Search Results

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

The LERADOTECH Scooter, SB is an indoor / outdoor Electrical 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 510(k) summary for the LERADOTECH Scooter, SB details a submission for a power mobility device, like an electric scooter, and therefore does not have acceptance criteria or associated studies in the way that an AI/ML medical device would. The information provided heavily focuses on demonstrating "substantial equivalence" to a predicate device, as is customary for 510(k) submissions.

Here's why the requested information cannot be fully provided from the given document:

• Type of Device: The LERADOTECH Scooter, SB is a physical medical device (an electric scooter), not an AI/ML algorithm or software. The concepts of "acceptance criteria," "test set," "ground truth," "MRMC study," and "training set" are primarily relevant to the evaluation of AI/ML-based medical devices or diagnostic tools.
• Regulatory Pathway (510(k)): The 510(k) pathway for traditional medical devices primarily focuses on demonstrating that a new device is "substantially equivalent" to a legally marketed predicate device. This involves comparing technical characteristics, indications for use, and performance data to show the new device is as safe and effective as the predicate. It does not typically involve the rigorous clinical performance studies (like multi-reader multi-case studies or standalone algorithm performance) that are common for AI/ML devices.

However, I can extract and interpret the information related to performance testing as described for this type of device, which serves a similar function to demonstrating that the device meets certain standards.

Interpretation and Information Extraction Based on the Provided Document:

Given the context of a 510(k) for an electric scooter, the "acceptance criteria" can be interpreted as compliance with relevant industry standards and safety certifications. The "study" refers to the performance testing conducted to meet these standards.

1. Table of Acceptance Criteria and Reported Device Performance

Explanation of Substantial Equivalence and Performance Aspects (Not "Acceptance Criteria" in the AI/ML sense):

The document primarily focuses on demonstrating substantial equivalence to the COMFORT Scooter LY-EW415 (K063032). Key comparisons made include:

• Intended Uses: Same.
• Warranty Period: Same.
• Electronic Systems: Both passed UL certification; same controller and switching power supplier.
• Back Upholstery: Same material, passed resistance ignition test by SGS.
• Differences (Agreed Not to Affect Safety/Effectiveness):
  • Tire size
  • Weight limit
  • Weight capabilities
  • Smaller/more agile dimensions (leads to smaller turning radius and safe climbing angle)
  • Maximum speed: New device 6.0 mph vs. predicate 5.0 mph (both under 6 mph limit, speeds adjustable).
  • Cruising range: New device 36 km vs. predicate 75 km (due to smaller batteries, real range depends on environment, deemed substantially equivalent).

Regarding the remaining specific questions (2-9), these are not applicable to the provided document for the following reasons:

• 2. Sample sized used for the test set and the data provenance: Not applicable. Performance testing for an electric scooter involves physical testing against standards, not a "test set" of data in the AI/ML context. Physical testing would be conducted on a representative sample of the manufactured device. Data provenance (country of origin, retrospective/prospective) is typically for clinical data used in studies, which is not described here.
• 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 this context would be whether the device physically meets a standard (e.g., does it emit less than X radiation per CISPR 11). This is determined by instrumental measurement and trained technicians/engineers, not clinical experts establishing diagnostic "ground truth."
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. Adjudication methods are for resolving discrepancies in expert interpretations, which is not part of an electric scooter's performance testing for regulatory submission.
• 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 specific to AI/ML devices that assist human interpretation or diagnosis.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is specific to AI/ML algorithms.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. The "ground truth" for this device's performance would be the physical properties and functionality measured against engineering and electrical safety standards.
• 8. The sample size for the training set: Not applicable. There is no "training set" for a physical device like an electric scooter.
• 9. How the ground truth for the training set was established: Not applicable, as there is no training set.

Ask a specific question about this device