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The product is used to obtain capillary blood samples from fingertip in a home. The device contains a sharp injury protection feature.

The Disposable Safety Lancets consists 7 parts, include a trigger, plastic handle, out shell, back cover, spring, protective cap and needle. The models of the Disposable Safety Lancets are 21G; 23G; 26G; 28G; 30G. The product is used to obtain capillary blood samples from fingertip in a hospital or at home. The device contains a sharp injury feature. The lancet is hit by pressure, and once the device strikes, the lancet needle can puncture the skin. And once activated, the needle retracts into the body of the device which reduces the risk of injury as the result if an exposed needle. Used Gamma sterilization, and are products for single use.

The provided text describes the 510(k) summary for a medical device (Disposable Safety Lancets) and focuses on demonstrating substantial equivalence to a predicate device, rather than the acceptance criteria and study data for an AI/algorithm-driven device.

Therefore, most of the requested information regarding AI/algorithm performance (e.g., sample size for test/training sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, etc.) cannot be extracted from this document, as it pertains to a physical medical device (blood lancet) and not an AI-powered diagnostic or assistive tool.

However, I can extract the acceptance criteria and performance results for the physical device's non-clinical testing.

Here's the information that can be extracted from the document:

1. Table of Acceptance Criteria and the Reported Device Performance (Non-Clinical Testing for a Physical Device)

Information that cannot be extracted from the provided text (as it's not relevant to this type of device submission):

• Sample sizes used for the test set and data provenance (e.g., country of origin, retrospective/prospective).
• Number of experts used to establish the ground truth for the test set and their qualifications.
• Adjudication method for the test set.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done, or the effect size of human readers improving with AI vs. without AI assistance.
• If a standalone (algorithm only) performance study was done.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.) for AI models.
• The sample size for the training set (for AI models).
• How the ground truth for the training set was established (for AI models).

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The Disposable Safety Lancets is intended to be used in a hospital or at home to obtain capillary blood samples from the fingertip for tests using small amounts of blood. The device contains a sharp injury protection feature.

The Disposable Safety Lancets consists 7 parts, include a lancet cap, body, slide, lancet, tip cover, spring and bottom. The models of the Disposable Safety Lancets are 18G; 21G; 23G; 26G; 28G; 30G; 32G; 33G. The Disposable Safety Lancets is intended to be used in a hospital or at home to obtain capillary blood samples from the fingertip for tests using small amounts of blood. The device contains a sharp injury protection feature. The lancet is hit by pressure, and once the device strikes, the lancet needle can puncture the skin. Used Gamma sterilization, and are products for single use.

The provided document describes a 510(k) premarket notification for "Disposable Safety Lancets" by Suzhou Kyuan Medical Apparatus Co., Ltd. This document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a clinical study of AI performance. Therefore, many of the requested details related to an AI-driven device's acceptance criteria and study proving its performance (e.g., MRMC studies, training set details, expert ground truth) are not applicable to this submission.

However, the document does contain information about performance testing for the mechanical and biological aspects of the lancet. I will extract the relevant information for the acceptance criteria and performance of the device itself (the lancet), not a hypothetical AI component, as well as indicating where information is not present or not applicable based on the nature of the submission.

Acceptance Criteria and Device Performance (Non-AI Device)

1. Table of Acceptance Criteria and Reported Device Performance

Biocompatibility Testing:

Sterilization and Shelf Life Testing:

• Irradiation sterilization validation: Per ISO 11173-1 and ISO 11173-3 (Pass, implied by conclusion of substantial equivalence).
• Pyrogen testing: Per USP (Pass, as listed in biocompatibility).
• Simulated shipping: Per ASTM D4169 (Pass, implied by conclusion of substantial equivalence).
• Shelf life: 5 years determined based on stability study which includes ageing test (Pass, implied by conclusion of substantial equivalence).

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

The document does not specify the exact sample sizes (number of units tested) for each of the performance or biocompatibility tests. It broadly states "The following performance data were provided in support of the substantial equivalence determination." This is common for 510(k) summaries where detailed protocols and raw data are part of the full submission but not typically presented in this summary format.

Data Provenance: Not explicitly stated beyond "non-clinical testing." It's generally assumed these tests were conducted at the manufacturer's or contracted labs (often in China, given the manufacturer's location in Suzhou, P.R.China) as part of their quality system requirements. These are laboratory tests of device properties, not clinical data from patients.

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

This is not applicable as this is a submission for a physical medical device (lancet), not an AI device that requires expert-established ground truth for image or data interpretation. The "ground truth" for the lancet specifications is based on physical measurements, mechanical properties testing, and standardized biological/chemical tests performed in a lab setting, not human expert consensus.

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

This is not applicable as there is no human interpretation or subjective assessment that would require an adjudication method for this type of device testing.

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. This is not an AI-assisted device.

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

This is not applicable. This is not an AI device.

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

The "ground truth" for this device's performance is based on pre-defined engineering specifications, material properties, and standardized biological safety endpoints (e.g., a penetration force

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