified criteria (e.g., sample size, data provenance, expert ground truth, MRMC study, standalone performance, training set details).

This type of 510(k) summary primarily:

• Identifies the device and its manufacturer.
• States the intended use and indications for use.
• Lists predicate devices to which substantial equivalence is claimed.
• Provides a brief device description.

It does not include:

1. Acceptance criteria table or reported device performance: There are no specific quantitative acceptance criteria or performance metrics (e.g., sensitivity, specificity, accuracy, effect size) reported in this document. The submission relies on claiming equivalence to predicate devices that are already approved.
2. Sample size, data provenance for a test set: No study with a test set is described.
3. Number of experts and qualifications for ground truth: No ground truth establishment is described as there's no independent study.
4. Adjudication method: Not applicable.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: Not performed or reported. This would typically be for diagnostic or screening devices evaluating human reader performance with and without AI assistance.
6. Standalone performance: Not performed or reported. This device is a physical traction table, not a standalone algorithm.
7. Type of ground truth used: Not applicable as no new clinical study to establish performance metrics is described.
8. Sample size for training set: Not applicable as there is no AI algorithm being trained.
9. How ground truth for training set was established: Not applicable.

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