Search Results

The C.T.M. Mobility Scooter HS-118 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-118 is an indoor/outdoor Mobility Scooter that is battery operated. It has a base with four wheels and a lightweight adjustable seat. The movement of the scooter is controlled by the rider who uses hand controls located at the top of the steering column. The device can be disassembled for transport and is provided with an off board battery charger.

The provided text is a 510(k) summary for the C.T.M. Mobility Scooter HS-118. This document focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than establishing acceptance criteria and proving performance through a study in the way a medical diagnostic AI device might.

Therefore, many of the requested categories (e.g., sample sizes for test/training sets, experts for ground truth, MRMC studies, standalone performance, specific types of ground truth) are not applicable to this type of submission.

Here's a breakdown of the information that can be extracted or deduced from the provided text, tailored to the context of this device:

Acceptance Criteria and Study for C.T.M. Mobility Scooter HS-118

The C.T.M. Mobility Scooter HS-118 sought 510(k) clearance by demonstrating "substantial equivalence" to predicate devices, namely the Go-Go Ultra X (K063389) and VCS S3T (K051131). The primary "acceptance criteria" were met by showing that its technological characteristics, intended use, and performance data were comparable to these predicates, and that any differences did not raise new questions of safety or effectiveness.

1. Table of "Acceptance Criteria" and Reported Device Performance

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

• Test Set Sample Size: Not applicable. This was a submission for a physical device, not an AI/diagnostic algorithm tested on a dataset of patient samples. The "test set" in this context refers to bench testing of the scooter itself.
• Data Provenance: Not applicable in the traditional sense of clinical data. The "data" comes from bench testing of the physical scooter and comparison of its specifications to predicate devices. The country of origin for the data generation would be where C.T.M. Homecare Product, Inc. conducted its testing, likely in China or the US given the company's address and contact. The testing was prospective in the sense that it was performed on the device being submitted for clearance.

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

• Number of Experts: Not applicable. The "ground truth" for a mechanical device like a scooter is its physical performance against established engineering and safety standards. There isn't a concept of expert consensus for labeling a case as positive or negative.
• Qualifications of Experts: Not applicable. Testing would have been conducted by engineers or technicians familiar with relevant standards (e.g., ISO, ANSI, FDA guidance).

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. There's no "test set" of cases requiring adjudication by multiple readers or experts.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The submission explicitly states: "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)." MRMC studies are typically used for diagnostic devices to assess human reader performance with and without AI assistance.

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

• Standalone Performance: Not applicable. This is a physical mobility device, not an algorithm.

7. The Type of Ground Truth Used

• Type of Ground Truth: For the "bench testing," the ground truth corresponds to accepted engineering specifications and safety standards outlined in the "Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Mechanical and Scooters, and Motorized Three Wheeled Vehicles, July 1995." Compliance with these predetermined thresholds and successful completion of the specified tests served as the "ground truth" for the device's functional and safety performance.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. There is no AI algorithm being "trained" in this context.

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

• Ground Truth for Training Set: Not applicable.

Ask a specific question about this device

The C.T.M. Mobility Scooter HS-515 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-515 is an indoor/outdoor scooter that is battery operated. It has a base with three wheels, a padded seat with adjustable armrests, and hand controls at the top of the steering column allowing the rider to control the scooter. It can be disassembled for transport and is provided with an off-board battery charger.

The provided document is a 510(k) summary for the C.T.M. Mobility Scooter HS-515. This type of submission is for medical devices that are mechanical or physical in nature, not AI/software-driven diagnostics or imaging systems. Therefore, many of the requested categories related to AI/software performance, such as sample sizes for test sets, expert ground truth, MRMC studies, and standalone algorithm performance, are not applicable to this device and its 510(k) submission.

Here's a breakdown of the available information based on your request:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria in the format typically seen for AI/software performance studies. Instead, the "acceptance criteria" are implied by compliance with established performance tests for mechanical scooters, as outlined in FDA guidance documents.

Study Information (as applicable to this device type)

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

   • N/A. This is a mechanical device. Performance testing involved physical tests on the scooter itself, not a "test set" in the data-driven sense. The document does not specify the number of units tested.
   • Data provenance: The tests were "conducted and the results included in the submission." The country of origin for the testing is not specified, but the applicant is C.T.M. Homecare Product, Inc. in Chino, CA, and the contact is in Eugene, OR.

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

   • N/A. Ground truth for a mechanical scooter primarily involves meeting engineering and safety specifications, which are assessed through direct physical testing and measurement, not expert review of data/images. The "ground truth" is adherence to established mechanical and electrical safety standards.

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

   • N/A. Adjudication methods like 2+1 or 3+1 are used for reconciling discordant expert readings in diagnostic AI/software studies. This is not relevant for a mechanical scooter.

4. 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:

   • N/A. This is a mechanical mobility scooter, not an AI-assisted diagnostic or imaging device. Therefore, no MRMC study or assessment of human reader improvement with AI assistance was conducted.

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

   • N/A. This device does not have an "algorithm" in the context of AI/software performance. It is a physical product.

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

   • For a mechanical device like a scooter, the "ground truth" for performance is based on objective measurements from engineering tests and compliance with established performance standards and safety regulations (e.g., stability, braking effectiveness, speed, battery life, weight capacity). The summary states that "Tests listed in the Guidance Document... were conducted."

7. The sample size for the training set:

   • N/A. This is a mechanical device, not an AI/software. There is no "training set" in the machine learning sense.

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

   • N/A. As there is no training set, this question is not applicable.

Ask a specific question about this device

The C.T.M. Mobility Scooter HS-528 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-528 is an indoor/outdoor scooter that is battery operated. It has a base with four wheels, a padded seat with adjustable armrests, and a steering column allowing the rider to control the scooter. It is capable of transport and is provided with an off-board battery charger.

This document is a 510(k) summary for the C.T.M. Mobility Scooter HS-528. It states that "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)." Therefore, there is no information in the provided text for acceptance criteria or specific study details proving the device meets those criteria.

However, the document does state: "Tests listed in the Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Mechanical and Scooters, and Motorized Three Wheeled Vehicles, July 1995, were conducted and the results included in the submission." This implies that the device was tested against the standards outlined in that guidance document, even if the specific results are not provided.

Without the actual study results and acceptance criteria from the guidance document, I cannot complete the table or answer most of the requested questions.

Here's a breakdown of what can be extracted and what cannot:

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

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

• Sample Size for Test Set: Not provided.
• Data Provenance: 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 or comparative performance testing was submitted, and therefore no ground truth established by experts for a test set is mentioned.

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

• Not applicable as no clinical or comparative performance testing was submitted.

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. The document explicitly states: "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)." This device is a mobility scooter, not an AI-assisted diagnostic tool, so an MRMC study is not relevant here.

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

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

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

• Not applicable as no clinical or comparative performance testing was submitted to require a ground truth. Performance would have been measured against engineering standards specified in the guidance document.

8. The sample size for the training set

• Not applicable. This is a physical device, and the testing described references compliance with guidance documents for physical product safety and performance, not machine learning model training.

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

• Not applicable for the same reasons as #8.

Ask a specific question about this device

The C.T.M. Mobility Scooter HS-628 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-628 is an indoor/outdoor scooter that is battery operated, has three wheels, a padded seat with adjustable armrests, and hand controls at the top of the steering column allowing the rider to control the scooter. It is provided with an off-board battery charger.

This document is a 510(k) premarket notification for a C.T.M. Mobility Scooter HS-628. It does not contain any information regarding acceptance criteria or a study that proves the device meets specific performance criteria in the context of an AI-driven medical device.

The document states:

• "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)."
• The device is a "C.T.M. Mobility Scooter HS-628 or Orion Electric scooter Motorized three-wheeled vehicle."
• Its intended use is to "provide transportation for a disabled or elderly person."
• The 510(k) notification focuses on demonstrating "substantial equivalence" to a predicate device (C.T.M. Mobility Scooter HS-890) based on similar technological characteristics (e.g., both are battery operated, have two wheels, one motor, automatic braking systems).
• It mentions "Tests listed in the Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Powered Wheelchairs and Scooters, and Motorized Three Wheeled Vehicles" were conducted, but the specific results or acceptance criteria are not detailed, nor are they framed as performance metrics for an AI system.

Therefore, I cannot provide the requested information for an AI-driven medical device, as this document pertains to a mobility scooter and explicitly states that comparative performance testing and clinical evaluations were not submitted. The questions you've asked are relevant for AI/ML-based medical devices or diagnostics, which this product is not.

Ask a specific question about this device

The C.T.M. Power Chair HS-1500 is an indoor/outdoor powered wheelchair that provides transportation for a disabled or elderly person.

The C.T.M. Power Chair HS-1500 is an indoor/outdoor powered wheelchair that is battery operated. It has a base with four wheels, a padded seat with adjustable armrests, and a controller attached to one armrest which allows the rider to control the movement of the chair. It can be disassembled for transport and is provided with an on-board battery charger.

This document, K073686, describes a 510(k) submission for a powered wheelchair, the C.T.M. Power Chair HS-1500. This type of device does not typically involve the kinds of studies and acceptance criteria commonly associated with AI/ML-based medical devices or diagnostic tools. Therefore, much of the requested information regarding AI/ML study design, ground truth, and expert evaluation is not applicable or available in this submission.

Here's a breakdown based on the provided text, addressing the points where information is available:

1. Table of Acceptance Criteria and Reported Device Performance

The submission states: "Tests listed in the Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Mechanical and Powered Wheelchairs, and Motorized Three Wheeled Vehicles, July 1995, were conducted and the results included in the submission."

However, the specific acceptance criteria (e.g., maximum speed, turning radius, battery life, weight capacity, stability, braking performance) and the reported performance results against these criteria are not detailed in this summary document. They would have been part of the more extensive 510(k) submission not included here.

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

This information is not provided in the summary. For a physical device like a wheelchair, "test set" would refer to the units of the product that underwent performance and safety testing. The number of units tested is not stated, nor is the provenance of the data (e.g., in-house testing, third-party lab). The testing appears to be physical performance and safety testing of the device itself, not data-driven evaluations.

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

Not applicable. For a powered wheelchair, "ground truth" would refer to established engineering standards, safety regulations, and performance specifications from the relevant guidance documents (as mentioned in the text). There isn't "ground truth" in the sense of expert annotation of medical images or other data for an AI algorithm. The performance is assessed against predefined physical and mechanical thresholds.

4. Adjudication Method for the Test Set

Not applicable. This concept pertains to resolving discrepancies in expert opinions or data labels, which is not relevant for the type of testing described for a powered wheelchair.

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

No. The submission explicitly states: "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)." MRMC studies are typically used to evaluate the impact of AI on human reader performance, which is not relevant for this device.

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

Not applicable. There is no AI algorithm being evaluated for this medical device. The device is a physical powered wheelchair.

7. The Type of Ground Truth Used

The "ground truth" implicitly used would be adherence to the safety and performance standards outlined in the "Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Mechanical and Powered Wheelchairs, and Motorized Three Wheeled Vehicles, July 1995." This would encompass physical measurements, load testing, endurance testing, braking tests, stability tests, etc. No "expert consensus," "pathology," or "outcomes data" in the typical AI context are mentioned for establishing ground truth for this device.

8. The Sample Size for the Training Set

Not applicable. This device is a physical product, not an AI/ML algorithm. There is no "training set" in the context of machine learning.

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

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

In Summary:

The K073686 submission is for a traditional medical device (a powered wheelchair) seeking substantial equivalence to a predicate device. The evaluation focuses on meeting established physical and mechanical performance standards and safety requirements rather than on the performance of a diagnostic algorithm or AI system. Therefore, most of the detailed questions regarding AI/ML study design are not addressed in this document.

Ask a specific question about this device

The C.T.M. Mobility Scooter HS-265 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-265 is an indoor/outdoor scooter that is battery operated. It has a base with three wheels, a padded seat with adjustable armrests, and hand controls at the top of the steering column which allow the rider to control the movement of the scooter. It can be disassembled for transport and is provided with an on-board battery charger.

Here's an analysis of the provided 510(k) summary regarding the C.T.M. Mobility Scooter HS-265, focusing on acceptance criteria and study details:

This document describes a mobility scooter, which is a physical device, not an AI/ML device. Therefore, the majority of the questions related to AI/ML device testing (e.g., sample size for test sets, ground truth, experts, MRMC studies, standalone performance, training set) are not applicable to this submission.

The 510(k) summary explicitly states: "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)." This indicates that the regulatory pathway relied on demonstrating "substantial equivalence" to a predicate device (C.T.M. Mobility Scooter HS-235 cleared under K032918) through technological characteristics and adherence to recognized guidance documents, rather than independent performance studies with acceptance criteria in the typical sense for AI/ML or efficacy studies.

However, I can extract the information that is present and indicate where information is missing or not applicable based on the nature of the device.

1. Table of Acceptance Criteria and Reported Device Performance

For the following questions, please note that they are largely not applicable to this type of device submission (a physical mobility scooter) and the regulatory pathway chosen (510(k) based on substantial equivalence to a predicate without new clinical or comparative performance studies beyond adherence to guidance documents).

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 (N/A). No specific "test set" in the context of AI/ML or comparative clinical performance was described. The testing mentioned refers to engineering/performance tests as outlined in a guidance document, not data-driven evaluations.

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 (N/A). Ground truth and expert consensus are irrelevant for device performance testing of a mobility scooter. The "ground truth" for a mobility scooter's safety/performance would be adherence to engineering specifications and safety standards.

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

• Not Applicable (N/A). Adjudication methods are used in clinical trials or expert label review for data, which is not described here.

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 (N/A). This is a mobility scooter, not a diagnostic AI/ML device. Therefore, MRMC studies and "human readers" are not relevant.

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

• Not Applicable (N/A). This is a physical device, not an algorithm.

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

• Not Applicable (N/A). No ground truth in the context of data labeling or clinical outcomes was used for this type of submission. The "ground truth" for device performance would be physical measurements against engineering specifications and safety standards.

8. The sample size for the training set

• Not Applicable (N/A). There is no "training set" as this is a physical product, not an AI/ML model.

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

• Not Applicable (N/A). As there is no training set, this question is not relevant.

Ask a specific question about this device

The C.T.M. Mobility Scooter HS-295 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-295 is an indoor/outdoor scooter that is battery operated. It has a base with four wheels, a padded seat with adjustable armrests, and hand controls at the top of the steering column which allow the rider to control the movement of the scooter. It can be disassembled for transport and is provided with an on-board battery charger.

The provided text is related to a 510(k) submission for a mobility scooter, which is a medical device. However, this document does not contain information about acceptance criteria or a study that proves the device meets those criteria in the context of an AI/ML medical device.

Here's why and what information is missing:

Why the provided text is not relevant to the requested information:

• Device Type: The device is a "C.T.M. Mobility Scooter HS-295," an electric scooter for transportation. This is a mechanical device, not an AI/ML software or algorithm.
• Testing Conducted: The summary explicitly states: "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)." It mentions that "Tests listed in the Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Mechanical and Scooters, and Motorized Three Wheeled Vehicles, July 1995, were conducted." This refers to standard mechanical and safety testing for such vehicles, not performance metrics for an AI/ML algorithm.
• Lack of AI/ML Specifics: There is no mention of algorithms, machine learning, deep learning, diagnostic accuracy, image analysis, or any other characteristic of an AI/ML medical device.

Therefore, I cannot provide the requested information based on the input text. The questions you've asked (about acceptance criteria for an AI/ML model, sample sizes for test/training sets, expert ground truth, MRMC studies, standalone performance, etc.) are specifically geared towards the evaluation of AI/ML software as a medical device. This document describes a physical mobility scooter.

Ask a specific question about this device

The C.T.M. Mobility Scooter HS-310 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-310 is an indoor/outdoor scooter that is battery operated. It has a base with three wheels, a padded seat with adjustable armrests, and hand controls at the top of the steering column which allow the rider to control the movement of the scooter. It can be disassembled for transport and has an on-board battery charger.

I am sorry, but based on the provided text, there is no information available regarding acceptance criteria or a study that proves the device meets specific performance criteria.

The 510(k) summary for the C.T.M. Mobility Scooter HS-310 explicitly states:

"Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)."

This indicates that the submission did not include a study designed to evaluate the device's performance against specific acceptance criteria. The clearance was based on substantial equivalence to a predicate device (C.T.M. Mobility Scooter HS-320) due to similar technological characteristics and intended use, rather than a direct performance study of the HS-310 itself.

Therefore, I cannot provide the requested information in the table or answer the specific questions about sample size, ground truth, experts, adjudication, MRMC studies, or standalone performance.

Ask a specific question about this device

The C.T.M. Power Chair HS-1000 is an indoor/outdoor powered wheelchair that provides transportation for a disabled or elderly person.

The C.T.M. Power Chair HS-1000 is an indoor/outdoor powered wheelchair that is battery operated. It has a base with four wheels, an adjustable padded seat with armrests, and a controller attached to one armrest which allows the rider to control the movement of the chair. It can be disassembled for transport and is provided with an on-board battery charger.

The provided document (K040020) is a 510(k) Pre-Market Notification for a powered wheelchair, the C.T.M. Power Chair HS-1000. For this type of device and submission, the acceptance criteria and study detailed are not typically in the format of an AI/software device evaluation. Instead, the submission focuses on demonstrating substantial equivalence to a predicate device through engineering performance testing. It does not involve AI, human readers, or medical image analysis.

However, I can extract information relevant to "performance" in the context of this device based on the available text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not specify a "sample size" in the context of individual units tested. The testing appears to have been performed on the C.T.M. Power Chair HS-1000 device itself, likely one or a few units, as part of engineering verification.
• Data Provenance: The document does not provide details on the country of origin of the data or whether it was retrospective or prospective. The testing was conducted by the submitter, C.T.M. Homecare Product, Inc. (located in Riverside, CA, USA).

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 to this 510(k) submission. "Ground truth" in the context of expert consensus is typically used for AI/diagnostic devices where human interpretation is being evaluated against an objective standard. For a powered wheelchair, the performance is assessed against technical specifications and safety standards as outlined in relevant guidance documents.

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

This information is not applicable. Adjudication methods are relevant for studies involving human reviewers or diagnostic decisions, not for the engineering performance testing of a mechanical device like a wheelchair.

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, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI or diagnostic imaging devices involving human readers. The submission explicitly states: "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)."

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

No, a standalone algorithm performance study was not done. This device is a powered wheelchair; it does not contain an algorithm that operates independently for diagnostic or interpretative tasks.

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

The "ground truth" for this device's performance is established by engineering and safety standards outlined in the "Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Mechanical and Powered Wheelchairs, and Motorized Three Wheeled Vehicles, July 1995." The device's performance parameters (e.g., braking time, speed, turning radius) are measured against criteria derived from these standards for safe and effective operation. In essence, meeting the criteria outlined in the guidance document serves as the "ground truth" for its safety and functional performance.

8. The sample size for the training set

This information is not applicable as there is no AI algorithm being developed or "trained" for this device.

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

This information is not applicable as there is no AI algorithm and therefore no training set or its associated ground truth.

Ask a specific question about this device

The C.T.M. Mobility Scooter HS-250 is an indoor/outdoor scooter that provides transportation for a disabled or elderly person.

The C.T.M. Mobility Scooter HS-250 is an indoor/outdoor electric scooter that is battery operated. It has a base with four wheels with a lightweight seat, armrests, and a front basket. The movement of the scooter is controlled by the rider who uses hand controls located at the top of the steering column. The device can be disassembled for transport and is provided with an onboard battery charger.

The provided 510(k) summary for the C.T.M. Mobility Scooter HS-250 does not include a table of acceptance criteria, detailed device performance, or a study proving that the device meets specific acceptance criteria in the way described for typical AI/ML medical devices.

Instead, this submission is for a physical medical device (a mobility scooter) and relies on a demonstration of substantial equivalence to a predicate device (C.T.M. Mobility Scooter HS-360) rather than a performance study against predefined acceptance criteria.

Here's an analysis based on the information provided, highlighting why a direct answer to your request is not possible with this type of document:

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

• Acceptance Criteria: Not explicitly stated as pass/fail metrics in the context of an AI/ML device. For this physical device, the "acceptance criteria" are implied by showing the device's technological characteristics are "very similar" to the predicate device and that it meets the "Intended Use" (providing transportation for disabled/elderly persons). The testing conducted refers generally to "Guidance Document for the Preparation of Premarket Notification [510(k)] Applications for Mechanical and Powered Wheelchairs, and Motorized Three Wheeled Vehicles, July 1995," but specific performance targets or thresholds from that document are not detailed in this summary.
• Reported Device Performance:
  • Braking distance at maximum speed: 4.67 feet
  • Minimum turning radius: approximately 35.4 inches
  • Forward speed range: 0-4.1 mph
  • Reverse speed range: 0-1.5 mph
  • Heaviest single component: 27.7 pounds
  • Total weight with batteries: approximately 107 pounds
  • Motor: 250 watt, 3800 rpm
  • Batteries: two 12-volt 12Ah batteries
  • Battery Charger: 24-volt constant current charger, plugs into 110V or 220V socket.
  • Self-diagnostic signals: 9 distinct codes for problems like battery, motor, or brake malfunctions.
    The document does not state how these performance metrics were tested or what thresholds they had to meet. They are presented as characteristics of the device.

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

• Sample Size: Not applicable. This is a physical device, and the "testing" involved verifying its mechanical and electrical characteristics, likely in a laboratory or engineering testing environment, rather than a clinical study with a "test set" of patient data.
• Data Provenance: Not applicable for a typical AI/ML "test set." The testing was likely internal by the manufacturer following industry guidance for mobility devices.

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

• Not applicable. Ground truth, in the context of AI/ML, refers to validated data labels. For this physical device, "ground truth" would relate to engineering specifications and safety standards, which are typically established by engineers and regulatory bodies, not clinical experts for "ground truth labeling."

4. Adjudication method for the test set

• Not applicable. There is no mention of "adjudication" as would be performed in a clinical study for an AI/ML 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 background document in the input indicates a MRMC study. This is a physical mobility device and does not involve "human readers" or "AI assistance" in the sense of an AI/ML diagnostic or predictive tool.

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

• No background document in the input indicates standalone performance. This is not an AI/ML algorithm.

7. The type of ground truth used

• Not applicable in the AI/ML sense. For this device, "ground truth" implicitly relates to engineering specifications, safety standards, and functional requirements for mobility scooters. For example, the braking distance being 4.67 feet is a measured characteristic against an engineering design, not a clinical pathology or outcome.

8. The sample size for the training set

• Not applicable. There is no AI/ML model for which to describe a "training set."

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

• Not applicable. There is no AI/ML model for which to describe a "training set" or its ground truth establishment.

In summary: The provided 510(k) pertains to a physical medical device (mobility scooter) and therefore does not contain the information requested for an AI/ML device's acceptance criteria and study data. The regulatory pathway for this device is based on demonstrating substantial equivalence to a predicate device, supported by engineering tests rather than clinical performance studies with "test sets" or "training sets" in the context of AI/ML. The document explicitly states: "Comparative performance testing and clinical evaluations were not submitted as part of this 510(k)."

Ask a specific question about this device