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The SLP OxSAT 100 Patient Oximeter Module is indicated for use in measuring and transmitting functional oxygen saturation of arterial hemoglobin (SpO2), pulse rate, and plethysmographic data to a compatible PSG and/or HST device. It is not intended for use with low perfused patients.

The SLP OxSAT 100 is a pulse oximeter module that photoelectrically determines the oxygenation of blood in a part of the body, based upon the sensor placement.

The OxSAT 100 contains the electronics to interface to an attached sensor. The red and infrared light are transmitted through oxyhemoglobin and are sensed in the photoelectric cell. The red and infrared light is absorbed in different amounts depending on the oxygenation of the blood.

The OxSAT 100 has the ability to determine both the percent of saturated hemoglobin and the pulse rate. It performs these functions on adult and pediatric patient populations. It is designed for measuring and transmitting functional oxygen saturation of arterial hemoglobin (SpO2), Pulse rate and plethysmographic data to compatible polysomnogram ("PSG") and/or home sleep testing ("HST") devices.

Pulse amplitude is not displayed. The OxSAT 100 is powered by the host monitor. The wavelength of red LED is 660nm and Infrared LED is 910 nm with maximum optical output power of less than 1 mW.

The OxSAT 100 Module is not intended for use with skin contact and, therefore, has not been tested for biocompatibility. The OxSAT 100 is either attached to the outside of a belt on the patient or is set off to the side of the bed. An extension cable might be used with the sensors to avoid skin contact.

The provide text describes the 510(k) premarket notification for the OxSAT 100 oximeter module and its substantial equivalence to a predicate device, the Nonin Model 4100. It focuses on the device's characteristics, intended use, and compliance with standards. It does not contain information about acceptance criteria, study methodologies for AI/ML performance, ground truth establishment for a test set, expert adjudication, or MRMC studies.

Therefore, I cannot fulfill the request to describe the acceptance criteria and the study that proves the device meets the acceptance criteria as it explicitly asks for details related to AI/ML device evaluation which are not present in the provided document. The document describes a traditional medical device (oximeter) and its performance testing against engineering and medical standards, not AI algorithm performance.

The document only states that "Testing to ensure clinical accuracy of the device in accordance with ISO 80601-2-61. This testing and results showed compliance to the standard." Without access to the specific details of the ISO 80601-2-61 standard and the test results, it is impossible to extract the requested information.

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The SleepStrip II is intended to measure apnea/hyponea events during sleep for the purpose of prescreening patients for sleep apnea syndrome. The device is intended to be used by adult patients as prescribed by a physician in either home, hospital or facility use settings.

The SleepStrip II is formed like a soft plastic "strip" or patch which is adhesively applied on the face under the nose for one night sleep. The SleepStrip II device comprises the following four main components: 1. Flexible body. 2. Sensor and signal acquisition and analysis hardware and firmware. 3. Battery as a power source. 4. A result display element. The SleepStrip II is designed to show a Sleep Apnea Syndrome (SAS) study results. It includes sensors, hardware and software to facilitate a sleep apnea screening study at the patient's home over one night sleep (under prescription). The SleepStrip II, detects and counts respiratory events (apneas and hypopneas) in real time.

The provided text does not contain detailed information about specific acceptance criteria for performance metrics or a comprehensive study demonstrating that the SleepStrip II meets these criteria. The document focuses on demonstrating substantial equivalence to a predicate device through a series of performance tests, rather than defining and proving specific quantitative acceptance criteria for a new device.

Here's a breakdown of what is available and what is missing:

The document states that the SleepStrip II is substantially equivalent to the cleared SleepStrip (K002135). The assessment of substantial equivalence relies on various performance tests and comparisons to the predicate device rather than defining new, specific acceptance thresholds for the SleepStrip II.

Missing Information:

• Specific Acceptance Criteria Table: The document does not provide a table of acceptance criteria with quantitative thresholds (e.g., specific accuracy, sensitivity, or specificity targets) and the reported device performance against those criteria.
• Sample Size for Test Set and Data Provenance: While performance testing is mentioned, the text does not specify the sample size used for any test set or the provenance of the data (e.g., country of origin, retrospective/prospective).
• Number and Qualifications of Experts for Ground Truth: There is no mention of experts being used to establish a ground truth for a test set, nor their number or qualifications.
• Adjudication Method: No adjudication method (e.g., 2+1, 3+1, none) is described.
• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: There is no indication that an MRMC study was conducted, nor any mention of human reader improvement with or without AI assistance.
• Standalone Performance Study: While "Software verification and validation" and "Bench tests /Performance testing" are mentioned, the document does not describe a formal standalone performance study with specific results. The focus is on verifying individual components and overall functionality.
• Type of Ground Truth Used: The nature of the ground truth (e.g., expert consensus, pathology, outcomes data) for any performance evaluation is not specified.
• Sample Size for Training Set: Since the device is not described as involving a learning algorithm that would require a "training set" in the typical machine learning sense, this information is not applicable and not provided. The development process seems more aligned with traditional embedded systems and signal processing.
• Ground Truth Establishment for Training Set: As above, this is not applicable given the apparent nature of the device's technology.

What is Reported Regarding Performance and Testing:

The document (Section 7.1.12 Performance Data & Substantial Equivalence in {1}) states:

• Objective: To demonstrate that the modified SleepStrip II "does not raise any new questions of safety and efficacy" compared to its predicate device, SleepStrip (K002135).
• Approach to Substantial Equivalence: The SleepStrip II is considered "substantially equivalent in all aspects, e.g., technological characteristics, mode of operation, performance characteristics, intended use, etc." to the predicate device.
• Performance Testing Categories: A series of performance tests were conducted, including:
  • Software verification and validation
  • Bench tests /Performance testing: Pressure Channel signal validity
  • Bench tests /Performance testing: Thermal Channel signal validity
  • Bench tests /Performance testing: Final Scoring Validity
  • Laboratory safety and EMC testing

These tests are described as having been performed to ensure the modified device's safety and efficacy are comparable to the predicate device. However, specific results or quantitative acceptance criteria for these tests are not disclosed in the provided text.

In summary, the provided information outlines the types of tests conducted to support substantial equivalence but lacks the detailed quantitative performance criteria and study results commonly found when a device's performance against specific acceptance criteria is being proven. The regulatory submission focuses on the argument of substantial equivalence to an already cleared device, rather than a de novo demonstration of performance against predefined thresholds.

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The RMX is a physiological data recorder intended to collect and record data from multiple physiological channels and additional auxiliary inputs from undesignated channels. It is indicated for use by or on order of a physician. The RMX is intended for use in a supervised (hospital) or unsupervised (home) environment.

The RMX is an ambulatory unattended recording device intended for the recording of sleep physiological data. The RMX functions exclusively as a data-recording device and is not intended to monitor Apnea or other vital signs in an intensive care unit or any other real time application. It is used by or on the order of a physician.

The RMX data recording device offers a platform for collecting multiple channels of physiological signals such as pulse rate, ECG, EEG, airflow, thoracic and abdominal respiratory effort, sounds intensity (i.e. noise due to snoring), body position and movements, leg movement, pulse oximetry or similar physiological signals. The data collection box is normally attached over the clothes of the patient's chest using the chest inductive effort sensor band made of clothing-standard woven elastic laces. The device may use its internal sensors, standard wired physiological sensors or several wireless sensors (not covered in this application) to match the specific needs of the patient.

Data collected is transferred on an SD memory card from the recorder to a PC at the physician's clinic, where it is converted into industry standard EDF format, after which it is analyzed by standard scoring software to generate a detailed final report with recommendations.

The RMX data recording device includes 3 software elements; 1) the SETUP part that runs on a PC and uploads the recorder setup parameters to the SD (secure digital) card as determined by the physician, 2) The Firmware operating the main and auxiliary CPU hardware which control the A/D conversion and storage of the data, and 3) the Post-Study Software which runs on a PC, reads the raw data file from the SD card as a single file and converts it into the industry standard EDF format suitable for input to analytical systems (see section 16 for software description).

This document describes the RMX Physiological Data Recorder, but it does not contain a typical acceptance criteria table with performance metrics and a study comparing those metrics against predetermined thresholds. Instead, it focuses on functional testing to ensure accurate data recording.

Here's an analysis of the provided information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or performance metrics in the way a diagnostic device might (e.g., sensitivity, specificity). The "acceptance criteria" can be inferred from the "FUNCTIONAL TEST" section, which describes the device's ability to accurately record signals.

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

• Sample Size for Test Set: Not specified. The description of the "FUNCTIONAL TEST" implies a single setup (a single device or system under test) where simulated signals were injected. It does not mention a "test set" of patient data or a specific number of tests.
• Data Provenance (country of origin, retrospective/prospective): Not applicable. The test involved "known simulated signals injected to its inputs," not real patient data.

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

• Number of Experts: Not applicable. The "ground truth" for the functional test was the "known simulated signals" that were injected into the device. The output was then compared to these known signals.
• Qualifications of Experts: Not applicable for establishing ground truth. The document mentions that the recorded signals are of "sufficient quality for later analysis by trained experts," but these experts are for downstream analysis, not for establishing the ground truth of the recording capability itself.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The functional test involved comparing the device's output to the "known simulated signals" (the ground truth). There's no mention of human adjudication in this technical verification process.

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

• Performed? No. The RMX is described as a "physiological data recorder," not an AI-powered diagnostic tool. The document focuses on its ability to accurately record data, not on the interpretation of that data by humans or AI. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this device's functional validation as presented.
• Effect Size: Not applicable.

6. Standalone (Algorithm Only) Performance Study

• Performed? Not applicable in the context of an "algorithm only" study for diagnostic performance. The device's primary function is recording, not automated interpretation or diagnosis. The "FUNCTIONAL TEST" describes the standalone performance of the recording system (hardware and firmware) in replicating input signals.
  • If "standalone performance" refers to the device's accuracy in recording data without human intervention, then the "FUNCTIONAL TEST" could be considered a form of standalone performance assessment. It confirms the device's ability to capture and store data correctly on its own.

7. Type of Ground Truth Used

• Type of Ground Truth: Known simulated signals. For the functional test described, the ground truth was the precisely known electrical signals injected into the RMX device's inputs.

8. Sample Size for the Training Set

• Sample Size: Not applicable. The RMX is a physiological data recorder, not a machine learning model that requires a training set. Its functionality is based on hardware design and firmware logic, not learned patterns from data.

9. How the Ground Truth for the Training Set Was Established

• How Established: Not applicable, as there is no training set for this type of device.

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SleepSense sensors provide a qualitative measure of a patient's physiological parameters for recording onto an FDA-cleared data acquisition system. Their target population: Children and adult patients who are screened during sleep disorder studies. Their environment of use is usually at a sleep laboratory or sometimes at the patient's home.

Monitoring various physiological parameters is standard practice in sleep disorder testing. Standard overnight recordings show, among others, traces of parameters like respiration movement, leg and arm movement, snoring sounds, respiration airflow and body position during sleep.

In order to record tracings showing these parameters, sensors are needed to convert the physiological parameter into an electrical signal. These sensors are very simple sensing elements like piezo-crystals that convert mechanical force or vibrations to an electrical signal. Other sensing elements may be thermocouples which generate a signal proportional to temperature, or gravity switches, that switch and electrical circuit on and off depending on their position.

In practice, these sensing elements are packaged in small, patient-friendly enclosures which are applied to the patient, and connected to the recording system via a long and flexible cable. There is no electrical contact of any kind between the sensors and the patient.

All signals received from the sensors are qualitative, and are only used to record the dynamic nature or existence of the physiological parameter recorded. A specially trained sleep technician called "scorer" reviews the overall recording in the morning following the study. The signals recorded, together with additional channels like EKG or EEG, are analyzed to arrive at a diagnosis of a sleep disorder like sleep apnea or insomnia.

This 510(k) summary for the SleepSense Sleep Sensors outlines the device's classification, intended use, and substantial equivalence to predicate devices. However, it does not include any specific acceptance criteria or details of a study demonstrating the device meets such criteria.

The document states:

• "No performance standards are specified for physiological sensors for sleep disorder testing."
• The manufacturer claims substantial equivalence because they are the OEM manufacturer for the predicate devices.

Therefore, I cannot provide the requested information regarding acceptance criteria and the study that proves the device meets them because this information is not present in the provided text.

Based on the provided text, I can only confirm the following:

• 1. A table of acceptance criteria and the reported device performance: This information is not provided.
• 2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not provided.
• 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 provided.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: 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: Not provided. The device is a sensor, not an AI system for clinicians.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as it's a sensor providing qualitative signals for human interpretation.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not provided.
• 8. The sample size for the training set: Not applicable, as it's a sensor without a "training set" in the context of an algorithm.
• 9. How the ground truth for the training set was established: Not applicable.

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The BiteStrip is generally indicated for use by orofacial pain professionals or dentists, to aid in the evaluation and management of nocturnal masticatory muscles activity disorders, which may be related to the patient's bruxism. temporomandibular disorder (TMD) or other oral function disorders during sleep.

The BiteStrip is intended as an aid in the evaluation of excessive nocturnal jaw muscle activity The device is generally indicated for use by orofacial pain professionals or dentists, to evaluate nocturnal masticatory muscle activity level. which may be related to the patient's braxism. temporomandibular disorder (TMD) or other oral function disorders during sleep.

The BiteStrip is a disposable diagnostic device. The device is intended for use in monitoring masseter muscle contractions during sleep. It is generally indicated for use by physicians to aid in the evaluation of the presence and severity of bruxism, to determine the need for treatment, and for treatment follow-up. The BiteStrip is specifically indicated to obtain a quantitative measure of masseter muscle contractions during sleep, which correlates with bruxism severity derived from formal sleep lab studies. The BiteStrip is intended for adult users during an overnight sleep episode, i.e., 4-6 hours.

The BiteStrip display gives an indication of muscle contraction severity as a single number, from 0 to 3 (Where 0 is very low count, and 3 is high count) depending on the total number of masseter muscle contraction episodes that the patient performs for the duration of the test. This number is referred to as the Bscore. While both Bscore and traditional bruxism score are very similar, and have good correlation, the terms differ because the bruxism score is measured using sleep lab EMG and additional physiological measures (not only EMG signals), while the Bscore is obtained by EMG analysis alone.

The provided text describes the BiteStrip device and its 510(k) summary, but it does not contain a detailed study report that proves the device meets specific acceptance criteria.

However, it does describe the device's intended use and mentions a correlation study without providing specific performance metrics or detailed methodology. I can extract the information that is present and note where information is missing.

Here's a breakdown of the requested information based on the provided text:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state acceptance criteria in the form of a table or specific measurable thresholds. It describes the device's output and how it correlates with bruxism severity.

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

The document does not specify the sample size used for any test set or the data provenance (e.g., country of origin, retrospective/prospective). It only refers to "formal sleep lab studies" without further detail.

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

The document does not specify the number or qualifications of experts used to establish ground truth for the test set. It mentions "formal sleep lab studies" as the source of "traditional bruxism score" used for comparison.

4. Adjudication method for the test set

The document does not specify any adjudication method used for the test set.

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

The document does not describe an MRMC comparative effectiveness study directly involving human readers' improvement with or without AI assistance. The BiteStrip is presented as a diagnostic device that outputs a "Bscore," not as an AI-assistant for human readers.

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

Yes, the BiteStrip appears to be a standalone device that provides an automated output (the Bscore) based on EMG analysis. The description states: "The BiteStrip display gives an indication of muscle contraction severity as a single number, from 0 to 3..." and "the Bscore is obtained by EMG analysis alone." This indicates standalone performance.

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

The ground truth used for comparison is the "traditional bruxism score" derived from formal sleep lab studies using sleep lab EMG and additional physiological measures.

8. The sample size for the training set

The document does not specify the sample size for any training set.

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

The document does not describe how the ground truth for a training set was established. It implies the device was developed to correlate with "traditional bruxism score" from formal sleep lab studies, which would serve as the reference.

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