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510(k) Data Aggregation
(158 days)
The Sunrise Air is a non-invasive home care aid in the evaluation of obstructive sleep apnea (OSA) in patients 18 years and older with suspicions of sleep breathing disorders.
The Sunrise Air consists of the Sunrise software (v1.28.00), which analyzes data from one of three compatible sensors (Sunrise sensor 1, Sunrise sensor 2, or Sunrise Air) placed on the patient's chin. Sunrise sensor 1 was approved through DEN210015, while Sunrise sensor 2 was cleared through K222262. The current version of the Sunrise device introduces a new sensor, Sunrise Air. The Sunrise device is intended to detect respiratory events, identify sleep stages and position, and generate key sleep parameters—such as the apnea-hypopnea index ("Sunrise AHI") and positional states classifications. The collected data is compiled into a report for further interpretation by a healthcare provider.
The provided FDA 510(k) clearance letter for the Sunrise Air device primarily focuses on demonstrating substantial equivalence to a predicate device, rather than detailing a comprehensive clinical study to prove the device meets specific acceptance criteria for its claimed indications.
The document highlights bench testing for technical equivalence, but lacks the detailed clinical study information typically provided for direct performance claims against established ground truth. Specifically, it states that "No modifications have been made to the Sunrise algorithm used to generate sleep parameters," and that a "validation study of SpO₂ and pulse rate accuracy for the subject device was conducted using raw PPG data acquired during the clinical validation for the Sunrise sensor 2 (K222262)." This suggests reliance on prior clearances for core algorithm performance and a specific re-validation for only the PPG data processing change.
Therefore, many of the requested details about acceptance criteria, clinical study design, and ground truth establishment for the overall device performance (e.g., AHI calculation, OSA evaluation) are not explicitly present in this summary.
Given the information in the provided document, here's what can be extracted and inferred:
1. A table of acceptance criteria and the reported device performance:
Based on the information provided, the "acceptance criteria" are implied by the comparisons to the predicate and reference devices, and some specific performance metrics are given for SpO2 and pulse rate. The primary acceptance criterion for the device's main function (evaluation of OSA via AHI) is that "No modifications have been made to the Sunrise algorithm used to generate sleep parameters," implying continued equivalence to the predicate's performance.
| Performance Metric | Acceptance Criteria (Implied/Direct) | Reported Device Performance (Sunrise Air) |
|---|---|---|
| Overall Device Performance (OSA Evaluation) | Implied substantial equivalence to predicate device (Sunrise K222262) in the evaluation of OSA, as no changes were made to the core AHI algorithm. | "No modifications have been made to the Sunrise algorithm used to generate sleep parameters." The device generates "key sleep parameters—such as the apnea-hypopnea index ('Sunrise AHI')." |
| SpO₂ Accuracy | Not explicitly stated but inferred from previous predicate's clearance (K222262). Common standards are often <3.0% RMS. | 1.91% RMS over the range of 70-100% |
| Pulse Rate Accuracy | Not explicitly stated but inferred from previous predicate's clearance (K222262). Common standards are often within 5 bpm or <5% RMS. | 2.73 beats per minute (bpm) RMS for a claimed measurement range of 51 to 104 bpm |
| Accelerometer and Gyroscope Signals | Technical equivalence to predicate device. | Signals measured by subject and predicate devices found to be equivalent. |
| Thermistor Signal (Breathing Patterns) | Equivalent performance to oronasal thermal airflow sensor of reference device. | Equivalent performance in capturing breathing patterns demonstrated. |
| Microphone Signal (Snoring) | Comparable performance to microphone of reference device (Somno HD). | Comparable performance observed; sound patterns visually similar, synchronized transitions, comparable noise variations. |
Study that Proves the Device Meets Acceptance Criteria:
The document describes a combination of bench testing and reliance on prior clinical validation for specific components. There isn't a single, new "study" designed to prove the overall device meets a set of clinical acceptance criteria for OSA evaluation, but rather, individual tests to establish equivalence of components or re-validate specific algorithm changes.
2. Sample size used for the test set and the data provenance:
- Overall Device (for AHI/OSA evaluation): Not explicitly stated for a new study. The document states that "No modifications have been made to the Sunrise algorithm used to generate sleep parameters." This implies reliance on the clinical validation data from the predicate device (Sunrise K222262). The original K222262 submission would contain this information.
- SpO₂ and Pulse Rate Accuracy:
- Sample Size: Not explicitly stated. The study was conducted using "raw PPG data acquired during the clinical validation for the Sunrise sensor 2 (K222262)." The sample size for that original clinical validation would be the relevant number.
- Data Provenance: Retrospective, as it used data from a previous clinical validation study (for Sunrise sensor 2, cleared under K222262). The country/region of origin of this data is not specified in this document.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Overall Device (for AHI/OSA evaluation): Not specified in this document, as the core algorithm relies on prior validation. For the original K222262 clearance, ground truth would typically be established by a consensus of sleep experts (e.g., board-certified sleep physicians or registered polysomnographic technologists (RPSGTs)).
- SpO₂ and Pulse Rate: Ground truth for these parameters is typically established through a co-oximeter or arterial blood gas analysis, not necessarily by "experts" in the human sense, but by a gold-standard measurement device.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not specified within this 510(k) summary for any new studies. For the original clinical validation of the AHI algorithm, an adjudication method (such as independent scoring by multiple qualified technologists/physicians with consensus or a tie-breaker) would typically be employed for the polysomnography (PSG) ground truth.
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, an MRMC comparative effectiveness study involving human readers and AI assistance is not described in this document. The device is for "aiding in the evaluation" and generates parameters; it is not presented as an AI-assisted diagnostic tool for human interpretation improvement in this summary.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Yes, the device's capability to "detect respiratory events, identify sleep stages and position, and generate key sleep parameters" and a "Sunrise AHI" implies a standalone algorithmic performance in generating these outputs from the sensor data. The statement "No modifications have been made to the Sunrise algorithm used to generate sleep parameters" means that the standalone performance of the algorithm itself is considered validated based on its prior clearance. The SpO₂ and pulse rate accuracy also represent standalone algorithm performance.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Overall Device (for AHI/OSA evaluation): Not explicitly stated, but for sleep apnea diagnostic devices, the ground truth is overwhelmingly polysomnography (PSG) scored by qualified experts (e.g., according to AASM guidelines). This would have been the ground truth for the predicate device's (K222262) clearance.
- SpO₂ and Pulse Rate: The ground truth for SpO₂ accuracy is typically established using a reference pulse oximeter or co-oximeter (invasive arterial blood gas analysis may be used for a subset of the data if required for the specific accuracy claims and range). For pulse rate, a simultaneous ECG or the reference oximeter's heart rate measurement.
8. The sample size for the training set:
- Not specified in this document. As the core algorithm is unchanged from the predicate, its training data would have been part of the K222262 submission.
- The document mentions "cloud-based algorithm (Sunrise PPG algorithm)" as a change for PPG data processing, but it does not specify the training set size for this particular component, only that its validation was done on existing test data.
9. How the ground truth for the training set was established:
- Not specified in this document, as the core algorithm leverages prior clearance. For the predicate device, ground truth for training data would have broadly been established in the same manner as the test set: expert-scored polysomnography (PSG) data. However, the specific details (e.g., single expert vs. consensus) are not provided here.
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(147 days)
The Sunrise device is a non-invasive home care aid in the evaluation of obstructive sleep apnea (OSA) in patients 18 years and older with suspicions of sleep breathing disorders.
The Sunrise device is a cloud-based software device that analyzes data from a sensor (Sunrise sensor 1 or Sunrise sensor 2) placed on the patient's chin. The device detects respiratory events, identifies sleep stages and position. The device generates sleep parameters, e.g. apnea hypopnea index "Sunrise AHI", and position discrete states. Data collected by the device is integrated in a report for further interpretation by the healthcare provider.
The provided text details the performance data for the Sunrise device to support its substantial equivalence determination. However, it does not explicitly state "acceptance criteria" in a表格 format as requested. Instead, it describes performance metrics (e.g., median measurement bias and LOA, sensitivity, specificity, global accuracy, and RMS values) for various parameters against pre-determined thresholds of clinical acceptability or against a gold standard (PSG).
Based on the provided information, I will infer the acceptance criteria from the reported performance, as these are the values the device did achieve and were deemed sufficient for substantial equivalence.
Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
As explicit acceptance criteria thresholds are not stated, the "Acceptance Criteria" column will reflect the reported performance that was deemed acceptable for substantial equivalence. The "Reported Device Performance" will reiterate these values.
| Parameter | Acceptance Criteria (Inferred from Reported Performance) | Reported Device Performance |
|---|---|---|
| Study 1 (Belgium, n=289) | ||
| TST Median Bias & LOA | Median bias within -4.50 min and LOA of -41.74 to +35.67 | -4.50 min (-41.74 to +35.67) |
| AHI Median Bias & LOA | Median bias within -0.46 event/h and LOA of -13.52 to +9.00 | -0.46 event/h (-13.52 to +9.00) |
| ORDI Median Bias & LOA | Median bias within +0.15 event/h and LOA of -10.70 to +10.12 | +0.15 event/h (-10.70 to +10.12) |
| Sensitivity (AHI>=5) | >= 0.99 | 0.99 |
| Sensitivity (AHI>=15) | >= 0.92 | 0.92 |
| Sensitivity (AHI>=30) | >= 0.81 | 0.81 |
| Specificity (AHI>=5) | >= 0.86 | 0.86 |
| Specificity (AHI>=15) | >= 0.94 | 0.94 |
| Specificity (AHI>=30) | >= 0.99 | 0.99 |
| Study 2 (France, n=31) | ||
| TST Median Bias & LOA | Median bias within -10.50 min and LOA of -37.42 to +25.79 | -10.50 min (-37.42 to +25.79) |
| AHI Median Bias & LOA | Median bias within +0.20 event/h and LOA of -12.30 to +6.30 | +0.20 event/h (-12.30 to +6.30) |
| ORDI Median Bias & LOA | Median bias within +1.01 event/h and LOA of -11.24 to +6.21 | +1.01 event/h (-11.24 to +6.21) |
| Sensitivity (AHI>=5) | >= 1.00 | 1.00 |
| Sensitivity (AHI>=15) | >= 0.94 | 0.94 |
| Sensitivity (AHI>=30) | >= 0.87 | 0.87 |
| Specificity (AHI>=5) | >= 0.75 | 0.75 |
| Specificity (AHI>=15) | >= 1.00 | 1.00 |
| Specificity (AHI>=30) | >= 1.00 | 1.00 |
| Study 3 (Belgium, n=10) | ||
| Position Discrete States Global Accuracy | >= 93% | 93% |
| Study 4 (SpO2 & Pulse Rate Accuracy) | ||
| SpO2 Accuracy (RMS) | <= 2.70% (over range 70-100%) | 2.70% (over range of 70-100%) |
| Pulse Rate Accuracy (RMS) | <= 1.95 bpm (over range 51-104 bpm) | 1.95 bpm (for a range of 51 to 104 bpm) |
| Thermistor Ability to Capture Airflow | Performance equivalent to PSG oronasal thermal airflow sensor | Equivalent to an oronasal thermal airflow sensor used in PSG |
2. Sample Sizes Used for the Test Set and Data Provenance
- Clinical Study 1: 289 patients, retrospective, comparative, open study. Performed in Belgium.
- Clinical Study 2: 31 patients, retrospective, comparative, open study. Performed in France.
- Clinical Study 3: 10 patients, retrospective, comparative, open study. Performed in Belgium.
- Clinical Study 4 (SpO2 & Pulse Rate): Not explicitly stated, but validated in accordance with ISO 80601-2-61:2019 and FDA guidance. This is typically a controlled bench study with a human subject population, but the document does not break down the sample size for this specific validation.
- Thermistor Validation: Not explicitly stated (the text mentions "a validation study was conducted").
All mentioned clinical studies are described as retrospective, comparative, and open studies.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The document does not specify the number or qualifications of experts used to establish the ground truth (PSG data). It only refers to "the gold-standard PSG" as the comparison. In typical PSG studies, the PSG data is scored by trained sleep technologists and sometimes reviewed by a sleep physician, but this detail is not provided.
4. Adjudication Method for the Test Set
The document does not describe any specific adjudication method for the test set. The ground truth is stated to be "the gold-standard PSG."
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 MRMC study comparing human readers with and without AI assistance is mentioned. The studies focus on the performance of the device (algorithm) itself against PSG.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Yes, the clinical studies describe the performance of the "algorithm" and the "device" against PSG, indicating a standalone (algorithm only) evaluation. The text states: "The algorithm was used to analyze sensor data and evaluate the performance of the device compared to PSG."
7. The Type of Ground Truth Used
The primary ground truth used for OSA parameters (TST, AHI, ORDI, OSA severity) and position discrete states was Polysomnography (PSG), referred to as the "gold-standard PSG." For SpO2 and pulse rate accuracy, the ground truth was established in accordance with ISO 80601-2-61:2019 and relevant FDA guidance, which typically involves comparison against a reference oximeter or validated measurement system. For the thermistor, it was compared to an "oronasal thermal airflow sensor used in PSG."
8. The Sample Size for the Training Set
The document does not explicitly state the sample size for the training set. The clinical studies mentioned (n=289, n=31, n=10) are described as performance evaluation studies for the device, not necessarily for training. It states the "Sunrise algorithm... has been updated," implying a development process that would include training, but the specifics of the training dataset are not provided.
9. How the Ground Truth for the Training Set Was Established
The document does not provide information on how the ground truth for any potential training set was established. It focuses solely on the performance evaluation of the device against the "gold-standard PSG" for its validation studies.
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(280 days)
The Sunrise SDDA device is a non-invasive home care aid in the evaluation of obstructive sleep apnea (OSA) in patients 18 years and older with suspicions of sleep breathing disorders.
The Sunrise SDDA device consists of a Sunrise sensor and a cloud-based software device that analyzes data from the sensor when placed on the patient's mandible. The device also includes a mobile application to record patient's responses to questions about their sleep quality and transfer sensor data to the cloud. By analyzing patient's mandibular movements, the device also detects obstructive respiratory disturbances, identifies sleep states, notifies about the Obstructive Sleep Apnea (OSA) severity in a categorical format (non-OSA, mild-OSA, moderate-OSA, severe-OSA), generates sleep structure information (namely, total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, arousal index) and head position discrete states. Data collected by the device is integrated in a report for further interpretation and diagnosis by the healthcare provider.
Here's a breakdown of the acceptance criteria and study information for the Sunrise Sleep Disorder Diagnostic Aid (SDDA), based on the provided text:
Acceptance Criteria and Reported Device Performance
| Assessment Metric | Acceptance Criteria (Implied) | Reported Device Performance (as stated in the text) |
|---|---|---|
| OSA Severity Output | The clinical data must demonstrate output consistency and compare device performance with a clinical comparator device (polysomnography). Diagnostic metrics (sensitivity, specificity) for different ORDI cut-offs should be presented and deemed acceptable. | Second Study (France): - Sensitivity: (b)(4) - Specificity: (b)(4) *For ORDI cut-offs: ORDI> (b)(4), ORDI> (b)(4), and ORDI> (b)(4) events/h, respectively. * (Specific values for each cutoff are redacted as (b)(4)). Third Study (Belgium): - Sensitivity: (b)(4) - Specificity: (b)(4) *For ORDI cut-offs: ORDI>= (b)(4), ORDI>= (b)(4), and ORDI>= (b)(4) events/h, respectively. * (Specific values for each cutoff are redacted as (b)(4)). |
| Sleep Structure Parameters (TST, SOL, WASO, SE, ArI) Including Total Sleep Time (TST), Sleep Onset Latency (SOL), Wake After Sleep Onset (WASO), Sleep Efficiency (SE), Arousal Index (ArI) | The clinical data must demonstrate output consistency and compare device performance with a clinical comparator device (polysomnography). Performance should be quantified by Root Mean Square Error (RMSE) and confidence intervals (CIs). | First Study (Belgium - Retrospective): - RMSE: (b)(4) (CI (b)(4)) for TST, SOL, WASO, SE, and ArI respectively. (Specific values for each are redacted as (b)(4)). Second Study (France - Prospective): - RMSE: (b)(4) (CI (b)(4)) for TST, SOL, WASO, SE, and ArI respectively. (Specific values for each are redacted as (b)(4)). Third Study (Belgium - Retrospective): - RMSE: (b)(4) (CI (b)(4)) for TST, SOL, WASO, SE, and ArI respectively. (Specific values for each are redacted as (b)(4)). |
| Biocompatibility | Demonstrate that patient-contacting components are biocompatible. | Test articles (skin adhesive and film dressing) found non-cytotoxic, non-sensitizing, and non-irritating per ISO 10993-5 and ISO 10993-10. |
| Electromagnetic Compatibility & Electrical Safety | Performance data must be provided to demonstrate EMC and electrical, mechanical, and thermal safety. | IEC 60601-1 and IEC 60601-1-2 testing performed; results support electrical safety and electromagnetic compatibility. |
| Software Validation | Appropriate documentation to support validation for a Moderate Level of Concern, including algorithms, hardware characteristics, and mitigations for subsystem failures. Cybersecurity measures also addressed. | "Appropriate documentation" provided per FDA's 2005 (Software) and 2014 (Cybersecurity) guidance documents, including workflow, handling of errors, and algorithm development steps. |
| Human Factors/Usability | Usability engineering testing in accordance with IEC 62366-1:2015 should demonstrate that safety-related tasks can be successfully performed. | Formative usability testing conducted in Belgium with adult users (tech-savvy & non-tech-savvy). Majority of participants completed all tasks correctly. Outcome assessed as satisfactory, providing "adequate assurance that all tasks linked to a safety mitigation could be successfully performed." No critical tasks were identified that could result in serious harm if performed incorrectly. |
| Packaging and Shelf Life | Packaging and labeling should withstand anticipated shipping conditions and preserve functionality. Shelf-life determined and supported. | Drop testing, resistance to rain/humidity, and label integrity evaluations demonstrated appropriate protection. Shelf-life of 2 years determined based on adhesive shelf-life. |
Study Details
The sponsor provided three clinical studies to support the safety and effectiveness of the Sunrise SDDA device.
1. First Clinical Study (Retrospective)
- Sample Size: Not explicitly stated for this particular study, but described as "patients."
- Data Provenance: Belgium, retrospective.
- Number of Experts for Ground Truth: One experienced sleep technician.
- Qualifications of Experts: "Experienced sleep technician."
- Adjudication Method for Test Set: None explicitly mentioned as a multi-expert adjudication process. The PSG data was visually scored by a single experienced sleep technician.
- MRMC Comparative Effectiveness Study: No. This study focused on algorithm performance against PSG.
- Standalone Performance: Yes, the Sunrise Machine Learning algorithms analyzed sensor data to evaluate the device performance for sleep structure parameters compared to in-lab PSG.
- Type of Ground Truth: Expert-scored Polysomnography (PSG) by an experienced sleep technician,
following 2012 AASM recommendations, and blinded to the study protocol. - Sample Size for Training Set: Not explicitly stated, however, the text mentions that "the same datasets were used for both optimizing diagnostic thresholds (training) and performance evaluation (validation)," suggesting this study may have contributed to or been part of the training data.
- How Ground Truth for Training Set was Established: PSG data visually scored by an experienced sleep technician according to 2012 AASM recommendations.
2. Second Clinical Study (Prospective)
- Sample Size: Not explicitly stated, described as "patients."
- Data Provenance: France, prospective.
- Number of Experts for Ground Truth: Not explicitly stated beyond "experienced sleep technicians."
- Qualifications of Experts: "Experienced sleep technicians from two different sleep centers (Université Grenoble Alpes, Grenoble, France and Imperial College London, London, United Kingdom)."
- Adjudication Method for Test Set: Not explicitly stated as a formal adjudication protocol (e.g., 2+1), but PSG data was scored by "experienced sleep technicians from two different sleep centers," suggesting independent scoring, though not necessarily an adjudication to resolve discrepancies.
- MRMC Comparative Effectiveness Study: No. This study focused on algorithm performance against PSG.
- Standalone Performance: Yes, the device's performance for all output parameters (OSA severity and sleep structure) was evaluated compared to ambulatory at-home PSG.
- Type of Ground Truth: Expert-scored Polysomnography (PSG) by experienced sleep technicians from two different sleep centers, following 2012 AASM recommendations.
- Sample Size for Training Set: Not mentioned as contributing to the training set. This was an independent prospective study.
- How Ground Truth for Training Set was Established: Not applicable; this study was for validation.
3. Third Clinical Study (Retrospective)
- Sample Size: Not explicitly stated, described as "patients."
- Data Provenance: Belgium, retrospective.
- Number of Experts for Ground Truth: One experienced sleep technician.
- Qualifications of Experts: "Experienced sleep technician."
- Adjudication Method for Test Set: None explicitly mentioned as a multi-expert adjudication process. The PSG data was visually scored by a single experienced sleep technician.
- MRMC Comparative Effectiveness Study: No. This study focused on algorithm performance against PSG.
- Standalone Performance: Yes, the Sunrise SDDA algorithms analyzed sensor data to evaluate the performance of the device compared to in-lab PSG.
- Type of Ground Truth: Expert-scored Polysomnography (PSG) by an experienced sleep technician,
following 2012 AASM recommendations, and blinded to the study protocol. - Sample Size for Training Set: Not explicitly stated. The study is described as "independent clinical study with similar design as the first one," but doesn't mention its role in training.
- How Ground Truth for Training Set was Established: Not applicable; this study was for validation.
Summary of Training and Validation Data Distinction:
- The First Clinical Study was noted to have used "the same datasets... for both optimizing diagnostic thresholds (training) and performance evaluation (validation)," which was deemed insufficient on its own for demonstrating reasonable assurance of safety and effectiveness.
- The Second and Third Clinical Studies appear to serve as independent validation studies, utilizing similar methodologies but without the noted confounding factor of using the same data for training and testing. The second study used the final Sunrise sensor and was prospective, while the third was retrospective like the first.
Key takeaway on training data: While specific training set sizes are not provided, the first study implicitly indicates that some of its data (or data from a similar source) was used for "optimizing diagnostic thresholds (training)." The methods for establishing ground truth for any training data would align with the method used for the first study's ground truth, i.e., expert-scored PSG.
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(89 days)
This sunlamp product is intended exclusively for cosmetic tanning of the human skin, for one person at a time, at the age of 18 or above.
The primary technical components of sunlamp products are artificial sources of UV radiation (UV lamps) and a mechanical structure. UV lamps emit different UV-A and UV-B proportions of the UV radiation. The UV-A proportion primarily generates a superficial tan, which appears rapidly and is intensive but also fades more rapidly, the UV-B radiation is primarily responsible for more long-term tanning results.
The provided text is a 510(k) summary for the JK-Holding GmbH's Sunrise 6200 and Sunrise 7200 tanning devices. It focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study of the device's performance against specific acceptance criteria.
Therefore, many of the requested details about acceptance criteria, study methodologies, and performance metrics are not available in this document. The document describes the device, its intended use, and compares it to a predicate device in terms of technical characteristics and compliance with electrical/safety standards.
Here's an attempt to answer the questions based only on the provided text, noting where information is absent:
1. Table of acceptance criteria and the reported device performance
The document does not explicitly state "acceptance criteria" for performance in terms of cosmetic tanning effectiveness. Instead, it focuses on compliance with established safety and electrical standards and showing that the proposed device is technologically equivalent to a predicate. The "performance" reported is compliance with these standards and similar technical specifications.
| Parameter (Implied Acceptance Criteria) | Predicate Device (Sunrise 480) Performance | Proposed Device (Sunrise 6200/7200) Performance | Evaluation against Implied Criteria |
|---|---|---|---|
| Intended Use/Indications for Use | Cosmetic tanning of human skin for one person, age 18+ | Cosmetic tanning of human skin for one person, age 18+ | Identical (Meets criterion for equivalence) |
| Number of body lamps | 48 | 48 | Identical (Meets criterion for equivalence) |
| Watts (per lamp) | 200 | 200 | Identical (Meets criterion for equivalence) |
| Max exposure time [min] | 9 | 9 | Identical (Meets criterion for equivalence) |
| Electrical requirements | 230V 3Ø or 230V 2Ø | 230V 3Ø or 230V 2Ø | Identical (Meets criterion for equivalence) |
| Rated overcurrent protection device | 40A / 3-pole 3Ø or 70A / 2-pole 2Ø | 40A / 3-pole 3Ø or 70A / 2-pole 2Ø | Identical (Meets criterion for equivalence) |
| Number of wires | 4 3Ø or 3 2Ø | 4 3Ø or 3 2Ø | Identical (Meets criterion for equivalence) |
| Irradiance ratio in accordance with 1040.20 | Fulfilled | Fulfilled | Identical (Meets criterion for compliance) |
| Electrical safety (IEC 60601-1, UL 482, IEC 60335-2-27) | Compliant | Compliant | Identical (Meets criterion for compliance) |
| Electromagnetic compatibility (IEC 60601-1-2) | Compliant | Compliant | Identical (Meets criterion for compliance) |
| Total power consumption [Watts] | 11300 | 9500 | Similar: Less consumption, performance not impaired (Meets criterion for equivalence) |
| Lamp item description | GENESIS VHP12 Turbo Power - 200 W | GENESIS VHP9 Smart Performance 200 W | Different description, identical nominal wattage (Meets criterion for equivalence) |
2. Sample size used for the test set and the data provenance
The document mentions "Summary of performance testing" and indicates that "The proposed devices have been tested in respect to biocompatibility in accordance with the ISO 10993-series, electrical and mechanical safety in accordance with IEC 60601-1 and EMC in accordance with IEC 60601-1-2." and "The proposed devices are in compliance with U.S. performance standard 21CFR 1040.20." It also refers to "section 18 for bench test report" regarding irradiance ratio.
- Sample Size: Not specified for any of the tests. This refers to physical devices tested, not clinical data sets.
- Data Provenance: The tests are likely conducted in a lab setting by the manufacturer or a third-party testing facility. The manufacturer is based in Germany. The document is for submission to the U.S. Food & Drug Administration (FDA). The nature of these tests (safety, electrical, EMC) implies them to be prospective, laboratory-based tests on the devices themselves. No human or patient data is mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not applicable and not provided. The "ground truth" for this device relates to its compliance with technical standards (e.g., electrical safety, UV irradiance limits). This is measured through instrumental testing and adherence to published standards, not through expert human assessment of an outcome like a medical diagnosis.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
Not applicable and not provided. Adjudication methods like 2+1 or 3+1 typically apply to human interpretation of medical imaging or clinical cases where consensus is needed to establish ground truth for algorithm performance. For a tanning device, compliance is determined by instrumental measurements and adherence to 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
Not applicable and not provided. This is a tanning device, not an AI-powered diagnostic tool requiring human-in-the-loop studies.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
Not applicable and not provided. There is no mention of an algorithm or AI component in this device. The "performance" relates to the physical device's technical specifications and safety compliance.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The "ground truth" for the tests performed (biocompatibility, electrical safety, EMC, irradiance ratio) would be defined by the specifications and limits set forth in the referenced international standards (e.g., ISO 10993, IEC 60601-1, IEC 60601-1-2, 21 CFR 1040.20). Compliance is determined by direct physical measurement against these established benchmarks.
8. The sample size for the training set
Not applicable and not provided. This is generally a physical product, not a machine learning model. There is no mention of a training set.
9. How the ground truth for the training set was established
Not applicable and not provided, as there is no training set mentioned for this product.
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(167 days)
Sunrise scooters empower physically challenged persons by providing a means of mobility.
The Three Wheeled mid Range Scooter is a medium duty, conventional, rear whech drive, rigid frame power Vehicle. The armrests of the sear are adjustable. The seat may be repositioned from from to back and chair height can be adjusted up and down. There are many kinds of accessories that are commonly sold after market. These accessories include canopies, crutch holders, cup holders, baskers etc.
Like most scooters, the tiller and throttle controls are the user interface. They transfer the rider's intentions to command the device. When the control is activated, or moved out of neutral position, the motor brake is energized and released, allowing the scooter to move in the appropriate direction. When the activation device is released, the scooter slows to a stop and the motor brake is automatically reengaged. These dynamic "on command" brakes allow the user to stop by letting go of the activation device.
If the scooter looses power, the motor brake is automatically engaged and the scooter comes to a stop. To prevent the rider from becoming stranded, the scooter may be pushed. The design incorporates a "free wheel" device motor lock disengagement device. This device allows the drive train to be manually disengaged, enabling the scooter to be pushed. It should be noted that the scooter would not have electronic brakes when in the "free wheel" mode.
The controller is microprocessor based and program-able. It is pro-programmed at the manufacturer to meet Sunrise specifications. This controller is currently used on selected models of the Sunrise scooters under K880425. Drive characteristics that are pre set are:
forward/reverse acceleration forward speed
forward/reverse deceleration reverse speed
The controller also has manual reset circuit breakers. These adjustments and features are similar to all standard scooter controllers.
The provided text describes a 510(k) submission for a medical device, specifically a mobility scooter. However, it does not include the typical information one would expect for demonstrating the acceptance criteria and performance of an AI/ML device in a clinical study.
The document is a K981885 submission for a "Sunrise 3 Wheel Scooter" in 1998, which is a physical device, not an AI/ML software device. The "testing" section refers to engineering standards like ISO 7176 and RESNA for wheelchairs, covering aspects like stability, brakes, energy consumption, and EMC. The "efficacy" section refers to articles about power wheelchairs in general, not specific studies on this particular device's clinical efficacy in a statistical sense.
Therefore, I cannot fulfill the request to describe the acceptance criteria and a study proving the device meets those criteria, as the provided input does not contain information relevant to an AI/ML device's clinical performance assessment.
Here's a breakdown of why each requested point cannot be addressed with the given document:
- A table of acceptance criteria and the reported device performance: The document lists engineering tests (e.g., Static Stability, Dynamic Stability, Effectiveness of Brakes) and states that the device was tested to these standards. It doesn't present specific acceptance criteria values (e.g., "must stop within X feet at Y speed") and then reported performance values against them in a table format. These are design and safety standards, not clinical performance metrics for an AI/ML diagnosis/prediction.
- Sample sized used for the test set and the data provenance: Not applicable. This refers to engineering tests, not a clinical study on patient data.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No ground truth is established for patient data.
- Adjudication method for the test set: Not applicable.
- 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.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
- The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable.
- The sample size for the training set: Not applicable.
- How the ground truth for the training set was established: Not applicable.
In summary, the provided document details the regulatory submission for a physical medical device (a scooter) and focuses on engineering safety standards and comparisons to predicate devices, not on the clinical performance validation of an AI/ML algorithm.
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(88 days)
The Sunrise Curing Lamp is indicated for use in curing of composite resin materials for restoration of cavity preparation, curing of bonding materials, and any application where a conventional halogen curing lamp would be used.
The Sunrise Curing Lamp is a high intensity light source that is filtered and transmitted through a liquid optical fiber to the tooth for curing of composite resins.
The provided text describes a 510(k) submission for the Sunrise Curing Lamp, comparing it to a predicate device, the ADT 1000 Plasma Arc Curing System. However, the information provided focuses on technical specifications and substantial equivalence, not on the performance of the device against specific acceptance criteria in a clinical study as would be expected for a diagnostic AI/ML device.
Therefore, many of the requested items cannot be extracted directly from this document.
Here's an analysis based on the provided text, highlighting what is present and what is missing based on your request:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria (Inferred from Predicate) | Reported Device Performance (Sunrise Curing Lamp) |
|---|---|
| Curing Power Output: 270mW to 850mW | 400mW ± 50mW |
| Duration: 10 sec. to 25 sec. | Default 10 sec.; Adjustable 1 to 99 sec. |
| Optical Bandwidth: 430nm to 500nm | 420nm to 500nm |
| Light Source: Xenon short arc lamp | Xenon short arc lamp |
| Beam Delivery: Liquid Light Guide | Liquid Light Guide |
| Intended Use: Curing composite resins, bonding materials, etc. (same as predicate) | Indicated for use in curing of composite resin materials for restoration of cavity preparation, curing of bonding materials, and any application where a conventional halogen curing lamp would be used. |
Explanation of Inferred Criteria:
The document states, "Based on the favorable comparison of the technical performance specifications of the Sunrise Curing Lamp with the ADT 1000 Plasma Arc Curing Lamp, the company concludes that these substantially equivalent devices are safe and effective." This implies that the technical specifications of the predicate device serve as the de facto acceptance criteria for the new device. The Sunrise Curing Lamp's reported performance falls within or is comparable to these specifications, supporting its claim of substantial equivalence.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Not applicable / Not provided. This document describes a medical device (curing lamp), not a diagnostic AI/ML system that would typically undergo a study with a test set of data. The "study" here is a comparison of technical specifications to a predicate device.
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 / Not provided. No ground truth establishment by experts is mentioned, as this is a technical equivalence submission for a physical device.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable / Not provided.
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 is not an AI-assisted diagnostic device, so an MRMC study is not relevant to this submission.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable / Not provided. This is not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable / Not provided. For this type of device, the "ground truth" for proving effectiveness would likely involve material science testing on cured composite resins (e.g., hardness, bond strength) rather than clinical outcomes or diagnostic accuracy. However, this document relies on substantial equivalence to a predicate device based on technical specifications.
8. The sample size for the training set
- Not applicable / Not provided. No training set is mentioned as this is not an AI/ML device.
9. How the ground truth for the training set was established
- Not applicable / Not provided. No training set ground truth is mentioned.
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