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510(k) Data Aggregation
(329 days)
LG SMARTHEALTH
The LG SmartHealth is intended to collect vital sign measurement devices intensurement devices intended for use in the home . Patients can review the stored vital sign measurement information and motivational content from caregivers(or nurse). Patients can also engage in video conferences with caregivers(or nurse).
The LG SmartHealth is not interpretive, nor is it intended for diagnosis or as a substitute for medical care, and it is not intended to provide real time data. It is made available to patients when time-critical care is not required.
The LG SmartHealth is contraindicated for patients requiring direct-medical supervision or emergency intervention. It is intended for patients who are willing and capable of managing its use. Clinical judgment and experience by a caregiver are required to check and interpret the information delivered.
The LG SmartHealth application is software planned to operate on the Android operating system (OS) that can be loaded as an application or "app" on a commercially available smartphone. LG intended the software to work on the Android OS, as well as to operate on smartphones as well. The scalability and differences between many smartphones today are not too great to allow this flexibility and option.
The LG SmartHealth application connects to commercially available wireless medical devices that are commonly used by patients in a home-care setting. These "sensor devices" are FDA cleared or FDA registered (Exempt) devices that can communicate with the LG SmartHealth application software loaded on the smartphone using Bluetooth connectivity. To avoid wireless interference and confusion on the part of the patient, serial readings are performed (i.e. only one Bluetooth sensor used at a time) and MAC address filtering is used for the various medical devices. The LG SmartHealth application plans to support the following sensor available medical devices, some initially, and others as the technology becomes available:
- -Glucose meters or glucometers
- -Blood pressure cuffs
- -Weight scales
- -Body fat readers
- -Activity monitors
On each screen of the LG SmartHealth application software a help button is present, which when pressed provides step-by-step based help to guide a patient through an interaction.
The medical device takes a reading depending on the frequency previously established and the LG SmartHealth application software fetches the information for the reading automatically. The LG SmartHealth application software stores and displays the information on the smartphone and transmits the information to the server. The LG SmartHealth application encrypts the information in preparation for transmit using SHA256 bit encryption, complying with HIPAA requirements.
The provided document is a 510(k) premarket notification for the LG SmartHealth device. It primarily focuses on demonstrating substantial equivalence to a predicate device (Intel Health Guide Express K103276) rather than providing detailed acceptance criteria and a comprehensive study report for the LG SmartHealth directly.
Based on the information within the document, here's what can be extracted and inferred regarding acceptance criteria and studies:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly present a table of "acceptance criteria" with quantitative metrics for the LG SmartHealth's performance in the typical sense (e.g., sensitivity, specificity, accuracy for a diagnostic device). Instead, it discusses meeting software design specifications and demonstrating substantial equivalence. The "performance" is largely described in terms of software functionality, usability, and hazard mitigation.
| Acceptance Criteria (Inferred from document) | Reported Device Performance |
|---|---|
| Software Performance: | |
| - Meets established Software Design Specifications. | "The software was tested against the established Software Design Specifications for each of the test plans to assure the device performs as intended." |
| "The testing results support that all the software specifications have met the acceptance criteria of each module and interaction of processes." | |
| "The LG SmartHealth device passed all testing..." | |
| - Performs as intended. | (Implicitly stated above) |
| - Safe operation. | "...and supports the claims of substantial equivalence and safe operation." |
| - Hazard analysis completed and risks mitigated. | "The device Hazard analysis was completed and risk control implemented to mitigate identified hazards." |
| Usability Performance: | |
| - Comprehension by users (nurses and participants). | "The study demonstrated: Comprehension of the study nurses and participants with the LG SmartHealth..." |
| - Appropriate human factors. | "The study demonstrated:... Appropriate human factors related to the LG SmartHealth..." |
| - Ease of use. | "The study demonstrated:... Ease of use of the LG SmartHealth." |
| Functional Equivalence: | |
| - Similar data collection software functionality. | "Both devices have the same data collection software functionality..." |
| - Similar communication method of patient device with central server. | "Both devices have the same... communication method of patient device with central server..." |
| - Similar types of sensors interfaced, implementation methods, connectivity, protocol. | "Both devices have the same... types of sensors which can be interfaced to the patient device, implementation method of collecting data from sensors, sensor software, connectivity, and communication protocol." (Note: some differences in specific supported device types are listed, e.g., predicate supports Pulse Oximeter and FEV/PEF, while subject supports Temperature and Activity Monitor, but the type of interfacing is stated as similar.) |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Software Testing: The document states that "The device's software development, verification, and validation have been carried out in accordance with FDA guidelines." It mentions testing against "each of the test plans." It does not provide specific sample sizes (e.g., number of test cases, number of runs) for the software verification and validation.
- Usability Study: The document explicitly mentions a "usability study of the LG SmartHealth under actual use." It states the study involved "study nurses and participants." However, it does not specify the sample size for nurses or participants, nor does it mention the country of origin or whether it was retrospective or prospective. It is implied to be a prospective study ("under actual use").
- Clinical Performance Data: The document explicitly states, "There was no clinical testing required to support the medical device as the indications for use is equivalent to the predicate device." Therefore, no sample size for a clinical test set is provided.
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)
- For the software testing directly, the "ground truth" would be the expected output or behavior defined by the Software Design Specifications. This doesn't involve external human experts in the context of diagnostic interpretation.
- For the usability study, the "ground truth" would implicitly be the observed comprehension, human factors, and ease of use. This would be established by the study design and observation, but the document does not mention specific experts or their qualifications contributing to establishing this "ground truth" (e.g., human factors engineers evaluating the results). The "study nurses" participated in the study; it's not stated they established ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
The document does not describe any adjudication method for either the software testing or the usability study results. The software testing seems to rely on automated or manual verification against specifications, and the usability study on observation and possibly participant feedback.
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 LG SmartHealth is described as a "Remote Patient Monitoring System" that collects vital signs and facilitates communication/education. It is not an AI-assisted diagnostic or interpretive device, and therefore, an MRMC comparative effectiveness study involving human readers improving with/without AI assistance is not applicable and was not performed or mentioned. The device explicitly states it "is not interpretive, nor is it intended for diagnosis or as a substitute for medical care."
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The device is essentially a software application that collects, stores, displays, and transmits vital sign data from other FDA-cleared/registered medical devices. Its primary function is data management and communication facilitating human care. It does not perform an "algorithm only" diagnostic or interpretive function in the sense that AI-driven diagnostic tools do. The software's performance was validated against its design specifications and its usability was evaluated.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- For software testing: The ground truth was the established Software Design Specifications – essentially, the predefined correct behavior and output of the software modules.
- For usability study: The ground truth was observed comprehension, human factors, and ease of use based on participant interaction and feedback during the study.
8. The sample size for the training set
Not applicable/Not mentioned. The LG SmartHealth is not described as an AI/ML device that requires a "training set" for model development. Its software operation is rule-based and functional, focused on data collection, storage, and transmission, rather than learning from data.
9. How the ground truth for the training set was established
Not applicable. As no training set is mentioned for an AI/ML model, this question does not apply.
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