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510(k) Data Aggregation
(325 days)
The device is intended for medical purposes to provide mobility to persons restricted to a seated position.
LERADO, Powered Wheelchair, DF4110 series include the devices with the same mechanic and electric controlling structure but with different colors of body and veneer. The LERADO Powered Wheelchair, DF4110 is an indoor / outdoor wheelchair that has a base with four-wheeled with a seat and is battery operated. The device can be disassembled for transportation, easily foldable and is provided with an off-board battery charger. The movement of the wheelchair is controlled by the rider who uses hand controls located at the top of the steering column.
The provided text describes a 510(k) premarket notification for the LERADO Power Wheelchair, Model DF4110. This document focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a study proving that the device meets specific acceptance criteria in the context of clinical performance or diagnostic accuracy. Instead, the submission describes adherence to various ISO and ANSI/RESNA standards for powered wheelchairs, materials testing, and a comparison of specifications with a predicate device.
Therefore, many of the requested items (e.g., sample sizes for test/training sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth for training) are not applicable or cannot be extracted directly from this type of regulatory submission for a powered wheelchair.
Here's an attempt to answer the questions based on the available information:
1. A table of acceptance criteria and the reported device performance
The acceptance criteria are implicitly defined by the standards the device claims to meet and by demonstrating performance comparable to the predicate device. The "reported device performance" are the specifications and compliance with these standards.
Acceptance Criteria (Standard Compliance / Specification) | Reported Device Performance (LERADO DF4110) |
---|---|
Electromagnetic compatibility (ANSI/RESNA WC Vol.2 Part 2: 2009) | Complies |
Static Stability (ISO7176-1: 1999) | Complies |
Electric Wheelchairs (General) (ISO7176-2: 2001) | Complies |
Brake Effectiveness (ISO7176-3: 2003) | Complies (Electromagnetic brake) |
Energy Consumption (ISO7176-4: 2008) | Complies (Continuous trip distance: 20km / 12.4 miles) |
Overall Dimensions, Mass, Maneuvering Space (ISO7176-5: 2008) | Complies (L: 1040mm, W: 625mm, H: 1250mm; Total weight: 70.3 kg) |
Maximum Speed, Acceleration, Retardation (ISO7176-6: 2001) | Complies (Max Speed: 6km/h (4mile/h)) |
Seating and Wheel Dimensions (ISO7176-7: 1998) | Complies (Seat depth: 410mm, Seat height: 530mm, Seat width: 475mm) |
Static, Impact, and Fatigue Strengths (ISO7176-8: 1998) | Complies |
Climatic Tests (ISO 7176-9: 2009) | Complies |
Climbing Ability (ISO7176-10: 2008) | Complies (6°) |
Test Dummies (ISO7176-11: 1992) | Complies |
Coefficient of Friction of Test Surfaces (ISO7176-13: 1989) | Complies |
Information Disclosure, Documentation, Labeling (ISO7176-15: 1996) | Complies |
Maximum Loading | 136 kgs (300 lbs) |
Frame Material (CAS# 7439-89-6 for SPCC Steel) | High-Quality SPCC Steel Pipe |
Seat Leather Fire Resistance (EN 1021-1/-2:2006 equivalent) | PVC Leather, Resistant to ignition source smouldering cigarette, and match flame |
Upholstery Fabric & Foam Fire Resistance (ANSI/BIFMA X5.1-1993, ISO 8191-1/-2, ISO 7176-16) | Fabric and Foam, resistance to ignition |
Tire Material (CAS# 101-68-8 for PU) | PU Solid Tire |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not provided in the document. The document describes compliance with international standards (ISO, ANSI/RESNA) which typically involve testing samples of the device, but the specific sample sizes used by the manufacturer for their internal testing or for the certification to these standards are not detailed. The manufacturer is LERADO Global (MACAO Commercial Offshore) Limited, based in Macau, China, suggesting the testing likely occurred in connection with their manufacturing operations, possibly with test labs in China or elsewhere. The nature of these tests (e.g., durability, stability) is generally prospective as they are performed on the device itself.
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 is not applicable in the context of this device submission. This document relates to a physical medical device (a powered wheelchair) and its performance against engineering standards, not to an AI/diagnostic algorithm where expert-established ground truth for a test set would be relevant.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This is not applicable as it pertains to human interpretation/adjudication of data, which is not relevant for the performance testing of a powered wheelchair against engineering standards.
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 is not applicable in the context of this device. MRMC studies are used for diagnostic or AI-assisted interpretation, not for mechanical devices like wheelchairs.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This is not applicable as there is no "algorithm only" component described for this powered wheelchair.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" in this context refers to the established engineering standards and specifications (e.g., ISO 7176 series, ANSI/RESNA WC Vol.2, EN 1021, ANSI/BIFMA X5.1). The device's performance is measured against these objective, quantifiable standards.
8. The sample size for the training set
This is not applicable. Powered wheelchairs are physical devices that do not typically use "training sets" in the sense of machine learning algorithms. Their design and manufacturing processes might involve iterative testing and refinement, but this is distinct from an AI training set.
9. How the ground truth for the training set was established
This is not applicable for the same reasons as #8.
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