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The Serenity Piezo and Serenity Thermocouple Sensors are intended to measure and limb movement and thermal respiratory flow signals, respectively, from a patient for archival in a polysomnography study.

The sensors are accessories to a polysomnography system which records and conditions the physiological signals for analysis and display, such that the data may be analyzed by a qualified sleep clinician to aid in the diagnosis of sleep disorders.

The Serenity Piezo and Serenity Thermocouple Sensors are intended for use on both adults and children by healtheare professionals within a hospital, laboratory, clinic, or nursing home; or outside of a medical facility under the direction of a medical professional.

The Serenity Piezo and Serenity Thermocouple Sensors are not intended for the life monitoring of high risk patients, do not include or trigger alarms, and are not intended to be used as a critical component of:

• an alarm or alarm system;
• · an apnea monitor or apnea monitoring system; or
• · life monitor or life monitoring system.

Serenity sleep sensors are intended to measure and output physiologic signals used for Polysomnography (PSG) or Sleep Studies. These devices are to be used as an accessory to compatible amplifiers.

Typical sleep amplifiers use sensors and electrodes to collect physiological signals to further digitize, and the amplifiers send these signals to a host PC.

Serenity sleep sensors are worn by the patient and connected directly to compatible inputs of an amplifier. The amplifier and related software then processes the signal for review by qualified practitioners to score polysomnograms and diagnose Sleep Disorders.

The Serenity Piezo Sensor uses an embedded piezo sensing element to detect the vibrations of snoring or to sense a patient's limb movement. The sensor outputs a signal which corresponds to movements of the limbs or snore vibrations. The Piezo sensor can be placed on the skin or worn in a heel strap.

The Serenity Thermocouple Sensor uses thermocouple wire that is ioined together to form sensing elements. Thermocouple junctions under each nostril and in front of the mouth output a signal which corresponds to the patient's thermal airflow. The Serenity Thermocouple sensor is available with an optional cannula hanger to aid in patient usability when worn with an airflow pressure cannula.

The Neurotronics Serenity Piezo Sensor and Serenity Thermocouple Sensors are medical devices intended to measure and output physiological signals (snore, limb movement, and thermal respiratory flow) for polysomnography studies. The provided text describes several non-clinical tests conducted to demonstrate the device's performance and safety.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the specific numerical sample size used for each individual test (e.g., "50 devices were tested"). Instead, it states "All samples passed the acceptance criteria" for electrical safety, piezo sensor verification, and thermocouple sensor verification. The reference device comparison also mentions "comparison testing shows equivalent performance."

• Sample Size: Not explicitly quantified. "All samples" is used consistently, implying a sufficient number were tested to be representative and satisfy the acceptance criteria.
• Data Provenance: The studies are non-clinical testing conducted by the manufacturer, Neurotronics, Inc. There is no mention of country of origin for the data or whether it was retrospective or prospective in the context of human patient data. These are engineering and performance validation tests, not clinical trials.

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

This section is not applicable as the tests described are non-clinical engineering and performance validations, not studies involving human interpretation or diagnosis. Therefore, there is no "ground truth" established by human experts in the context of the device's diagnostic performance. The ground truth for these tests is defined by the technical specifications and standards (e.g., signal level, resistance, tensile strength, ISO standards).

4. Adjudication Method for the Test Set

This section is not applicable as the tests are non-clinical and do not involve human interpretation or subjective assessment that would require adjudication. The results are objective measurements against defined technical criteria.

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 section is not applicable. The device (Serenity Piezo Sensor, Serenity Thermocouple Sensor) is a sensor that collects physiological signals, not an AI-powered diagnostic tool for interpretation by a human reader. Its function is to accurately measure and output signals, not to process them with AI or aid in human interpretation improvement.

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

This section is not applicable. The device is a sensor; it does not contain a standalone algorithm for diagnostic performance. It outputs raw physiological signals for analysis by a polysomnography system and qualified sleep clinician.

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

For the non-clinical tests described, the "ground truth" is based on:

• Technical Specifications: Defined parameters for signal level, electrical properties (dielectric strength, resistance), mechanical properties (connector retention, tensile strength, mating cycles).
• International Standards: ISO 10993 for biocompatibility and IEC 60601-1 for electrical safety.
• Reference Device Performance: The performance of the Serenity sensors was compared to established performance characteristics of predicate and reference devices, implying these established devices serve as a benchmark for "ground truth" equivalence in signal output.

8. The sample size for the training set

This section is not applicable. The device is a sensor, not a machine learning model. Therefore, there is no "training set" in the context of AI/ML development.

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

This section is not applicable for the same reasons as #8.

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The Serenity RIP and Serenity Body Position Sensors are intended to measure and output respiratory effort signals and body position, respectively, from a patient for archival in a polysomnography study. The sensors are accessories to a polysomnography system which records and conditions the physiological signals for analysis and display, such that the data may be analyzed by a qualified sleep clinician to aid in the diagnosis of sleep disorders.

The Serenity RIP and Serenity Body Position Sensors are intended for use on both adults and children by healthcare professionals within a hospital, laboratory, clinic, or nursing home; or outside of a medical facility under the direction of a medical professional.

The Serenity RIP and Serenity Body Position Sensors are not intended for the life monitoring of high risk patients, do not include or trigger alarms, and are not intended to be used as a critical component of:

• an alarm or alarm system;
• · an apnea monitor or apnea monitoring system; or
• · life monitor or life monitoring system.

Serenity sleep sensors are intended to measure and output physiologic signals used for Polysomnography (PSG) or Sleep Studies. These devices are to be used as an accessory to compatible amplifiers.

Typical sleep studies use sensors and electrodes to collect, digitize, and send physiological signals to a host PC.

Serenity sleep sensors are worn by the patient and connected directly to compatible inputs of an amplifier. The amplifier and related software then processes the signal for review by qualified practitioners to score polysomnograms and diagnose Sleep Disorders

The Serenity Body Position uses a 3-axis accelerometer to track the patient's body orientation; outputting a voltage which corresponds to one of 5 positions (sitting/upright, supine, prone, left-side, and rightside).

The Serenity RIP Sensor uses respiratory inductance plethysmography to output a waveform which corresponds to patient's respiratory effort. The patient wears an adjustable elastic belt which connects to the RIP driver, the RIP driver then connects to the host device. The Serenity RIP sensor is available for both thorax and abdomen. Thorax and abdomen versions are identical, except that they operate at different frequencies to avoid interference.

The provided text, K173868, details the 510(k) premarket notification for the Serenity Body Position Sensor and Serenity RIP Sensors. It focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed clinical study data with specific acceptance criteria and performance metrics for an AI-powered device. Therefore, a comprehensive answer to your request, particularly regarding AI-specific criteria, human reader improvement with AI assistance, and detailed ground truth establishment, cannot be fully extracted from this document as the device in question is a sensor, not an AI algorithm.

However, based on the information provided for the sensors, here's a breakdown of what can be inferred:

1. A table of acceptance criteria and the reported device performance:

The document doesn't provide acceptance criteria and reported performance in terms of clinical accuracy or diagnostic capabilities for the sensors themselves in a traditional table format with quantitative metrics. Instead, it demonstrates compliance with safety and performance standards and comparative performance to predicate devices.

2. Sample sizes used for the test set and the data provenance:

• Sample Size: The document mentions "All samples passed the acceptance criteria" for the safety, EMC, and specific sensor verification tests. However, it does not specify the exact number of samples (devices) used for these tests. It's common for these types of engineering verification tests to use a small, representative sample size (e.g., 3-10 units) rather than large clinical trial numbers.
• Data Provenance: The tests appear to be retrospective engineering verification and validation tests conducted by the manufacturer, Neurotronics, Inc. The document does not specify the country of origin for the data or testing other than being performed by the applicant (Neurotronics, Inc.) located in Gainesville, Florida, USA.

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/provided in the context of this 510(k) submission. This submission is for physical sensors that measure physiological signals (body position and respiratory effort) for archival in a polysomnography study. It is not an AI algorithm that performs an "analysis" or "diagnosis" by itself requiring expert consensus on ground truth for an AI test set. The sensors output raw signals, which are then analyzed by a "qualified sleep clinician." The expertise required is in the manufacturing and testing of medical devices to relevant standards, and the comparison is largely on technical specifications and intended use.

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

This is not applicable/provided. Adjudication methods are typically used in clinical studies where multiple human readers interpret medical images or data and their interpretations need to be reconciled to establish a ground truth or resolve discrepancies, particularly for AI algorithm validation. This document describes engineering and performance verification of physical sensors, not a clinical study involving human interpretation consensus.

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/provided. The device is a sensor, not an AI algorithm. Therefore, an MRMC study assessing human reader improvement with AI assistance is not relevant to this submission.

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

This is not applicable/provided. The device is a sensor, not an algorithm, and its output is explicitly stated to be "for archival in a polysomnography study" and for analysis "by a qualified sleep clinician." It is not a standalone diagnostic algorithm.

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

For the sensor performance tests, the "ground truth" is established by engineering measurements and compliance with specified physical and electrical parameters and industry standards. For comparative performance, the ground truth is simply the measured output of both the new device and the predicate device when subjected to the same inputs/conditions, demonstrating "equivalent performance." There is no mention of expert consensus, pathology, or outcomes data being used to establish ground truth for the sensor's direct output. The interpretation of the sensor data by a sleep clinician in a PSG study implicitly relies on established clinical ground truth for sleep disorders, but this is downstream from the sensor itself.

8. The sample size for the training set:

This is not applicable/provided. This device is a physical sensor, not an AI algorithm that requires a "training set."

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

This is not applicable/provided, as no training set for an AI algorithm is involved.

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The Sanuthera's Serenity device is indicated to provide a mean of sound enrichment therapy that is programmed by a hearing health care professional familiar with diagnosis and management of tinnitus as part of a personalized tinnitus management program to provide temporary relief from the tinnitus symptoms.

The target population is primarily the adult population over 18 years of age.

Sanuthera's Serenity is a device utilizing sound therapy as a means to mitigate the symptoms associated with tinnitus. The Serenity device works as a plug-in device to the uDirect2 bridge device, manufactured by a hearing- aid company Unitron and can be customized to a patient's tinnitus profile and then adjusted to his/her preference to play a number of sounds aimed at obscuring the ringing in the patient's ear and/or re-train patients to avoid focusing on the ringing, essentially “habituating” them away from the disease.

The process of providing tinnitus therapy occur a number of ways although the most popular are Tinnitus Retraining Therapy (TRT) and Tinnitus Masking (TM). In either case, the patient is provided with the Serenity device which is custom programmed. The patient is then taken through a process of multiple protocols to set filter and volume parameters via an onboard processing unit and an onboard digital band pass filter to slowly assist in the habituation to the tinnitus.

Associated Accessories:
• The Software that is utilized by an audiologist to customize, per patient's preference during the device fitting process, the sounds aimed at obscuring the ringing in the patient's ear and/or re-train patients to avoid focusing on the ringing.
• The Unitron's commercially available neck-worn uDirect2 bridge device with Unitron's Moxi Kiss Behind-the-Ear family hearing aids (K130494).
• The battery charger to simultaneously charge in parallel the batteries of the Serenity and the uDirect2 bridge device.

The provided text is a 510(k) premarket notification for a Tinnitus Masker device (Serenity). This type of document is submitted to the FDA to demonstrate that a medical device is substantially equivalent to a legally marketed predicate device.

Crucially, a 510(k) submission for a Class II device like a Tinnitus Masker, especially one cleared through substantial equivalence to a previously marketed device, often relies on demonstrating technological equivalence and safety and effectiveness through non-clinical performance data and comparison to the predicate, rather than new, extensive clinical studies with specific statistical acceptance criteria for a novel AI algorithm.

The document states:

• "The Serenity Tinnitus Masking Device did not conduct any performance testing on animals."
• "The Serenity Tinnitus Masking Device did not conduct any clinical testing."

It mentions "Software Verification and Validation Testing" but does not provide specific performance metrics, acceptance criteria, or a study design for a clinical performance study as would be typical for an AI-powered diagnostic device. The "performance data" section primarily discusses biocompatibility and software validation in general terms.

Therefore, many of the typical questions for AI acceptance criteria and studies (like sample size, number of experts, adjudication, MRMC studies, effect size, training set details) are not applicable to this specific 510(k) submission, as it does not rely on a clinical study demonstrating AI performance against a ground truth.

Based on the provided text, I cannot fill out the requested table and details because the device is a Tinnitus Masker, not an AI diagnostic device, and its 510(k) clearance is based on substantial equivalence to a predicate device, without new clinical performance studies.

However, I can extract the relevant information regarding the type of data presented and the basis for its clearance:

Summary of Acceptance Criteria and Study Information as Pertains to this 510(k) Submission (which is not an AI-driven device requiring clinical performance metrics):

Given that the device is a Tinnitus Masker – a sound therapy device – and not an AI diagnostic tool, the typical "acceptance criteria" for AI performance metrics (e.g., sensitivity, specificity, AUC) and associated studies (clinical trials comparing AI-assisted vs. unassisted performance) are not present in this document. The "proof" of the device meeting criteria relies on demonstrating substantial equivalence to an existing predicate device based on technological characteristics and safety considerations.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Not Applicable. No clinical test set data is presented in this 510(k) submission for performance evaluation. The device clearance relies on demonstrating substantial equivalence to a predicate based on existing technological and safety profiles, and non-clinical testing (biocompatibility, software validation).

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

• Not Applicable. No test set with ground truth established by experts is mentioned, as there were no clinical studies for performance.

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

• Not Applicable. No test set requiring expert adjudication is mentioned.

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. This is not an AI diagnostic device, and no MRMC study was conducted or required for this type of 510(k) clearance.

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

• Not Applicable. This is not an AI diagnostic algorithm. The device's "standalone" function is to generate sound, which is then customized and used by a healthcare professional as part of a patient's management program.

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

• Not Applicable. As no clinical performance study was conducted, there was no ground truth established for performance evaluation. The "ground truth" for the device's function is its ability to produce sounds according to specifications, which is verified through software and hardware testing, not clinical outcomes data in this submission.

8. The sample size for the training set:

• Not Applicable. This device is not an AI/machine learning model that requires a "training set" in the conventional sense. The "training" that occurs is the programming of the device by a healthcare professional according to a patient's individual needs.

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

• Not Applicable. See point 8.

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The Serenity Pro PSF™ System is an accessory for a compatible leqally marketed Laser or Intense Pulse Light System for use in hair removal. Its handpiece produces a negative pressure over the skin surface, just prior to the administration of the treatment beam through it.

The Serenity Pro PSF™ System is a device which has the ability to produce a vacuum at a level of 400-700 mbar. Suction can be delivered through its handpiece, which has a sapphire window at its distal end, to be positioned over the skin for laser or IPL treatment. When the PSF system is activated, the negative pressure results in the flattening of the skin of the treatment site. During the time duration of suction, the treatment beam of the laser or IPL is administered through the sapphire window of the handpiece, which is transparent and thermally conductive. The resultant tight mechanical contact produced by the PSF expels blood from the treatment site which enhances the light penetration of the laser or IPL in tissue as well as the removal of its heat from the skin. This can reduce the possibility of post treatment ervthema.

I am sorry, but the provided text does not contain information about acceptance criteria or a study proving device performance in the format requested. The document is a 510(k) summary for the Serenity Pro PSF™ System, which describes the device, its intended use, and its substantial equivalence to a predicate device for FDA clearance. It does not detail specific performance metrics, clinical study design, or results in the way you've outlined.

Therefore, I cannot populate the table or answer the specific questions about acceptance criteria, study details, sample sizes, expert qualifications, or ground truth establishment based on the provided text.

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The Serenity PSF™ (Pneumatic Skin Flattening) System is an accessory for a compatible legally marketed Laser or Intense Pulse Light System for use in hair removal. Its handpiece produces a negative pressure over the skin surface, just prior to the administration of the treatment beam through it.

The Serenity PSF™ (Pneumatic Skin Flattening) System is a device which has the ability to produce a vacuum at a level of 200-700 mmHg. Suction can be delivered through its handpiece, which has a sapphire window at its distal end, to be positioned over the skin for laser or IPL treatment. When the PFS system is activated, the negative pressure results in the flattening of the skin of the treatment site. During the time duration of suction, the treatment beam of the laser or IPL is administered through the sapphire window of the handpiece, which is transparent and thermally conductive. The resultant tight mechanical contact produced by the PSF expels blood from the treatment site which enhances the light penetration of the laser or IPL in tissue as well as the removal of its heat from the skin. This can reduce the possibility of post treatment erythema.

This 510(k) summary (K062589) describes the Serenity PSF™ (Pneumatic Skin Flattening) System, an accessory to compatible laser or Intense Pulsed Light (IPL) systems for hair removal. The document focuses on establishing substantial equivalence to a predicate device and does not contain detailed information about specific acceptance criteria or a comprehensive study demonstrating direct performance against such criteria.

Therefore, the requested information cannot be fully extracted from the provided text. However, based on the context of a 510(k) submission, we can infer some general aspects and state what is not present:

Missing Information:
The provided document does not include:

• A table of acceptance criteria and reported device performance.
• Sample sizes used for test sets.
• Data provenance (country of origin, retrospective/prospective).
• Number and qualifications of experts for ground truth.
• Adjudication method for the test set.
• Results from a multi-reader multi-case (MRMC) comparative effectiveness study, nor an effect size for human reader improvement with AI.
• Details on a standalone (algorithm only) performance study.
• The type of ground truth used (e.g., pathology, outcomes data).
• Sample size for the training set.
• How ground truth for the training set was established.

Analysis based on available information:

The document is a 510(k) summary, which aims to demonstrate that a new device is substantially equivalent to a legally marketed predicate device. This process typically focuses on comparing technological characteristics, intended use, and safety/effectiveness rather than presenting a performance study against predefined acceptance criteria for a novel algorithm's accuracy or efficacy.

Here's an attempt to answer the questions based on the limited information, primarily noting what is not provided:

1. A table of acceptance criteria and the reported device performance

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: Not specified in the provided document.
• Data Provenance: Not specified in the provided document.

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 specified. This document does not describe a study involving expert-established ground truth for a test set.

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

• Not specified. There is no mention of a test set requiring adjudication in this document.

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. The device is a pneumatic accessory for laser/IPL therapy, not an AI-assisted diagnostic or interpretative system. Therefore, an MRMC study comparing human readers with/without AI assistance is not applicable and not mentioned.

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

• No. This device is a physical accessory, not an algorithm, so a standalone algorithm performance study is not applicable.

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

• Not applicable in the context of an algorithm's "ground truth." The document describes the physical and functional aspects of the device in relation to its intended use (skin flattening, enhanced light penetration, reduced erythema for hair removal). Performance is gauged by these physical effects and the established safety of similar predicate devices.

8. The sample size for the training set

• Not applicable. As a physical device accessory, there is no "training set" in the sense of machine learning.

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

• Not applicable, as there is no training set for an algorithm. The "ground truth" for the device's claims would be based on engineering specifications, physical testing, and potentially clinical observation of its effects (skin flattening, blood expulsion, etc.) in a clinical setting, but these details are not provided beyond the functional description.

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