(349 days)
The Vitls Platform is a wireless remote monitoring system intended for use by healthcare professionals for continuous collection of physiological data in in healthcare and home settings. This includes heart rate (HR) and body tomperature.
The data from the Tego VSS Sensor is intended for use by healthcare professionals as an aid to diagnosis and treatment. It is not intended for use on critical care patients nor replace standard monitoring and/or rouance care,
The device is intended for use as a general patient monitor, to provide physiological information, on patients who are 2 years of age or older.
The Vitls Platform is a wireless multi-parameter vital signs monitoring system. The Vitls Platform was developed to include an Application Programming Interface (API) which is intended to allow development of user interface applications, enabling clinicians and medically qualified personnel to access recorded vital signs information for respective analysis only, not for active patient monitoring. The Vitls Platform consists of: Wearable device with multiple sensors (the Tego VSS Sensor – An Adhesive Patch with integrated Sensors) The Secure Server Library (Cloud-based, including an API) The Vitls App (accessible on a smartphone, tablet, PC or monitor that displays the data and configures the Tego VSS Sensor)
The Tego VSS Sensor is a battery-operated adhesive patch with integrated sensors and wireless transceiver which is worn on the upper body and records heart rate and body temperature. There are two different sizes, one for adult and one for pediatric patients, they are 140 cm and 80 cm in length of the flexible portion of the sensor, respectively. The Tego VSS Sensor continuously gathers multiparameter vital signs data from the person being monitored and then transmits the encrypted data via bi-directional communication to the third-party connectivity relay, when in range. When not in range, the collected data is stored on the Tego VSS Sensor (for a maximum of 3 hours) and transmitted when a connection with the third-party connectivity relay has been restored. The encrypted wireless data recorded by the Sensor is sent, by the third-party connectivity relay, to the Secure Server. The data may be downloaded from the Secure Server Library or integrated into a Third-Party Application via the APIs of the Secure Server Library. In addition, the wireless data may be transferred to an optional Secure Server Library where they may be stored for future analysis.
The provided text describes the Vitls Platform, a wireless remote monitoring system that continuously collects physiological data, specifically heart rate and body temperature. The document is an FDA 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than proving novel clinical effectiveness through extensive clinical trials for new AI/ML devices. Therefore, the information regarding acceptance criteria and performance studies is primarily focused on engineering and functional validation against established standards and predicate device performance for the cleared device.
Based on the provided text, here's a breakdown of the requested information:
1. A table of acceptance criteria and the reported device performance
The document does not present a formal table of quantitative acceptance criteria for clinical performance (e.g., sensitivity, specificity, or accuracy metrics typical for AI/ML diagnostic devices) for the entire Vitls Platform beyond the temperature accuracy specification. Instead, it focuses on demonstrating compliance with recognized consensus standards and performance in comparison to predicate devices, particularly for heart rate and temperature measurements.
| Parameter | Acceptance Criteria (from text) | Reported Device Performance (from text) |
|---|---|---|
| Heart Rate | - Implied: Performance comparable to predicate device (Isansys Patient Status Engine) & FDA cleared patient monitor (GE Dash 5000). | - "The heart rate feature of the Vitls Platform was compared to the values acquired by an FDA cleared patient monitor, the GE Medical Systems Information Technologies Dash 5000 Patient Monitor (K073462) providing objective evidence that the design outputs for the design inputs as defined in the test protocol have been met with the required confidence and reliability and that there is no greater bias observed in a particular measurement interval." |
| Body Temperature | - Accuracy: ± 0.3° C (from table) | - Reported as: "± 0.3° C" (Explicitly stated in the table comparing to Fever Scout). |
| Biocompatibility | - Compliance with ISO 10993-1, 10993-5, and 10993-10. | - "Biocompatibility testing per ISO 10993-1, 10993-5 and 10993-10 demonstrate that the two patient contacting materials are biocompatible." |
| Electrical Safety | - Compliance with IEC 60601-1 and IEC 60601-1-11. | - "Electrical safety testing per IEC 60601-1 shows that the device meets the relevant requirements for electrical safety." |
- "Electrical safety testing per ISO 60601-1-11 shows the device meets the relevant requirements for devices used in home healthcare environment." |
| Software V&V | - Demonstrated performance as intended. | - "Software V&V demonstrates that the device performs as intended." |
| EMC | - Compliance with IEC 60601-1-2, FCC Part 15, Subpart B, Class B, RF Exposure Evaluation per 47 CFR 2.1091 and 2.1093, wireless coexistence per ASNI C63.27.2017, and RF Testing per FCC Part 15, Subpart C, 15.247. | - "Electromagnetic compatibility testing showed the device met the requirements of IEC 60601-1-2, FCC Part 15, Subpart B, Class B, RF Exposure Evaluation per 47 CFR 2.1091 and 2.1093, wireless coexistence per ASNI C63.27.2017 and RF Testing per FCC Part 15, Subpart C, 15.247." |
| Clinical Thermometer Performance | - Compliance with ISO 80601-2-56. | - "Compliance with ISO 80601-2-56 regarding performance of clinical thermometers for body temperature measurement." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document does not explicitly state the sample size (number of subjects/patients) for the heart rate and temperature comparison studies, nor does it specify the country of origin of the data or whether the studies were retrospective or prospective. It only mentions a comparison against an FDA cleared patient monitor for heart rate and compliance with a standard for temperature. This level of detail is typically not required for 510(k) substantial equivalence claims for monitoring devices unless there are novel clinical claims or significant technological differences.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
This is not applicable in the context of this device and study. The ground truth for physiological measurements like heart rate and temperature is typically established directly by reference devices (e.g., FDA-cleared patient monitors or calibrated thermometers) or established clinical methods, not by expert human readers/reviewers in the same way it would be for image-based diagnostic AI.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. Physiological measurements are directly compared to reference devices, not subject to human adjudication.
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 MRMC comparative effectiveness study was done. This type of study is more common for diagnostic AI/ML algorithms that assist human interpretation of complex data (e.g., medical images). The Vitls Platform is a physiological monitoring device, not a diagnostic AI intended to assist human readers in interpreting readings.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Yes, a form of "standalone" performance was effectively assessed for the core physiological measurements. The device's heart rate and temperature measurements were compared directly against established reference methods/devices (GE Dash 5000 for HR, and compliance with ISO 80601-2-56 for temperature), without an explicit human-in-the-loop component being evaluated. The device itself is intended for continuous collection of physiological data for healthcare professionals to use as an aid, meaning the algorithm is providing the base measurements that healthcare professionals use.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The ground truth for heart rate and temperature measurements was established by comparison to established, FDA-cleared reference devices/methods (e.g., GE Medical Systems Information Technologies Dash 5000 Patient Monitor for heart rate, and compliance with ISO 80601-2-56 for body temperature measurements, which would imply a validated reference thermometer).
8. The sample size for the training set
The document pertains to a 510(k) submission for a physiological monitoring device, not a machine learning or AI-driven diagnostic device in the modern sense that typically involves extensive training datasets. While the "Vitls Platform" might have some algorithmic processing for its physiological signal acquisition (e.g., PPG signal processing for heart rate), the document does not discuss a discernible "training set" in the context of machine learning. The validation described is more akin to traditional medical device testing for accuracy, reliability, and safety against known standards and predicate devices.
9. How the ground truth for the training set was established
Not applicable, as a distinct "training set" and associated ground truth establishment process for machine learning are not detailed or implied by the provided 510(k) summary for this device.
§ 870.2910 Radiofrequency physiological signal transmitter and receiver.
(a)
Identification. A radiofrequency physiological signal transmitter and receiver is a device used to condition a physiological signal so that it can be transmitted via radiofrequency from one location to another, e.g., a central monitoring station. The received signal is reconditioned by the device into its original format so that it can be displayed.(b)
Classification. Class II (performance standards).