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VitalSense® can be used in any setting where physiological body core and skin temperature are used to further the understanding of body function. The device can be used for simultaneous assessment of core body temperature, dermal surface temperature, or ambient temperatures that require logging of data over time with subsequent conversion, display, and analysis of the aforementioned parameters. VitalSense® may be used in any instance where quantifiable analysis of temperature data is desirable.

VitalSense® is a compact, ambulatory, physiological data logger. VitalSense® may be attached to the belt or worn in a shirt pocket. Up to ten telemetric sensors may be used with a single VitalSense® logger. The device senses and records physiological data and displays the data on its LCD screen. Recorded data may be transferred later to a PC for display and conversion for export to other programs.

Here's a breakdown of the acceptance criteria and study information for the VitalSense® device based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document does not explicitly state a "test set" in the context of clinical data or human subjects. The tests described are laboratory-based performance verification tests.

• Sample Size: For the stability test, the image description mentions "Two Temperature Probes" (Sensor 24 and Sensor 26). For linearity, the image description also refers to "Sensor_24" and "Sensor_26". The total number of devices or sensors tested across the entire evaluation is not specified beyond these two examples for illustration.
• Data Provenance: The data is generated from internal laboratory testing by Mini Mitter Co., Inc. (as indicated by "Mini Mitter Company has established criteria..." and "Mini Mitter has tested the accuracy..."). The country of origin is the USA, specifically Bend, Oregon, where the company is located. The study is prospective in nature, as it involves active testing of the device's performance.

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

Not applicable. The ground truth for these performance tests is based on objective, quantifiable measurements against established standards and calibration, not expert consensus or interpretation of medical data. The "ground truth" for temperature linearity is a "standard, NIST-traceable digital RTD thermometer."

4. Adjudication Method for the Test Set:

Not applicable. There is no adjudication method used for these non-clinical performance tests, as the results are numerical comparisons against defined thresholds.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No, an MRMC comparative effectiveness study was not done. The document describes engineering performance tests of the device itself (accuracy and stability of temperature measurement), not studies involving human readers or assessment of human interpretation with or without AI assistance.

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

Yes, the studies described are standalone performance evaluations of the device's ability to accurately and stably measure temperature. The device functions as a data logger, and the tests evaluate its fundamental measurement capabilities directly, without human intervention in the data acquisition or algorithmic processing during the test.

7. The Type of Ground Truth Used:

The ground truth used for these performance tests is based on:

• Reference Standards: For temperature linearity, a "standard, NIST-traceable digital RTD thermometer" served as the reference for ground truth.
• Defined Baseline/Stability: For temperature stability, the expectation of minimal drift over time (e.g., in a stable bath) serves as the ground truth.

8. The Sample Size for the Training Set:

Not applicable. This document describes the verification and validation of a finished device's performance, not the development or training of an algorithm using a dataset. The device is a physiological data logger, not an AI/ML algorithm that requires a training set in the typical sense.

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

Not applicable, as there is no training set for an AI/ML algorithm described.

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The Mini-Logger® Series 2000 (hereafter referred to as Mini-Logger) is a compact, lightweight, physiological data logger for monitoring heart rate, interbeat-interval (IBI), temperature, ambient light, and activity. The Mini-Logger® can be used in behavioral and circadian rhythm studies, sleep research, occupational health and sports medicine research, and obesity/weight loss studies. The device can be used for any assement of human heart rate or IBI, temperature, and activity that requires logging of data over time and an integrated analysis of the forementioned parameters. The Mini-Logger® may be used in any instance where quantifiable analysis of physiological data is desirable.

The Mini-Logger® Series 2000 is a compact physiological data logger whose physical size and appearance are similar to a small TV remote control. The Mini-Logger® is powered from two replaceable, non-rechargeable lithium cells. The Mini-Logger® is generally worn in the shirt pocket or on a belt using its optional soft pouch. Direct-wired probes used to sense the physiological data are plugged into one or more of the four available data input channels. The device acquires and logs digital data and resistances whose values represent the amplitudes of physiological signals. The physiological signals are temperature, heart inter-beat-interval (IBI), counts representing gross motor activity, and resistance representing ambient light intensity.

This 510(k) Premarket Notification document for the Mini-Logger® Series 2000 does not contain specific acceptance criteria or a detailed study proving the device meets acceptance criteria. The document focuses on demonstrating substantial equivalence to a predicate device (Vitalog HMS-5000) rather than presenting a performance study with defined acceptance metrics.

Therefore, many of the requested sections regarding acceptance criteria, study design, sample sizes, ground truth establishment, expert involvement, and comparative effectiveness studies cannot be extracted from the provided text.

Here's an assessment based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

• Weight: 125 grams
• Battery type: 3.6 volt lithium cells (2 each)
• Moisture susceptibility: Not water resistant
• Memory: 128 Kilobyte or 1 Megabyte
• Storage Temperature: -10 C to 50 C at 0-95% relative humidity
• Operating Temperature: 0 C to 40 C |
  | Compatibility: | Compatible with IBM-compatible computer for data download (Implied by substantial equivalence) | Communicates data with an IBM-compatible computer. |
  | Sensor Interface: | Ability to interface with specified sensor technologies | Accepts direct-wired probes for physiological data into four input channels; utilizes thermistor, Polar chest band with ECG skin electrode, motion-sensitive switch, and photoconductive sensor technologies. |

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

• Not provided. This document is a 510(k) submission focused on substantial equivalence, not a detailed clinical or performance study report. There is no mention of a specific "test set" in the context of device performance evaluation with a defined sample size or data provenance (e.g., country of origin, retrospective/prospective). The assessment appears to be based on a comparison of technical characteristics and intended use to the predicate device.

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

• Not applicable/Not provided. Since there's no described "test set" for performance evaluation, there's no mention of experts establishing ground truth or their qualifications.

4. Adjudication Method for the Test Set

• Not applicable/Not provided. Without a defined test set requiring ground truth, there is no adjudication method described.

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 Mini-Logger® is a physiological data logging device, not an AI-assisted diagnostic tool. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not relevant and was not performed or described.

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

• No, not in the context of an "algorithm" as typically conceived in AI/imaging. The device itself is a standalone data logger. Its performance is inherent in its ability to accurately acquire and record physiological signals according to its specifications and the principles of the sensors used. The 510(k) primarily assesses this standalone capability against a predicate.

7. The Type of Ground Truth Used

• Not explicitly stated in the context of a performance study. For a device like the Mini-Logger®, "ground truth" would typically refer to the actual physiological values (e.g., a reference thermometer for temperature, a gold-standard ECG for heart rate/IBI) used to calibrate and verify the accuracy of the device's sensors and logging. However, the document does not detail such calibration or verification studies with specified ground truth methods. The ground truth for this submission is implicitly the performance and established safety/effectiveness of the predicate device for the purpose of demonstrating substantial equivalence.

8. The Sample Size for the Training Set

• Not applicable/Not provided. This device is not an algorithm that uses a "training set" in the sense of machine learning.

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

• Not applicable. As above, there is no "training set" for this device.

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The Actiwatch-Score® is a compact, lightweight, wrist-worn activity monitor that can be used to analyze circadian rhythms, automatically collect and analyze data for sleep parameters, and assess activity in any instance where quantifiable analysis of physical motion is desirable. In addition, the Actiwatch-Score® has a built-in score pad that allows the subject to subjectively assign and enter a score from 0 to 9. The score pad can be used as a substitute or in addition to the traditional patient diary used in conjunction with activity monitoring.

The Actiwatch-Score® is a compact, wrist-worn, battery-operated activity monitor whose physical characteristics are similar to a small wristwatch. The monitor consists of the activity monitor itself and a disposable wrist band. The Actiwatch-Score® is intended for the measurement, storage, and analysis of body activity. The Actiwatch-Score® can be attached to the subject's limb and through the use of an accelerometer, motion of that limb is measured, the activity stored within the activity monitor. A computer program is used to set up the Actiwatch-Score® to collect data. This program is called Actiware-Sleep and runs on an IBM-compatible personal computer (PC). The major functions of Actiware-Sleep are to create a patient score schedule, program the device to collect data, retrieve the data from the activity monitor, display the data, and to store the data for future reference and comparison. The Actiwatch® Reader is a compact interface device that provides a communications link between the Actiwatch-Score® and the PC. The Actiwatch® Reader is connected to the serial communications port of the PC via a standard 9-conductor RS-232 cable. The Actiwatch-Score® utilizes a motion sensor known as an "accelerometer" to monitor the occurrence and degree of motion. This type of sensor integrates the amplitude and speed of motion and produces a small signal whose magnitude and duration depend on the amount of motion. The activity signals are amplified and digitized by the on-board circuit. This information is stored in memory on board the device as activity counts. In addition, the patient self-score data are stored as integer values within memory.

Acceptance Criteria and Study for Actiwatch-Score®

Here's an analysis of the provided text regarding the acceptance criteria and supporting studies for the Actiwatch-Score® device:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes two key performance aspects for the Actiwatch-Score® related to its new "score" feature:

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

• Sample Size:
  • Audible Signal Timing: "a device" (singular) was used.
  • Patient Score Recording Accuracy: "An Actiwatch-score" (singular) was used.
• Data Provenance: The studies appear to be prospective internal validation tests conducted by the manufacturer, Mini-Mitter Co., Inc. The country of origin is implicitly the USA, where Mini-Mitter Co., Inc. is located.

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

• No external experts are mentioned for establishing ground truth for these specific tests.
• For the audible signal timing test, the ground truth was established by a chronograph standard.
• For the patient score recording accuracy test, the ground truth was the manually entered scores by a tester.

4. Adjudication Method for the Test Set:

• None explicitly stated or implied. The tests relied on direct comparison to a timing standard (chronograph) or the known input of a score.

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

• No, an MRMC comparative effectiveness study was not done. The document focuses on the technical functionality of the device's new scoring feature, not on human-in-the-loop performance or comparison with human readers.

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

• Yes, the described tests are essentially standalone performance evaluations of the device's ability to accurately time its alerts and record user input. There is no human interpretation of data involved in the evaluation of these specific functionalities.

7. The Type of Ground Truth Used:

• Audible Signal Timing: Mechanical/digital standard (chronograph).
• Patient Score Recording Accuracy: Known user input/entered data.

8. The Sample Size for the Training Set:

• The document does not mention any training set or machine learning components for the described functionalities. The device's core function of sensing motion is based on an accelerometer, and the new score feature involves timing and data storage, which are deterministic operations.

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

• Since no training set is mentioned, this information is not applicable.

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The Actiwatch® is an ultra-compact, lightweight, wrist-worn activity and ambient light monitor that can be used to analyze circadian rhythms, automatically collect and score data for sleep parameters, and assess activity in any instance where quantifiable analysis of physical motion is desirable.

The Actiwatch® is a compact, wrist-worn, battery-operated activity monitor whose physical characteristics are similar to a small wristwatch. The monitor consists of the activity monitor itself and a disposable wrist band. The Actiwatch® is intended for the measurement, storage, and analysis of body activity. The Actiwatch® can be attached to the subject's limb and through the use of an accelerometer, motion of that limb is measured, the activity stored within the activity monitor. A computer program is used to set un the Actiwatch® to collect data. This program is called Sleepwatch and runs on an IBM-compatible personal computer (PC). The major functions of Sleepwatch are to program the device to collect data, retrieve the data from the activity monitor, display the data, and to store the data for future reference and comparison. The Actiwatch® Reader is a compact interface device that provides a communications link between the Actiwatch® and the PC. The Actiwatch® Reader is connected to the serial communications port of the PC via a standard 9-conductor RS-232 cable. The Actiwatch® utilizes a motion sensor known as an "accelerometer" to monitor the occurrence and degree of motion. This type of sensor integrates the amplitude and speed of motion and produces a small signal whose magnitude and duration depend on the amount of motion. The activity signals are amplified and digitized by the on-board circuit. This information is stored in memory on board the device as activity counts.

The Mini-Mitter Co., Inc. Actiwatch® 510(k) submission [K983533] describes a device developed for measuring, storing, and analyzing body activity. The primary study presented focuses on the device's sensitivity to motion and inter-device variation rather than a clinical effectiveness study with human subjects.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state formal "acceptance criteria" for performance that would typically be seen in more recent FDA submissions (e.g., minimum sensitivity, specificity, or accuracy percentages). Instead, it describes performance characteristics that were measured and compared to the predicate device.

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

• Sample Size for Test Set:
  • Motion Sensitivity: Not explicitly stated as a number of devices or repetitions. The test involved "programming the device to collect data on one-minute intervals" and then subjecting "the device" to uniform simple harmonic motion. It appears to be a single device test or representative test of the device model's capability. Attachment No. 1 would likely provide more details, but it is not included in the provided text.
  • Inter-device Variation: A sample of five devices was used.
• Data Provenance: The tests described appear to be conducted in a laboratory setting by the manufacturer, Mini-Mitter Co., Inc., for the purpose of demonstrating device performance. This would be considered retrospective in the context of the 510(k) submission, as the data was collected prior to market approval. The country of origin of the data is not explicitly stated but can be inferred as the USA, where the company is located.

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

This type of study did not involve human experts establishing ground truth. The assessments were technical performance measurements against known physical inputs:

• Motion Sensitivity: Ground truth was established by calculation from the physical setup – "From the rotational speed of the motor and the length of the lever arm, the maximum acceleration can be calculated." This is an objective, deterministic ground truth, not requiring human expert interpretation.
• Inter-device Variation: Ground truth was the controlled, known input motion applied to the devices, and the "ground truth" for comparison was the consistency of the readings among the devices.

4. Adjudication Method for the Test Set

Not applicable, as no human expert adjudication was involved in establishing the ground truth for these technical performance tests.

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

No, an MRMC comparative effectiveness study was not done. The submission focuses on the standalone performance characteristics of the device and its substantial equivalence to a predicate device, not on comparing human reader performance with and without AI assistance.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, the studies described are standalone performance assessments of the Actiwatch® device.

• The "Counts vs. motion" test assesses the device's ability to accurately measure motion (algorithm and hardware combined) against a physically controlled input.
• The "Variation between devices" test assesses the consistency of the device's measurements across different units.
  Both are focused purely on the device's inherent performance.

7. The Type of Ground Truth Used

• Motion Sensitivity: Objective, physically calculated maximum acceleration based on a controlled mechanical setup (simple harmonic motion).
• Inter-device Variation: Controlled, known input motion (implicitly, the same motion applied to all five devices). The "ground truth" here is the expectation of consistent readings for a given input.

8. The Sample Size for the Training Set

The document does not describe the use of a "training set" in the context of machine learning, as this device (from 1999) predates widespread use of AI/ML in medical devices requiring such sets. The Actiwatch® utilizes an accelerometer and on-board circuitry to amplify and digitize signals, storing them as "activity counts." This is a deterministic signal processing approach, not a learned algorithm.

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

Not applicable, as no training set for a machine learning algorithm was used.

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