Search Results

The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The A&I Scooter SC-402 is an indoor / outdoor Powered Scooter that is battery operated. It has a base with four-wheeled with a seat. The movement of the Scooter is controlled by the rider who uses hand controls located at the top of the stecring column. The device can be disassembled for transport and is provided with an onboard battery charger.

This submission is for a motorized scooter, not an AI/ML powered device. Therefore, many of the requested categories for describing an AI study are not applicable. I will extract the relevant information from the provided text regarding the scooter's performance and testing.

Device: A&I Scooter, SC-402

The regulatory submission describes the A&I Scooter, SC-402, as an indoor/outdoor battery-operated powered scooter with four wheels and a seat. It is controlled by hand controls on the steering column, can be disassembled for transport, and includes an onboard battery charger.

The study presented here is a 510(k) submission for substantial equivalence to a predicate device, focusing on safety and functional similarities rather than a performance study with acceptance criteria in the typical sense for an AI/ML device. The "performance testing" referenced is related to electrical and mechanical safety standards rather than clinical efficacy or accuracy metrics.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of this submission (a 510(k) for substantial equivalence of a medical device, specifically a motorized scooter), "acceptance criteria" and "device performance" are framed in terms of compliance with safety standards and similarity to a predicate device, rather than specific numerical efficacy metrics.

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

This section is not applicable as this is a medical device approval for a physical product (electric scooter) based on substantial equivalence to a predicate device and compliance with safety standards, not an AI/ML software device requiring a test set of data. The "testing" involves physical product testing against specified standards.

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

This section is not applicable. Ground truth, in the context of expert consensus, is typically used for AI/ML diagnostic or prognostic devices. For this physical product, regulatory bodies (e.g., UL, SGS) or internal engineering teams would verify compliance with standards.

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

This section is not applicable. Adjudication methods are typically employed in clinical studies or for establishing ground truth in AI/ML performance evaluations.

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 section is not applicable. MRMC studies are designed for evaluating diagnostic AI systems, not physical medical devices like a scooter.

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

This section is not applicable. This is a physical device, an electric scooter, with no AI algorithm involved.

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

The "ground truth" here is implied by the established engineering and electrical safety standards (e.g., ANSI / RESNA WC/Vol.2-1998, CISPR 11: 1990, EN61000-3-2: 1995, IEC61000-3-3: 1995, UL certification, SGS resistance ignition test). Compliance with these standards serves as the "ground truth" for the device's safety and foundational functionality. Substantial equivalence to a legally marketed predicate device (WU's 3-Wheeled Neo Scooter, WT-L4Jr (K032617)) also forms a key part of the "ground truth" for regulatory approval.

8. The sample size for the training set

This section is not applicable. The device is a physical product and does not involve AI/ML requiring a training set.

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

This section is not applicable due to the absence of an AI/ML component and training set.

Ask a specific question about this device

The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The A&I Scooter SC-301 is an indoor / outdoor Powered Scooter that is battery operated. It has a base with four-wheeled with a 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 onboard battery charger.

The provided document is a 510(k) premarket notification for a medical device called the "A&I Scooter, SC-301," which is a motorized three-wheeled vehicle. This type of document is used to demonstrate that a new device is substantially equivalent to a legally marketed predicate device, rather than proving its effectiveness through clinical trials with specific acceptance criteria as you've outlined for AI/ML devices.

Therefore, the information regarding acceptance criteria, study design elements (sample sizes, ground truth, experts, adjudication, MRMC studies, standalone performance, training data), is not applicable to this document.

Instead, the "performance testing" section of this 510(k) document refers to engineering and safety standards, and the "study" is a comparison to a predicate device.

Here's an analysis based on the information provided, tailored to a 510(k) submission for a non-AI/ML device:

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

For this device, "acceptance criteria" are not reported as specific performance metrics like sensitivity or specificity. Instead, the device is deemed acceptable if it meets established safety and electromagnetic compatibility (EMC) standards and is substantially equivalent to a legally marketed predicate device.

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

• Not Applicable: This type of information is not relevant for the 510(k) submission of this medical device. The "test set" here refers to the actual scooter undergoing engineering and safety tests, not a dataset for an AI model. There is no data provenance in the context of clinical or image data.

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: This information is not relevant as there is no "ground truth" established by human experts in the context of an AI/ML model for this device. The standards compliance is assessed by testing facilities (e.g., SGS for ignition test) and regulatory bodies.

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

• Not Applicable: There is no adjudication method described as there's no "ground truth" for an AI/ML model being assessed. Compliance with standards is evaluated through specified test procedures.

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 is not an AI/ML device, so no MRMC study was conducted or is relevant.

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

• Not Applicable: This is not an AI/ML device, so no standalone algorithm performance was assessed. The device itself is a standalone product.

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

• Not Applicable: There is no ground truth in the context of clinical outcomes or diagnostic accuracy for this device. "Ground truth" for this product would be adherence to engineering specifications and safety standards defined by organizations like ANSI/RESNA, CISPR, EN, and IEC.

8. The sample size for the training set

• Not Applicable: This is not an AI/ML device, so there is no training set.

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

• Not Applicable: This is not an AI/ML device, so there is no training set ground truth to establish.

Ask a specific question about this device

The device is intended for medical purposes to provide mobility to persons restricted to a seated position.

The A&I Power Wheelchair, PC-401 is an indoor / outdoor Powered Wheelchair that is battery operated. It has a base with four-wheeled with a seat. The movement of the Wheelchair 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 document describes the predicate device information, but does not sufficiently detail any studies to prove that the device meets the acceptance criteria. The document states that performance testing was conducted according to certain standards (ANSI / RESNA WC/Vol.2-1998, CISPR 11: 1990, EN61000-3-2: 1995, IEC61000-3-3: 1995), but it does not provide any results from these tests or specific acceptance criteria. Instead, it relies on a comparison to a predicate device to establish substantial equivalence.

Therefore, the following information can be extracted, but many sections requested in the prompt cannot be fulfilled due to lack of detail in the source document.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document emphasizes "substantial equivalence" to a predicate device (SINON Power Wheelchair, SN-W401, K040319) rather than predefined acceptance criteria for a new device. The "reported device performance" is primarily a comparison against the predicate.

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

The document does not specify a separate "test set" or its sample size. The performance testing refers to general compliance with standards, and the comparison is based on device specifications rather than a clinical trial or specific test set.

• Data Provenance: Not explicitly stated for specific tests, but the device is manufactured in Taiwan, R.O.C. (Republic of China). The testing standards are international.

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

Not applicable. No ground truth establishment for a test set is mentioned. The assessment is based on engineering specifications and adherence to standards.

4. Adjudication Method for the Test Set

Not applicable. No test set requiring adjudication is mentioned.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Not applicable. This is a medical device (power wheelchair), not an AI-powered diagnostic tool, so an MRMC study is not relevant.

6. Standalone (Algorithm Only) Performance

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

7. Type of Ground Truth Used

Not applicable in the typical sense of a diagnostic algorithm. The "ground truth" for the device's performance would be the physical measurements and tests conducted according to the cited standards (ANSI / RESNA, CISPR, EN, IEC) to ensure functionality and safety.

8. Sample Size for the Training Set

Not applicable. This is a manufactured product, without a "training set" in the context of machine learning.

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

Not applicable.

Ask a specific question about this device