(176 days)
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
| Parameter | Acceptance Criteria (Not explicitly stated in document) | Reported Device Performance (Implied by substantial equivalence) |
|---|---|---|
| Physiological Parameter Measurement: | Performance expected to be equivalent to predicate device | Acquire and log digital data and resistances for temperature, heart inter-beat-interval (IBI), gross motor activity, and ambient light intensity. |
| Data Logging Capabilities: | Performance expected to be equivalent to predicate device | Store data until downloaded to a PC. User-definable data collection algorithms, numbers of channels, and types of channels. Internal clock and event marker for time-stamping. |
| Physical Characteristics: | Defined values in Table 11 | - Size: 65x120x22 mm |
- 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.
§ 882.1845 Physiological signal conditioner.
(a)
Identification. A physiological signal conditioner is a device such as an integrator or differentiator used to modify physiological signals for recording and processing.(b)
Classification. Class II (performance standards).