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510(k) Data Aggregation
(157 days)
The BioButton System is a remote monitoring wearable device intended for continuous collection of physiological data in home and healthcare settings while the patient is at rest. This could include heart rate, respiratory rate, skin temperature, and other data such as activity level, body position, sleep, and step and gait analysis.
Data are securely transmitted via wireless connection for storage, review, analysis, and display.
The Device can include the ability to display data and notify healthcare professionals when physiological data fall outside clinician-specified parameters.
The data from the Device are intended as an aid to diagnosis, disease management, and treatment. The Device is intended for use on patients who are 18 years of age or older.
The Device is not intended to output physiological measurements while the patient undergoes significant motion or is active.
The Device is not intended for critical care.
The BioButton System (the "Device") is a wireless remote monitoring system intended for use by healthcare professionals for continuous collection of physiological data in home and healthcare settings while the patient is at rest. This can include heart rate, respiratory rate, and skin temperature. Data are transmitted from the Device for storage and analysis.
The Device is an extension of the Predicate Device (K212957) with the same intended use. The Device consists of a multiple-use and rechargeable wearable hardware sensor module to collect data from a patient and other Medical Device Data System (MDDS) components that enables remote transfer of collected data. The main components of the Device include the following:
- A wearable sensor to collect data from a patient
- A device-based Medical Device Data System (MDDS) data gateway to transfer data from the wearable sensor to the cloud
- A cloud-based Medical Device Data System (MDDS) for data storage and transmission
- A cloud-based system for configuration of the wearable sensor and data analysis
- A cloud-based system for healthcare professionals to view patient information
The Device is used to collect physiological information from a patient using the sensor for a set duration (as defined by different use cases) in home and healthcare settings. Physiological data is collected continuously while the patient is at rest. The medical physiological data collected includes:
- Heart rate at rest,
- Respiratory rate at rest, and
- Skin temperature
There are other wellness parameters that can be collected by the device that include: activity level, body position, sleep, and step and gait analysis. These wellness data types are not discussed in detail the regulatory submission since they do not meet the definition of medical device.
Upon completion of a physiological data collection period, the data offload is conducted via wireless Bluetooth connection using the Offload Software. The data offloading is performed and qualified personnel. The Device also provides a web display for healthcare professionals to view patient information.
The provided text is a 510(k) summary for the BioButton System, a remote monitoring wearable device. It describes the device, its intended use, and comparisons to a predicate device, along with performance testing conducted to support substantial equivalence.
Based on the provided text, here's a detailed breakdown of the acceptance criteria and the study that proves the device meets them:
1. A table of acceptance criteria and the reported device performance
The document provides the following performance specifications for the BioButton System:
| Performance Item | Acceptance Criteria (Claimed) | Reported Device Performance (Achieved) |
|---|---|---|
| Heart Rate Range | 40-150 Beats per Minute | 40-150 Beats per Minute (Implied to be met, as it's the claimed range) |
| Heart Rate Accuracy | 5 Beats per minute (<±5 Beats per minute) | Met (Clinical studies confirmed accuracy claims for heart rate measurements) |
| Respiratory Rate Range | 5-35 Breaths per Minute | 5-35 Breaths per Minute (Implied to be met, as it's the claimed range) |
| Respiratory Rate Accuracy | 3 Breaths per Minute (<±3 Breaths per Minute) at rest | Met (Clinical studies confirmed accuracy claims for respiratory rate measurements) |
| Skin Temperature Standard | Meets ASTM E1112-00 standard | Met (Benchtop testing) |
| Skin Temperature Range | 86°F - 107°F (30°C - 42°C) | Met (Benchtop testing) |
Note: The document states that "all subgroups independently met device accuracy claims for heart rate and respiratory rate measurements" in the clinical studies section, which directly addresses the heart rate and respiratory rate accuracy criteria. For skin temperature, it explicitly says "Temperature measurement performance validation per ASTM E1112 standard per the Device's measurement range," indicating compliance.
2. Sample size used for the test set and the data provenance
- Sample Size: The clinical study for heart rate and respiratory rate involved 52 qualified subjects.
- For heart rate, 1394 datasets were collected.
- For respiratory rate, 1898 datasets were collected.
- Data Provenance: The document does not explicitly state the country of origin. However, the FDA 510(k) submission process implies that the studies were conducted to US regulatory standards. The study was a clinical study performed on the general population, which means it was prospective data collection.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document does not specify the number of experts or their qualifications used to establish the ground truth for heart rate, respiratory rate, or skin temperature. It only states that clinical studies were performed to "confirm the measurement performance" and benchtop testing was done for temperature. This typically means the device's measurements were compared against a reference standard or validated method, rather than an expert consensus process.
4. Adjudication method for the test set
The document does not mention any adjudication method for the test set. Given the nature of physiological measurements (heart rate, respiratory rate, skin temperature), ground truth is usually established via highly accurate reference devices or methods, rather than expert 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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The BioButton System is a device for collecting physiological data, not an AI-assisted diagnostic tool that would typically involve human readers interpreting images. The closest relevant statement is that "The data from the device are intended as an aid to diagnosis, disease management, and treatment," but this does not imply a human-in-the-loop AI effectiveness study.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
Yes, the performance testing described for heart rate, respiratory rate, and skin temperature is effectively a standalone (algorithm only) performance evaluation. The device's measurements are validated against a reference standard to confirm its accuracy, without directly involving human interpretation assisted by the device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The type of ground truth used is implied to be concurrent measurement against a reference standard or validated method.
- For heart rate and respiratory rate, the "clinical studies were performed... to confirm the measurement performance," which suggests comparison against a validated, highly accurate physiological monitoring system.
- For skin temperature, it explicitly states "Temperature measurement performance validation per ASTM E1112 standard," indicating the use of a calibrated temperature reference.
8. The sample size for the training set
The document does not provide information regarding a separate training set or its sample size. This submission is for a 510(k) of a continuous physiological data collection device, not necessarily an AI/ML driven diagnostic device that would typically have distinct training and test sets in the same way. The performance data presented are from validation studies of the device itself.
9. How the ground truth for the training set was established
Since information about a specific training set and its sample size is not provided, how its ground truth was established is also not described in the document.
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