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The NomadAir PMU810 is intended to record physiological signals acquired from a patient for archival in a sleep study. Data may be analyzed on dedicated polysomnography software running on a personal computer by a qualified sleep clinician to aid in the diagnosis of sleep-disordered breathing (SDB).

The NomadAir PMU810 is intended for use within a hospital, laboratory, clinic, nursing home, or patient's home.

The NomadAir PMU810 is intended for use on adults only under the direction of a physician or qualified sleep technician.

The NomadAir PMU810, or any accessory, does not include or trigger alarms, and is not intended to be used alone as, or a critical component of,

• an alarm or alarm system:
• an apnea monitor or apnea monitoring system; or
• a life monitor or life monitoring system.

The NomadAir PMU810 is a portable device that records physiological signals used for sleep studies. The device can be worn on the chest or the wrist and is attached to the patient using a RIP belt or a disposable strap comected directly to the patient also wears a pulse oximeter probe, a nasal cannula, and an optional sensor, such as a RIP belt, thermocouple, EMG electrode, or ECG electrode.

During the typical workflow of using the clinical user configures the device for a patient. The clinician will give the patient instructions on how to attach the device and send the unit and accessories home with the patient. Before going to bed, the patient will connect everything, then go to sleep. The Nomad Air records the signals from the sensors and saves the data to internal memory. The patient may perform up to 3 sleep studies before returning the device. Once the device, they can connect it to a PC using a USB cable and download the study for analysis.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

• Input Impedance: >= 20 MOhm
• Pressure Sensor Accuracy: +/- 1 cmH2O
• Sampling Rate: 250 Hz +/- 0.05%
• Battery Life: minimum of 24 hours
• RIP Driver Test: Peak to trough measurement > 750 uV for 1" deflection of belt

These are engineering and performance metrics, not clinical outcomes, expert consensus, or pathological findings.

8. The Sample Size for the Training Set

The provided text does not mention a training set because the device described, NomadAir PMU810, is a physiological signal amplifier and recorder. It does not appear to employ machine learning or AI algorithms that would require a distinct "training set" for model development. The performance testing focuses on its ability to accurately acquire and record physiological signals according to engineering specifications.

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

Since there is no mention of a training set, the method for establishing its ground truth is not applicable.

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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.

• Humidity Preconditioning
• Determination of Applied Part and Accessible Parts
• Legibility of Marking
• Durability of Marking
• Patient Leakage Current
• Dielectric Voltage Withstand
• Resistance to Heat
• Excessive Temperature
• Ingress of Liquids (IEC 60529)
• Cleaning, Disinfection and Sterilization of ME Equipment and ME Systems
• Enclosure Mechanical Strength (Push, Impact, Drop Test Hand-Held ME Equipment)
• Mold Stress Relief | "All samples passed the acceptance criteria." (for both Serenity Body Position Sensor and Serenity RIP Sensor). The document notes that predicate devices were not found to publish testing to a basic safety standard. |
  | Electromagnetic Compatibility (EMC) | Compliance with IEC 60601-1-2 (Medical Electrical Equipment - Part 1-2: General Requirements for Safety - Collateral Standard: Electromagnetic Compatibility) concerning:
• Radiated Emissions (CISPR11 ed5.0)
• Electro-Static Discharge Immunity Test (IEC 61000-4-2 ed2.0)
• Conducted, Radio-Frequency, Electromagnetic Immunity Test (IEC 61000-4-6 ed2.0)
• Power Frequency Magnetic Field Immunity Test (IEC 61000-4-8 ed2.0) | "All samples passed the acceptance criteria." (for both Serenity Body Position Sensor and Serenity RIP Sensor). The document notes that predicate devices were not found to publish testing for electromagnetic compatibility. |
  | Body Position Sensor Specific | The Serenity Body Position sensor is expected to accurately detect and output signals corresponding to 5 positions: Right Side, Left Side, Supine, Prone, and Upright (Sitting).
  It should also meet specified performance for:
• Position test
• Dielectric strength
• Transition and Hysteresis
• Output Impedance
• Operational Battery Life Calculation
• Dimensional Analysis
• Output Noise
• Connector Tests
• Strap Fasten/Unfasten Cycle
• Wire Construction Test
• Operational Battery Voltage Range Test | "All samples passed the acceptance criteria." The document notes that predicate devices were not found to publish testing details. Comparative testing showed "equivalent performance of the Serenity sensors and the reference devices, using the same host system configurations." |
  | RIP Sensor Specific | The Serenity RIP sensor is expected to accurately detect and output a waveform corresponding to respiratory effort.
  It should demonstrate performance equivalent to the predicate device in detecting respiratory effort from chest or abdomen movement. | Comparative testing showed "equivalent performance of the Serenity sensors and the reference devices, using the same host system configurations." |
  | Predicate Comparison | The Serenity Body Position Sensor and Serenity RIP Sensors should demonstrate substantial equivalence to identified predicate devices (Braebon Ultima Body Position Sensor and Ambu RIPmate for technical characteristics, and Neurotronics Polysmith Sleep System/Nomad Sleep System for overall intended use and integration as accessories). This implies similar physical, electrical, and environmental designs, and no new questions of safety or effectiveness. | The document concludes: "Based on the results of the Intended Use Comparison, the Technical Comparison, and Testing Data, it is believed that the Serenity Body Position Sensor and Serenity RIP Sensors present no new questions of safety and effectiveness and, are substantially equivalent to the identified predicate. Both sensors have similar physical, electrical, and environmental designs. Both share the same intended use." |
  | Biocompatibility | No toxic or irritating effects from patient contact. | "Not Applicable" for the regulatory submission, implying the materials are standard and well-understood for patient contact, or fall under a category where specific biocompatibility testing for this 510(k) was not deemed necessary for substantial equivalence given the context of a sensor accessory. The document notes that predicate devices were not found to publish biocompatibility information. |
  | Sterility | If applicable, the device should meet sterility requirements. | "Not applicable." The document notes that predicate devices were not found to publish sterility information. |

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 Polysmith Sleep System, Model NT17593 is intended to measure, amplify, and record physiological signals acquired from a patient for archival in a sleep study. The physiological signals are recorded and conditioned for analysis and display. The data may be analyzed in real-time or offline on dedicated polysomnography software running on a personal computer by a qualified sleep clinician to aid in the diagnosis of Sleep Disorders.

The Polysmith Sleep System, Model NT17593 is intended for use by healthcare professionals within a hospital, laboratory, clinic, or nursing home; or outside of a medical facility under direct supervision of a medical professional.

The Polysmith Sleep System, Model NTT7593 is intended for use on both adults and children only under the direction of a physician or qualified sleep technician.

The Polysmith Sleep System, Model NTT7593 includes automatic detection of some arrhythmias (including some potentially life threatening arrhythmias), however detection of an arrhythmia may be performed with 30 seconds or more delay, and is based on a single ECG lead only.

The Polysmith Sleep System, Model NTI7593, or any accessory, is not intended for the life monitoring of high risk patients, does not include or trigger alarms, and is not intended to be used alone as, or a critical component of,

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

The Polysmith Sleep System, Model NT17593 is intended to amplify and record physiologic potentials used for Polysomnography (PSG) or Sleep Studies. The device consists of a compatible amplifier, head box, PC, patient sensors, and may include optional external devices, USB DC Box, and audio/video input devices.

Compatible amplifiers may use commercially available sensors and electrodes, an internal SpO2 module, and internal pressure transducers to collect, digitize, and send physiological signals to the host PC.

The Polysmith software may record from video, speaker and microphone equipment. The Polysmith software may also record auxiliary signals from compatible amplifiers or USB DC Box which allow for data inputs from compatible sources.

Polysmith records and displays the data for online or offline review. Qualified practitioners use the information to score polysomnograms and diagnose Sleep Disorders.

Here's an analysis of the acceptance criteria and study as described in the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

(Note: The document states the new device is "comparable" to the BSM-9100A, which includes the "same algorithm." It does not explicitly list the acceptance criteria values for the BSM-9100A, but rather assumes that comparable performance to a device with a more critical intended use is sufficient.)

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

• Sample Size: Not explicitly stated as a number of patients or recordings. The document refers to the use of standard databases:
  • MIT: The Massachusetts Institute of Technology–Beth Israel Hospital Arrhythmia Database
  • AHA: The American Heart Association Database for Evaluation of Ventricular Arrhythmia Detectors
  • NST: The Noise Stress Test Database
• Data Provenance: The databases (MIT, AHA, NST) are widely recognized cardiological datasets. The document does not specify their country of origin for this particular study, nor whether the data was retrospective or prospective. Given they are established historical databases, they are inherently retrospective.

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

• Not explicitly stated in the provided text. The databases (MIT, AHA, NST) are widely recognized and have ground truths established by clinical experts during their creation. However, the document does not detail how this specific study confirmed ground truth for its testing or the number/qualifications of experts involved in the original ground truth creation of these databases.

4. Adjudication method for the test set:

• Not explicitly stated. Given the use of established databases, the ground truth annotations within these databases would have been created through expert consensus or established protocols, but the specific adjudication method for this particular study is not detailed.

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 with and without AI assistance was not conducted or described. The study focuses solely on the standalone performance of the algorithm against reference databases.

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

• Yes, a standalone algorithm-only performance evaluation was conducted. The tables provided show the "Polysmith Sleep System, NTI7593 (NEW)" performance metrics (Sensitivity, Predictivity, FPR) directly against the reference databases, without any mention of human-in-the-loop interaction. The document states: "The arrhythmia analysis results are to be reviewed by a qualified clinician and are not to serve as results for direct diagnosis or treatment of arrhythmia conditions. The arrhythmia analysis function is only to provide indicators for further investigation," which further reinforces its standalone, assistive role.

7. The type of ground truth used:

• The ground truth used is based on expert consensus annotations embedded within the standard, publicly available databases:
  • MIT: The Massachusetts Institute of Technology–Beth Beth Israel Hospital Arrhythmia Database
  • AHA: The American Heart Association Database for Evaluation of Ventricular Arrhythmia Detectors
  • NST: The Noise Stress Test Database

8. The sample size for the training set:

• Not explicitly stated. The document indicates that the "newly integrated algorithm is the same algorithm implemented in the reference device, BSM-9100A (K082785)," implying this algorithm was likely trained or developed previously, possibly using portions of these or other similar databases. However, the training set size specific to this submission for the Polysmith device is not provided.

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

• Not explicitly stated for this submission. Since the algorithm is adopted from the BSM-9100A, the ground truth for its original training would have been established during the development of that device or the algorithm itself, likely through expert annotation of ECG recordings, similar to how the ground truth for the testing databases was established. The document doesn't provide details on the development of this algorithm's ground truth.

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The device is intended to measure, amplify, and record physiological signals acquired from a patient for archival in a sleep study. The physiological signals and conditioned for analysis and display. The data may be analyzed in real-time or offline on dedicated polysomnography software running on a personal computer by a qualified sleep clinician to aid in the diagnosis of Sleep Disorders.

The device is intended for use by healthcare professionals within a hospital, laboratory, clinic, or nursing home; or outside of a medical facility under direct supervision of a medical professional.

The device is intended for use on both adults and children only under the direction of a physician or qualified sleep technician.

The device or any accessory, does not include alarms, and is not intended to be used as a critical component of an alarm system.

The device or any accessory, is not to be used alone as an apnea monitor or as a component in an apnea monitoring system.

The device or any accessory, is not to be used alone as a life support device or as a critical component of a life support system.

The Polysmith Sleep System, Model NTI6600 is intended to amplify and record physiologic potentials used for Polysomnography (PSG) or Sleep Studies. The device consists of a compatible amplifier, head box, PC, patient sensors, and may include optional external devices, USB DC Box, and audio/video input devices.

Compatible amplifiers may use commercially available sensors and electrodes, an internal SpO2 module, and internal pressure transducers to collect, digitize, and send physiological signals to the host PC.

The Polysmith software may record from video, speaker and microphone equipment. The Polysmith software may also record auxiliary signals from compatible amplifiers or USB DC Box which allow for data inputs from compatible sources.

Polysmith records and displays the data for online or offline review. Qualified practitioners use the information to score Polysomnograms and diagnose Sleep Disorders.

Here's a breakdown of the acceptance criteria and study details for the Polysmith Sleep System, Model NTI6600, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" as separate performance thresholds the device must meet. Instead, it presents the "Automated Analysis Agreement" as the device's performance, which is then compared against "Average Human Scoring Agreement." Assuming the implied acceptance is substantial equivalence to human performance for these metrics, the table is structured as follows:

In the "Additional Sleep Staging Analysis," which seems to be a more detailed analysis, the total agreement for automated scoring against consensus human scoring is:

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

• Sample Size (Automated Analysis): 8,053 recorded epochs, of which 7,606 were scored.
• Sample Size (Additional Sleep Staging Analysis): 20 sleep studies.
• Data Provenance: The studies were chosen at random from existing sleep studies of acceptable signal quality from accredited labs. For the automated analysis, studies were chosen at random from a sleep lab independent of Neurotronics. The document does not specify the country of origin, but given the FDA submission, it's likely US-based or compliant with US standards. The data is retrospective.

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

• Automated Analysis: Two expert scorers from different organizations. Each is a registered sleep clinician with at least 5 years' experience scoring sleep records.
• Additional Sleep Staging Analysis: Three independent scorers. Each is a registered sleep specialist with at least five years' experience in the field. Each had some prior experience using Polysmith to manually score studies.

4. Adjudication Method for the Test Set

• Automated Analysis: The document states "The human scoring was completed by two expert scorers." It then calculates "Average Human Scoring Agreement," implying an average of their individual scores or comparison. It doesn't explicitly describe an adjudication process for disagreements between the two human scorers to establish a single ground truth for direct comparison with the automated analysis. Instead, it compares the automated system's performance against this average human agreement, and also compares the two human scorers' agreement with each other.
• Additional Sleep Staging Analysis: This section explicitly used a majority method (2/3 majority-rule) to establish the "true sleep staging (consensus)." Epochs where there was no agreement among the human scorers were discarded (non-consensus).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, a direct MRMC comparative effectiveness study "with AI vs without AI assistance" was not explicitly described in the context of improving human reader performance. The study focused on the standalone performance of the automated analysis system compared to human scoring. While humans scored the data, the goal was to assess the device's accuracy relative to human experts, not to measure the improvement in human performance aided by the device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, a standalone performance analysis was conducted. The "Automated Analysis Agreement" and the "Results" section for "Additional Sleep Staging Analysis" directly report the performance of the algorithm itself against human expert assessments (either average or consensus). The scorers for the "Additional Sleep Staging Analysis" were explicitly provided with a version of Polysmith that "did not have any automated analysis capability," emphasizing that the human scoring served purely as ground truth.

7. The Type of Ground Truth Used

• Expert Consensus / Expert Scoring: For both analyses, the ground truth was established by human expert scorers. In the "Automated Analysis," it's based on two expert scorings. In the "Additional Sleep Staging Analysis," it's based on a 2/3 majority rule consensus of three expert scorers.

8. The Sample Size for the Training Set

• Not provided. The document states, "The studies used for this testing were not used to train the algorithm," but it does not specify the size or characteristics of the training set used for the algorithm's development.

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

• Not provided. The document focuses solely on the ground truth for the test sets and explicitly states the test sets were not used for training. Information on how the training data's ground truth was established is absent.

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The Innovative Neurotronics WalkAide External Neuromuscular Stimulator (WalkAide System) is intended to address the lack of ankle dorsiflexion in patients who have sustained damage to upper motor neurons or pathways to the spinal cord. During the swing phase of gait, the WalkAide System electrically stimulates the appropriate muscles that cause ankle dorsiflexion and may thus improve the gait in patients with chronic stroke. Medical benefits of Functional Electrical Stimulation (FES) may include prevention of disuse atrophy, increased local blood flow, muscle reeducation, and maintained or increased joint range of motion.

The WalkAide is an external functional electrical stimulator. It is a small device that attaches to the leg just below the knee, near the head of the fibula. During a gait cycle, the WalkAide stimulates the common peroneal nerve, which innervates the tibialis anterior and other muscles that cause dorsiflexion of the ankle. The WalkAide System consists of the WalkAide Patient Kit and the WalkAide Clinician Kit. The WalkAide Patient Kit comprises of all the components and accessories that the patient will take home and use. The Clinician System comprises the accessories that a clinician (i.e., orthotic specialist, physiotherapist, occupational therapist, etc.) will use to set up a patient's WalkAide.

Here's an analysis of the acceptance criteria and study information based on the provided document:

Acceptance Criteria and Device Performance

The document describes the WalkAide System and primarily focuses on extending its "Indications for Use" to specifically include chronic stroke patients for improved gait. Given that the device itself (hardware and software) is stated to be "identical to the predicate K123972" except for this indication, the acceptance criteria here are implicitly tied to demonstrating the device's effectiveness and safety for this expanded indication compared to a standard treatment.

The document doesn't present a specific table of quantitative acceptance criteria from the FDA for a new device, but rather a Comparison Conclusion Table (on pages 16-17) that highlights the identity of the current device to its predicate (K123972) in terms of technical specifications. The key acceptance is based on the clinical study supporting the new indication.

Implicit Acceptance Criteria (for the new indication) and Reported Device Performance:

Study Information:

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

   • Sample Size: The exact sample size is not explicitly stated in the provided document. It only mentions "a randomized trial utilized an unblinded, parallel group design."
   • Data Provenance: The document does not specify the country of origin. The study was a "randomized trial," which suggests it was prospective. Data analysis used "an intention to treat analysis with missing data points calculated using multiple imputations."

2. 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)

   • This information is not provided in the document. The study compared the device (WA) to an Ankle-Foot Orthosis (AFO) and measured "gait velocity, SIS composite score and safety." These seem to be objective and standardized outcome measures, rather than requiring subjective expert ground truth establishment for the test set.

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

   • This information is not provided in the document. Given the outcome measures (gait velocity, SIS score, safety), it's unlikely that an adjudication method for image interpretation or diagnosis was required.

4. 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 was not an MRMC comparative effectiveness study involving human readers and AI assistance. This was a clinical trial comparing a medical device (WalkAide) against a conventional treatment (AFO) in patients. The document does not mention human readers or AI assistance in the context of interpretation.

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

   • No. The WalkAide System is a functional electrical stimulator used by patients with setup and monitoring by a clinician. It is a human-in-the-loop device. The study itself was a clinical trial assessing patient outcomes with the device.

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

   • The "ground truth" for evaluating the device's effectiveness was based on clinical outcomes data, specifically:
     • Gait velocity
     • SIS composite score (Stroke Impact Scale or similar, implying a functional assessment)
     • Safety data

7. The sample size for the training set

   • This information is not applicable and therefore not provided. The WalkAide system is a hardware device (functional electrical stimulator) with accompanying software for configuration and analysis. It is not an AI/ML algorithm that is trained on a dataset in the typical sense. The study was a clinical trial to demonstrate effectiveness for an indication, not to train or validate an algorithm.

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

   • This information is not applicable for the reasons stated above. The device doesn't have a "training set" in the context of artificial intelligence. Its functionality is based on established principles of electrical stimulation and biomechanics. Its performance is validated through clinical trials.

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The Live View Panel is an accessory to EEG and PSG systems, intended to transmit EEG or PSG data to a remote location where the data can be viewed by a clinician to aid in diagnosis of epilepsies, sleep disorders, and other related disorders.

The Live View Panel is intended for use by medical personnel within a medical facility, clinic or nursing home, or outside a medical facility under the supervision of a medical professional. The Live View Panel is available for use on all patient populations, including adults and children as determined by the medical professional.

This device is not to be used to monitor life threatening situations.

This device is not to be used to control life supporting or life sustaining devices.

The Live View Panel (LVP) consists of several software components that allow remote viewing of digitized physiological waveforms and general patient information for the purpose of viewing EEG (electroencephalography) or PSG (polysomnography) patients in real time or in review. The software uses off-the-shelf and custom software components to manage multiple computer displays to facilitate the viewing of several patients simultaneously.

The Live View Panel consists of three software components. The Live View Panel Acquisition Interface Server (AIS) located on the acquisition system collects patient data from a recording machine and transmits this information over a network to a client machine. The Live View Panel client program receives this information and displays basic information in grid pattern along with other patients. The Live View Panel Monitor Controller program manages a bank of displays, each displaying a single patient. The Live View Panel grid mimics the physical locations of the monitors to allow the clinician manage and keep track of multiple patients displayed on the bank of displays.

The Live View Panel is software only and does not connect to the patient except through a cleared and currently marketed EEG or PSG device. A software module resides on the EEG or PSG device and sends patient data to a remote computer where another software module displays the data on an array of monitors. The software runs on off-the-shelf computers.

Regarding the Live View Panel (LVP) device:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document is a 510(k) summary for a software accessory (Live View Panel) rather than a diagnostic device that outputs numerical performance metrics against specific acceptance criteria. Therefore, there isn't a traditional table of "acceptance criteria" and "reported device performance" in terms of clinical accuracy (e.g., sensitivity, specificity, AUC).

Instead, the acceptance criteria for this type of device are centered on demonstrating substantial equivalence to predicate devices by meeting functional, technical, and safety requirements. The "performance" is primarily about fulfilling its intended use as a data display and management system.

Here’s a conceptual table based on the information provided, focusing on its functional equivalence:

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

The document states, "Testing Data Testing included: Software testing." This indicates that the "study" for this device was primarily software verification and validation testing. There is no mention of a clinical test set involving patient data for the LVP itself in a diagnostic performance context. The device's function is to display data from already-cleared EEG/PSG devices, so its "performance" is about accurate rendering and transmission, not interpretative diagnostic accuracy.

• Sample Size for Test Set: Not applicable in the context of clinical data for diagnostic performance. The testing was of the software itself.
• Data Provenance: Not applicable in the context of clinical data for diagnostic performance.

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

Not applicable. Since the "study" was primarily software testing to ensure correct display and transmission of data, there was no need for expert ground truth establishment for diagnostic purposes. The ground truth for software testing would be the expected output of the software functions (e.g., if a waveform is supposed to appear in a certain location with certain characteristics, it does).

4. Adjudication Method for the Test Set

Not applicable for the reasons stated above. Software testing relies on predefined specifications and expected outputs rather than expert adjudication of clinical findings.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of AI vs. Without AI Assistance

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed, nor would it be relevant for this specific device.

• The Live View Panel is an accessory for displaying existing EEG/PSG data; it is not an AI-driven diagnostic tool or an "AI assistant" that interprets data or makes diagnoses. Its purpose is to facilitate viewing, not to enhance human reader performance through AI.
• Therefore, there is no "effect size of how much human readers improve with AI vs without AI assistance" to report.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

No, a standalone performance study was not done.

• The Live View Panel is explicitly described as an accessory that facilitates human viewing of data. It does not perform any diagnostic or interpretive function independently ("algorithm only"). Its core function is to display data for a clinician.

7. The Type of Ground Truth Used

For the software testing that was performed, the "ground truth" would be the functional specifications and expected outputs of the software components. For example:

• Expected behavior of data transmission over a network.
• Expected graphical rendering of waveforms and patient information on various display configurations.
• Expected response to user interface interactions (e.g., changing parameters, adding events).

This is a technical "ground truth" rather than a clinical one (like pathology or expert consensus).

8. The Sample Size for the Training Set

Not applicable. The Live View Panel is a data display and transmission software, not a machine learning or artificial intelligence algorithm that requires a training set of data to learn patterns or make predictions.

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

Not applicable, as there was no training set for this device.

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The Innovative Neurotronics WalkAide External Functional Neuromuscular Stimulator (WalkAide System) is intended to address the lack of ankle dorsiflexion in patients who have sustained damage to upper motor neurons or pathways to the spinal cord. During the swing phase of gait, the WalkAide System electrically stimulates the appropriate muscles that cause ankle dorsiflexion and may thus improve the patient's gait. Medical benefits of Functional Electrical Stimulation (FES) may include prevention/ retardation of disuse atrophy, increased local blood flow, muscle re-education, and maintained or increased joint range of motion.

The WalkAide is an external functional electrical stimulator. It is a small device that attaches to the leg just below the knee, near the head of the fibula. During a gait cycle, the WalkAide stimulates the common peroneal nerve, which innervates the tibialis anterior and other muscles that cause dorsiflexion of the ankle. The WalkAide System consists of the WalkAide Patient Kit and the WalkAide Clinician Kit . The WalkAide Patient Kit comprises of all the components and accessories that the patient will take home and use. The Clinician System comprises the accessories that a clinician (i.e., orthotic specialist, physiotherapist, occupational therapist, etc.) will use to set up a patient's WalkAide.

The provided text describes a 510(k) summary for the Innovative Neurotronics, Inc. WalkAide System, which is an external functional neuromuscular stimulator. The summary focuses on demonstrating substantial equivalence to predicate devices, particularly regarding changes in output specifications (voltage, pulse width, and addition of ramp modulation).

Here's an analysis of the acceptance criteria and the "study" (which in this context refers to the technical comparison and testing described for regulatory approval):

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated in a quantifiable manner as "acceptance criteria" for a study in the typical sense of clinical trials. Instead, the document frames "acceptance" as meeting applicable safety and performance standards (like IEC 60601-2-10) and being substantially equivalent to predicate devices. The "reported device performance" refers to the technical specifications and measured values of the proposed WalkAide (K123972) and a comparison to its predicate (K052329) and other competitive devices (Bioness L300 Plus, Odstock Pace).

Below is a table summarizing key electrical output criteria and the proposed device's performance, as derived from the "Predicate Comparison Table" and the "Discussion of Table 6.1 equivalent parameters" section.

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The Nomad device is a digital amplifier capable of measuring bio-potential signals that may be incorporated into a Polysomnogram.

The device is intended to measure, amplify, and record physiological signals acquired from a patient for archival in a Sleep Study, such as Limb Movement, Respiration Effort, and SpO2. The data may be analyzed on dedicated polysomnography software running on a personal computer by a qualified sleep clinician to aid in the diagnosis of Sleep Disorders.

This device is not to be used alone as an apnea monitor or as a critical component in an apnea monitoring system.

This device is intended for use on both adults and children on the order of physician.

This device, or any accessory, is not to be used alone as a life support device or as a critical component of a life support system.

The device is not sterile.

Caution: Federal (USA) law restricts this device to sale by or on the order of a physician.

The device is intended to amplify and record physiologic potentials used for Polysomnography (PSG) or Sleep Studies. The bio-potentials are transferred to Polysmith polysomnography software running on a personal computer. Qualified practitioners use the information to score Polysomnograms and diagnose Sleep Disorders. The device is intended for use on both adults and children under the direction of a physician or qualified sleep technician.

The Neurotronics® Nomad device is a digital amplifier designed to measure, amplify, and record physiological signals for Polysomnography (PSG) or Sleep Studies. It aids qualified sleep clinicians in diagnosing Sleep Disorders by allowing analysis of data such as Limb Movement, Respiration Effort, and SpO2. This device is not intended as an apnea monitor or life support device.

Here's an analysis of the provided information regarding acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided document describes performance testing in general terms but does not present specific quantitative acceptance criteria values or detailed device performance metrics in a tabular format. Instead, it states that the device was verified and validated according to product specifications, and that test results confirmed the device is in accordance with its specifications.

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

The document does not specify a sample size for any clinical test set involving patient data. The performance and safety testing described pertains to device-level engineering and software verification/validation, not a clinical efficacy or performance study involving human subjects and diagnostic outcomes. There is no mention of data provenance (e.g., country of origin, retrospective or prospective) for a clinical test set.

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

Since no clinical test set involving human subjects for diagnostic accuracy is described, there is no information provided regarding the number of experts used or their qualifications for establishing ground truth. The device is a physiological signal amplifier, and its performance evaluation focused on its ability to accurately measure, amplify, and record signals, rather than its diagnostic capabilities per se.

4. Adjudication Method for the Test Set:

Given the nature of the described performance and safety testing (device-level engineering), an adjudication method for a clinical test set involving diagnostic outcomes is not applicable and not mentioned in the provided text.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted or described. The document focuses on the device's technical performance and safety, and its substantial equivalence to a predicate device, rather than its impact on human reader performance.

6. If a Standalone (Algorithm Only) Performance Study Was Done:

The Nomad device is described as a "digital amplifier" that measures, amplifies, and records physiological signals. The data is then analyzed by "dedicated Polysomnography software" and "a qualified sleep clinician." The document does not describe a standalone algorithm (i.e., AI or automated interpretation) within the Nomad device that would require an "algorithm only" performance study. The device's role is to acquire data for human interpretation using separate software. So, no standalone algorithm performance study was described or performed as it's not applicable to this type of device.

7. Type of Ground Truth Used:

For the device's performance testing (environmental, mechanical, electromagnetic, safety, and software verification), the "ground truth" was established by engineering specifications, industry standards (e.g., IEC 60601-1, 21 CFR Part 898), and internal product requirements. There is no mention of expert consensus, pathology, or outcomes data as ground truth for such testing.

8. Sample Size for the Training Set:

Since the Nomad device is a physiological signal amplifier and not an AI/machine learning diagnostic algorithm in the context of the provided text, the concept of a "training set" in the context of AI models does not apply. The described testing refers to verification and validation of hardware and software functions. Therefore, no sample size for a training set is provided.

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

As there is no training set for an AI/machine learning model described, this question is not applicable. The ground truth for the device's technical specifications and compliance was based on established engineering principles, regulatory standards, and internal product definitions.

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The device is intended to measure, amplify, and record physiological signals acquired from a patient for archival in a Sleep Study. The physiological signals are recorded and conditioned for analysis and display. The data may be analyzed in real-time or offline on dedicated polysomnography software running on a personal computer by a qualified sleep clinician to aid in the diagnosis of Sleep Disorders.

This device, or any accessory, is not to be used alone as an apnea monitor or as a component in an apnea monitoring system.

This device, or any accessory, is not to be used alone as a life support device or as a critical component of a life support system.

This device is intended for use on both adults and children only under the direction of a physician or qualified sleep technician.

The device is intended to amplify and record physiologic potentials used for Polysomnography (PSG) or Sleep Studies. The bio-potentials are transferred to Polysmith polysomnography software running on a personal computer. Qualified practitioners use the information to score Polysomnograms and diagnose Sleep Disorders. The device is intended for use on both adults and children only under the direction of a physician or qualified sleep technician.

This 510(k) summary for the Polysmith Sleep System (K062943) focuses on its substantial equivalence to predicate devices based on technological characteristics, safety, and performance standards, rather than clinical performance acceptance criteria based on a specific study. Therefore, much of the requested information regarding performance metrics, sample sizes, expert involvement, and ground truth types is not present in the provided document.

Here's an analysis of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide specific quantitative acceptance criteria related to a device's diagnostic performance (e.g., sensitivity, specificity for detecting sleep disorders) or a study reporting such performance. Instead, the "acceptance criteria" are implied through compliance with various safety and industrial standards.

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

The document does not describe a clinical test set with a specific sample size. The testing described focuses on device safety, electrical performance, and compliance with standards, rather than a clinical validation study involving patient data.

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

Not applicable, as no clinical test set requiring expert-established ground truth is described.

4. Adjudication method for the test set

Not applicable, for the same reason as above.

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 device is described as an amplifier and recorder of physiological signals for use in Polysomnography (PSG) by a qualified sleep clinician to aid in diagnosis. It is not an AI-driven diagnostic tool intended to supercede or augment human reading in the way an MRMC study would evaluate. It is a data acquisition device.

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

Not applicable. The device itself is not an algorithm performing diagnosis. It's a data capture system. Its "performance" is in accurately acquiring and conditioning physiological signals, not in interpreting them. That interpretation is explicitly stated to be done by a "qualified sleep clinician."

7. The type of ground truth used

For the safety and performance testing described, the "ground truth" would be the established requirements and limits set by the various industrial standards (e.g., maximum leakage current, electromagnetic interference limits, stress test resilience, accurate signal amplification).

8. The sample size for the training set

Not applicable. This document describes a medical device for data acquisition, not a machine learning model that requires a training set of data.

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

Not applicable, for the same reason as above.

Summary of the Study Proving the Device Meets Acceptance Criteria:

The provided 510(k) summary does not detail a single "study" in the sense of a clinical performance trial. Instead, it describes a comprehensive set of engineering, safety, and quality assurance activities that collectively demonstrate the device's adherence to its specifications and relevant regulatory standards.

The "study" comprises:

• Voluntary Compliance with Industrial Standards: The device underwent testing to ensure compliance with a range of international and national standards for medical electrical equipment (e.g., UL 60601-1, EN 60601-1-4, IEC 60601-2-26, CAN/CSA 22.2 No 601.1 M90, CISPR 11). These standards cover aspects like electrical safety, electromagnetic compatibility, and specific requirements for EEG/PSG devices.
• Quality System Compliance: The manufacturer's adherence to 21 CFR Part 820 (Quality System Regulation) and CAN/CSA-ISO13485:2003 (Medical Devices Quality Management Systems) ensures that the device was designed, manufactured, and tested under a robust quality management framework.
• Verification and Validation Activities: The device was "verified and validated according to the product specifications." This included:
  • Environmental and mechanical stress testing.
  • Electromagnetic immunity and emissions testing.
  • Medical device safety testing.
  • Software verification and validation according to its functionality.

The overall conclusion is that "The test results confirm that the device is in accordance with its specifications," thereby meeting the implicit acceptance criteria set by these standards and internal product requirements for a device intended to measure, amplify, and record physiological signals for Polysomnography. The device's substantial equivalence to predicates was based on similar indications for use, intended use, and technological characteristics, as well as adherence to these safety and performance standards.

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