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510(k) Data Aggregation
(329 days)
The ActTrust is an ultra-compact, lightweight, wrist-worn activity, temperature and ambient light monitor that can be used to analyze circadian rhythms, automatically collect and store data for sleep parameters, and assess activity in any instance where quantifiable analysis of physical motion is desirable. The device is intended to monitor limb or body movements during daily living and sleep. ActTrust is indicated for adults of 22 years of age and over.
ActTrust is a compact, ambulatory, battery-operated data recorder with physical characteristics similar to a small wristwatch. The ActTrust is intended for the acquisition and analysis of the physical activity of the body, peripheral temperature and light exposure during daily living and sleep. The ActTrust uses state of the art miniature electronic technology to measure the data and store these data within the device. The ActTrust require operational software to allow configuration, data download, storage and off-line analysis of activity data by a health care provider. The device is connected directly by means of a standard Universal Serial Bus connection for configuration and download.
The ActTrust device is an activity, temperature, and ambient light monitor designed to analyze circadian rhythms, collect sleep parameters, and assess physical movement.
Here's an analysis of the acceptance criteria and study proving the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance:
| Requirement Summary | Pass/Fail Criteria | Test Result |
|---|---|---|
| The device shall measure linear acceleration with an accuracy of +/-5% over the full range. | The recorded acceleration over the test range shall meet the requirement. | PASS |
| The device accuracy shall be <= +/-5% at the calibration point (i.e. 1g). | The variation in calibration values shall meet or exceed the requirement. | PASS |
| The device shall have a frequency response of 0.5 to 12.5 Hz. | The frequency response shall meet the requirement to within +/-10%. | PASS |
| The device shall output zero counts when no physical stimulus is applied. | The device shall record zero for the period of no physical stimulus. | PASS |
| The light sensor shall have an accuracy of +/-7.5% over the stated range. | The device shall meet the requirement, however it is acceptable that the accuracy worsens as light level increases. The accuracy over particular ranges shall be specified in the IFU. | PASS |
| The device shall output zero lux when the sensor is in total darkness | The device shall record zero lux for the test-period. | PASS |
| The device shall recover from unexpected reset events and/or total loss of power with no effect on the stored data. | No loss of function/data shall occur following the multiple reset events. | PASS |
| The Thermistor shall have an accuracy of +/- 0.5°C over the stated range. | The temperature must be between the specified range | PASS |
These acceptance criteria were established to verify the performance parameters of the device's main sensors (accelerometer, light sensor, and thermistor) and its data integrity under various conditions.
2. Sample Size Used for the Test Set and Data Provenance:
The document states, "To verify the performance of the ActTrust a sample of devices were subjected to a suite of bespoke tests to verify each performance parameter." However, the specific sample size (number of devices) used for this test set is not explicitly stated.
The data provenance is not mentioned (e.g., country of origin, retrospective or prospective). The tests were conducted internally by the manufacturer ("bespoke tests").
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts:
This information is not provided. The document describes a series of technical performance tests comparing the device's output against known inputs or established reference points, rather than a study requiring expert interpretation of results to establish ground truth.
4. Adjudication Method for the Test Set:
An adjudication method is not applicable and not mentioned. The tests are objective measurements against defined criteria (e.g., "The recorded acceleration over the test range shall meet the requirement").
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size:
No MRMC comparative effectiveness study was mentioned or performed. This device is a sensor for collecting activity data, not an AI-assisted diagnostic tool that would typically involve human readers.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:
Yes, a standalone performance assessment was done. The performance testing described in Table 5.4 focuses on the device's sensors and data recording capabilities independent of human interpretation. For example, testing the accuracy of the accelerometer, light sensor, and thermistor involves comparing the device's output to known reference values, without any human-in-the-loop component for the measurement itself. The device's operational software is mentioned for "off-line analysis of activity data by a health care provider," but the performance criteria listed are for the raw data acquisition.
7. The Type of Ground Truth Used:
The ground truth used for these tests was based on known physical inputs and calibrated reference measurements.
- Linear Acceleration: Simulated reference acceleration.
- Calibration Point (1g): Comparison to random samples of calibration records to examine inter-device variation, implying a known 1g reference.
- Frequency Response: Fixed acceleration over a range of frequencies.
- Zero Counts: No physical stimulus applied (known zero motion).
- Light Sensor Accuracy: Simultaneously using a calibrated light meter.
- Zero Lux: Sensor covered with fully opaque tape (known total darkness).
- Thermistor Accuracy: Devices placed in a climatic chamber with a ramp curve on the temperature (known temperature changes).
8. The Sample Size for the Training Set:
This information is not applicable and not provided. The ActTrust is described as a data collection device with embedded sensors; the provided documentation focuses on its hardware performance and does not describe it as an AI/machine learning device that would typically have a "training set" for an algorithm.
9. How the Ground Truth for the Training Set Was Established:
This information is not applicable and not provided, as no training set for an AI/ML algorithm is described.
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