(324 days)
The Alio Medical Remote Monitoring System is a wireless remote monitoring system intended for use by healthcare professionals to intermittently collect physiological data in home use settings. The data includes skin temperature, auscultation sound data and heart rate. Data is transmitted wirelessly from the SmartPatch wearable sensor to a web-based portal for the healthcare provider's (HCP) review.
The Alio Medical RMS is intended for use on general care patients who are 18 years of age or older. The SmartPatch sensor is indicated to measure skin temperature and pulse rate where clinically indicated. The SmartPatch sensor is indicated to record and transmit auscultation sound data where clinically indicated.
The device is not intended for use in critical care or other high-acuity environments. The Alio Medical RMS is a secondary, adjunct patient monitor and is not intended to replace existing standard-of-care patient monitoring practices.
Alio Medical Remote Monitoring System, or "Alio Medical RMS", utilizes a wearable device (SmartPatch) on the skin to gather physiological data and then transmits it to a device (Bedside Hub) located in the subject's home. The Bedside Hub then relays this raw data to the Alio Medical Cloud where it is processed and analyzed using Alio's proprietary algorithms. Data is accessible to Healthcare Professionals and the Alio clinical team via a web-based Clinician Portal. The SmartPatch and Bedside Hub are intended to be used on general care patients who are 18 years of age or older in a non-clinical environment. The web-based Clinical Portal is to be used by healthcare professionals in an office environment.
The Alio Medical Remote Monitoring System includes the following components:
- SmartPatch
- Bedside Hub
- Alio Medical Cloud (backend only - not user facing)
- Clinician Portal
SmartPatch: A flexible, silicone-encased patch that can be worn where clinically indicated for up to seven days at a time. It houses numerous sensor technologies, which include a microphone, accelerometer, temperature sensors, and a PPG sensors collect physiological data including skin temperature, auscultation sound data, and heart rate. Data is transmitted to the Cloud, via the Hub, where it is analyzed and sent to a Healthcare Professional via the Web Portal.
Bedside Hub: The Bedside Hub has the form and finish of an at-home device. It automatically communicates with the activated SmartPatch and uploads physiological data to the Alio Medical Cloud.
Alio Medical Cloud: The Cloud features a database that supports storage, analytics, system monitoring and visualization capabilities. The Alio Medical Cloud is encrypted and HIPAA compliant. All patient data is fully traceable to device and patient ID via the database.
Clinician Portal: The Clinician Portal is the interface tool between a user (healthcare professional users only) and the system that enables the user to visualize and interact with data being generated by the system.
The provided text is a 510(k) summary for the Alio Medical Remote Monitoring System. It details the device's indications for use, components, and a comparison to predicate and reference devices, as well as listing compliance with various safety and performance standards. However, it does not contain the specific acceptance criteria or the study data that proves the device meets those criteria.
The section titled "9. Performance Data" states that "Nonclinical verification and validation test results established that the device meets its design requirements and intended use, that it is as safe, as effective, and performs as well as the predicate devices, and that no new issues of safety and effectiveness were raised." It also mentions "extensive safety and performance testing as shown in the test results provided in this submission."
Despite these statements, the actual acceptance criteria, reported device performance (e.g., accuracy metrics for heart rate or temperature), sample sizes, ground truth establishment, or details of a multi-reader multi-case study are not included in this summary. The summary focuses on regulatory compliance and substantial equivalence argument rather than detailed performance study results against specific criteria.
Therefore, I cannot populate the requested table and answer many of the questions based solely on the provided text. To fulfill the request, one would need access to the full submission documents, specifically the detailed performance study reports.
Based on the provided text, the following information is available (and what is not):
1. A table of acceptance criteria and the reported device performance:
- Not provided in the text. The text only generally states that "the device meets its design requirements and intended use." Specific numerical acceptance criteria for measured parameters (skin temperature, auscultation sound, heart rate) and corresponding achieved performance values are absent.
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):
- Not provided in the text. The text mentions "extensive safety and performance testing" but does not specify the sample sizes of patients or data points for any performance tests. Data provenance is also not mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not provided in the text. No information about expert involvement in establishing ground truth is present.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not provided in the text. No details on adjudication methods for test sets are mentioned.
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/Not mentioned. The device described is a "remote monitoring system" that collects physiological data for review by HCPs. It is not an AI-powered diagnostic imaging device typically subject to MRMC studies comparing human reader performance with and without AI assistance. The text does not describe any AI component that directly assists in human interpretation or diagnosis.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Partially inferred/Limited information: The system uses "Alio's proprietary algorithms" to process and analyze raw data in the Alio Medical Cloud. While a standalone algorithm performance evaluation would logically be done internally to ensure accuracy of processed data (heart rate, temperature, sound data), the detailed results of such a standalone performance or how its accuracy was quantitatively measured against a gold standard are not provided in this summary. The stated function is to transmit data for HCP review, implying the algorithm's role is data processing rather than a standalone diagnostic output.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Not provided in the text. The method for establishing ground truth for any measurements (e.g., a clinically validated temperature probe for skin temperature, or a gold standard ECG for heart rate) is not detailed.
8. The sample size for the training set:
- Not applicable/Not provided. While the system uses "proprietary algorithms," the document does not explicitly state that these algorithms are machine learning models requiring "training sets" in the typical sense. Even if they are, the training set size is not mentioned.
9. How the ground truth for the training set was established:
- Not applicable/Not provided. As with the training set itself, the method for establishing ground truth for any potential training data is not mentioned.
In summary, the provided 510(k) summary serves as a high-level overview for regulatory purposes, demonstrating substantial equivalence. It does not delve into the detailed technical performance study results, acceptance criteria, or statistical validations typically found in comprehensive study reports.
§ 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).