Search Results

Quickie powered wheelchairs empower physically challenged persons by providing a means of mobility. This included conditions in all ages such as: Arthritis Amputee Paraplegic Cerebral Palsy Hemiplegic Tetaplegic (Quadraplegic) Spina Bifida Head Injury or Trauma Muscular Dystrophy Multiple Scierosis Polio Geriatric Conditions And other immobilizing or debilitating conditions

Quickie P90 Power Wheelchairs consists of typical components found on most wheelchairs, such as push handles, armrests, backrest, seat frame, cushion, footrest and casters. Accessories include items such as positioning belts, backpacks, seat pouches, oxygen tank holders, IV poles, etc. As motorized wheelchairs, they also contain controllers, joysticks, motors, brakes, drive wheels and batteries. Many of these components are available in a range of sizes, shapes, angles, forms, materials or coverings. These variations allow the chairs to be configured to meet the specific desires and needs of the user.

Here's an analysis of the provided text regarding the acceptance criteria and supporting study for the medical device:

The provided document describes a 510(k) submission for the Quickie P90 Power Wheelchair Series. It is important to note that this document is for a medical device (a power wheelchair), not an AI/ML-driven diagnostic or prognostic device. Therefore, many of the typical acceptance criteria and study methods associated with AI, such as standalone performance, MRMC studies, ground truth establishment by experts, and sample sizes for training/test sets in the context of machine learning, are not applicable to this type of device submission.

The document focuses on demonstrating substantial equivalence to predicate devices, primarily through engineering and safety standards.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of the device (a power wheelchair) and the context of a 510(k) submission, the "acceptance criteria" are primarily established by compliance with recognized engineering and safety standards, and the "performance" is demonstrated by passing tests defined by these standards.

• Proposed Addition to ANSI/RESNA W/C 14 Electromagnetic Compatibility Requirements for powered Wheelchairs and Motorized Scooters Version 1.5 Dated 1/11/94
• ISO EMC Draft Standard 7176-14 Rifled Draft ISO EMC Group Proposal Electromagnetic Compatibility Addition Dated 4/3/95 Regarding Electromagnetic Compatibility Requirements for Powered Wheelchairs and Motorized Scooters. |

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

• Sample Size for Test Set: Not explicitly stated as "sample size" in the context of clinical trials or data for an AI algorithm. For a physical product like a wheelchair, testing typically involves one or more prototypes of the device model itself, not a "sample size" of patient data. The standards define how those prototypes are tested.
• Data Provenance: Not applicable in the AI/ML sense. The "data" here comes from direct physical testing of the device prototypes in a laboratory or controlled environment, against established engineering standards. There is no patient data or retrospective/prospective data collection described for the testing of substantial equivalence.

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

• Number of Experts: Not applicable. The "ground truth" for a mechanical device like a wheelchair is established by its ability to meet objective, quantifiable measurements and performance targets defined by established engineering and safety standards (e.g., brake effectiveness, stability angles, fatigue cycles). These standards are developed by consensus of engineers and safety experts over time, but there isn't a specific set of experts establishing ground truth for this device's test set in the way one would for diagnostic imaging.
• Qualifications of Experts: N/A.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. Testing against engineering standards is typically objective; a test either passes or fails according to predefined criteria. There's no subjective interpretation requiring adjudication of results in the way an AI diagnostic result might.

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

• Was an MRMC study done? No. This type of study is relevant for evaluating the impact of an AI diagnostic aid on human reader performance, which is not applicable to a power wheelchair.
• Effect size of human readers improve with AI vs without AI assistance: Not applicable.

6. Standalone (Algorithm Only) Performance

• Was a standalone performance study done? No. This concept applies to AI algorithms that can operate independently of human intervention for tasks like detection or classification. A power wheelchair is a physical product directly used by a human.

7. Type of Ground Truth Used

• Type of Ground Truth: The "ground truth" for this device's acceptance is adherence to established engineering and safety standards. These standards define objective, measurable performance characteristics (e.g., maximum speed, stability angles, brake effectiveness, fatigue resistance, EMC compliance).

8. Sample Size for the Training Set

• Sample Size for 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

• How Ground Truth for Training Set Was Established: Not applicable, as there is no training set for this type of device.

Summary for the Quickie P90 Power Wheelchair Series:

This device's acceptance criteria are based on its compliance with international (ISO 7176) and national (ANSI/RESNA) wheelchair safety and performance standards. The "study" involves subjecting prototypes of the wheelchair to a battery of tests specified by these standards, covering aspects like stability, braking, durability, and electromagnetic compatibility. The demonstration of passing these tests constitutes the evidence that the device meets its performance and safety requirements for market clearance under the 510(k) pathway for substantial equivalence. The submission does not involve clinical trials, AI algorithm performance, or human reader studies.

Ask a specific question about this device

Quickie Powered Wheelchairs empower physically challenged persons by providing a means of mobility.

Quickie powered wheelchairs consist of typical features found on any wheelchair, such as push handles, adjustable armrests, backrest, seat frame and cushion, footrests, and casters. Because these are motorized wheelchairs, they also consist of joy stick controller, motors, brakes, batteries and drive wheels.

The provided text describes a 510(k) submission for a change in the controller of a powered wheelchair. This is a medical device submission, but it primarily focuses on engineering and performance testing related to the wheelchair's functionality and safety, rather than a clinical study evaluating diagnostic or therapeutic efficacy.

Therefore, many of the typical acceptance criteria and study details relevant to AI/diagnostic medical devices (such as sample size for test sets, data provenance, expert ground truth adjudication, MRMC studies, standalone performance, training sets, etc.) are not applicable or not provided in this document.

Here's a breakdown based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not specified. The testing described is likely on a limited number of physical units of the Quickie Power Wheelchair with the new P&G controller.
• Data Provenance: The testing was conducted on the Quickie Power Wheelchair with the P&G Controller. The data would be prospective, as it was generated from testing the new configuration. The country of origin is not explicitly stated but can be inferred as the US, given the submission to the FDA.

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

• Not Applicable. This is not a study requiring expert interpretation of diagnostic images or data. Ground truth here refers to engineering specifications and measurements, which are established by engineers and adherence to industry standards, not medical experts.

4. Adjudication method for the test set

• Not Applicable. Not a clinical study requiring adjudication of expert opinions. Performance is measured against predefined engineering specifications.

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 not relevant to a powered wheelchair controller change.

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

• Not Applicable. The "device" here is a physical wheelchair system, not an AI algorithm. Its performance is inherent in its physical operation.

7. The type of ground truth used

• Engineering Specifications and Predicate Device Performance: The "ground truth" for this submission is established by:
  • Predefined engineering parameters (e.g., speed ranges, acceleration limits).
  • The performance characteristics of the previously approved Quickie wheelchair with the Dynamics controller (predicate device).
  • The performance characteristics of other commercially available wheelchairs using the P&G 8 controller (other predicate devices).

8. The sample size for the training set

• Not Applicable. This submission does not involve an AI algorithm that requires a "training set" in the machine learning sense. The controller's software is developed and validated, not "trained" on a dataset.

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

• Not Applicable. (See point 8)

Ask a specific question about this device

Quickie Powered Wheelchairs empower physically challenged persons by providing a means of mobility.

Quickie powered wheelchairs consist of typical features found on any wheelchair, such as push handles, adjustable armrests, backrest, seat frame and cushion, footrests, and casters. Because these are motorized wheelchairs, they also consist of joy stick controller, motors, brakes, batteries and drive wheels.

The provided text is a Summary of Safety and Effectiveness for the Quickie Powered Wheelchair with Penny and Giles Controller, a medical device submission. It describes the device, its intended use, and compares it to predicate devices. However, the document does not contain the information requested in your prompt regarding acceptance criteria and a study proving the device meets those criteria, specifically:

• Table of acceptance criteria and reported device performance: This is absent. The document only states that testing "demonstrate that the wheelchair performs as the predicate device" and "according to specification," but no specific criteria or quantified performance metrics are provided.
• Sample size and data provenance for the test set: Not mentioned for any testing.
• Number of experts and their qualifications for ground truth: Not applicable, as this is hardware testing, not an AI or diagnostic study requiring expert consensus.
• Adjudication method: Not applicable.
• Multi-reader multi-case (MRMC) comparative effectiveness study: Not conducted, as this is a physical device and controller modification, not a diagnostic imaging or AI-assisted interpretation system.
• Standalone (algorithm only) performance: Not applicable, as it's a physical controller; its performance is always "in-the-loop" with the wheelchair.
• Type of ground truth used: For non-clinical testing, the "ground truth" would be engineering specifications and safety standards, but these are not explicitly detailed.
• Sample size for the training set: Not applicable, as this is hardware testing, not a machine learning model.
• How ground truth for the training set was established: Not applicable.

The document primarily focuses on demonstrating substantial equivalence to existing predicate devices through non-clinical testing of programmable parameters and electromagnetic compatibility (EMI). The core assertion is that the new P&G controller does not change the core wheelchair specifications and performs comparably to the previous Dynamics controller, which is already on the market.

Specific findings from the document related to testing:

• Non-clinical testing: Performed on all programmable parameters, including:
  • Maximum and minimum forward and reverse speeds
  • Maximum and minimum turn speeds
  • Maximum and minimum acceleration and deceleration
  • Maximum and minimum turn acceleration and deceleration
• Comparative testing: Regarding speed, acceleration, and brake distance, results "demonstrate that the wheelchair performs as the predicate device with the Dynamics controller."
• Electromagnetic compatibility testing: Performed, and results "demonstrate that the wheelchairs pass the 20 V/m EMI test."
• Software validation information: Includes requirements, design, development, verification, validation, hazard analysis, and mitigation associated with controller safety.

In summary, the document states that the device meets "specifications" and performs "as the predicate device," but it does not provide the quantitative acceptance criteria or detailed study results that your prompt requests. The nature of this submission (a modification of a physical device's controller) does not lend itself to many of the AI-specific questions in your prompt.

Ask a specific question about this device

Quickie Powered Wheelchairs empower physically challenged persons by providing a means of mobility.

Quickie powered wheelchairs consist of typical features found on any wheelchair, such as push handles, adjustable armrests, backrest, seat frame and cushion, footrests, and casters. Because these are motorized wheelchairs, they also consist of joy stick controller, motors, brakes, batteries and drive wheels.

This document is a 510(k) premarket notification for a change in the controller of an existing powered wheelchair. It does not describe a study involving "acceptance criteria" and "device performance" in the context of typical AI/ML medical device evaluations.

Therefore, I cannot extract the requested information as it is not present in the provided text. The document focuses on demonstrating substantial equivalence to a predicate device due to a controller change, not on evaluating the performance of a new AI/ML algorithm against predefined metrics.

Ask a specific question about this device