(176 days)
BioStamp nPoint is a wireless remote monitoring system intended for use by researchers and healthcare professionals for continuous collection of physiological data in home and professional healthcare settings during research studies. These physiological data include heart rate variability, respiration rate, activity (including step count and activity classification), and posture (body position relative to gravity). The system is also intended for measurement of surface electromyography, and to monitor limb or body living and sleep. Data are transmitted wirelessly from the Sensors for storage and analysis.
The device is intended for use on general care patients who are 18 years of age or older as a general patient monitor, to provide physiological information. The BioStamp nPoint system are only intended for use by researchers and healthcare professionals for research applications, including at the discretion of a qualified healthcare professional as an aid to diagnosis and treatment in the context of clinical research and product development. The device is not intended for use on critical care patients, and is not a real time or remote diagnostic device.
The BioStamp nPoint system is a wireless remote monitoring platform intended for use by healthcare professionals and researchers for the continuous collection of physiological data in home and healthcare settings. The system is designed only for data collection during research studies.
The BioStamp nPoint system centers on body-worn Wearable Sensor Patches (WSPs) and can be used in both clinic and home settings for up to 24 hours. Study facilitators (either researchers or physicians) set up data collection studies using a web-based study configuration tool, called the Investigator Portal. For supervised uses, the BioStamp nPoint system includes a Tablet with Investigator Application that study facilitators use to connect to and configure WSPs. When used at home, study subjects interact with the system through the Mobile Phone Link Application. The Link Hub is used to charge and synchronize data from the Wearable Sensor Patches. The BioStamp nPoint system includes an algorithm package that delivers processed metrics on general activity classification, heart rate, heart rate variability, posture, sleep, and respiration during sleep. The BioStamp nPoint system is intended for use on general care patients who are 18 years of age or older and is not intended for use on critical care patients.
The BioStamp nPoint device is a wireless remote monitoring system. The provided text offers details about its performance validation, but it does not include a specific table of acceptance criteria with reported device performance metrics, nor does it describe an AI-specific study.
However, based on the information provided, we can infer and construct some aspects of the performance study and how it relates to general acceptance criteria for medical devices of this type.
Here's an attempt to answer your request, gleaning information from the provided text and making reasonable inferences where specific details are missing:
The BioStamp nPoint system is a wireless remote monitoring platform. While the document does not explicitly state acceptance criteria in a table format with corresponding performance results, it indicates that "V&V testing was performed to establish the safety and effectiveness of BioStamp nPoint." The device's performance was evaluated against its intended use for measuring physiological data.
1. Acceptance Criteria and Reported Device Performance
Given the nature of the device, the implicit acceptance criteria would revolve around the accuracy, reliability, and safety of its physiological data collection.
Inferred Acceptance Criteria Table and General Performance Statement:
| Physiological Data Metric | Acceptance Criteria (Inferred) | Reported Device Performance |
|---|---|---|
| Heart Rate | Accurate and reliable measurement within clinically acceptable limits compared to a reference standard. | "The results of the clinical investigation demonstrate an effectiveness profile that is similar to the predicate devices." (Exact accuracy metrics are not provided in this summary.) |
| Heart Rate Variability | Accurate and reliable measurement within clinically acceptable limits compared to a reference standard. | "The results of the clinical investigation demonstrate an effectiveness profile that is similar to the predicate devices." (Exact accuracy metrics are not provided in this summary.) |
| Respiration Rate | Accurate and reliable measurement within clinically acceptable limits compared to a reference standard. | "The results of the clinical investigation demonstrate an effectiveness profile that is similar to the predicate devices." (Exact accuracy metrics are not provided in this summary.) |
| Activity/Step Count | Accurate and reliable measurement compared to a reference standard, demonstrating appropriate classification of general activity and step count. | "The results of the clinical investigation demonstrate an effectiveness profile that is similar to the predicate devices." (Exact accuracy metrics are not provided in this summary.) |
| Posture | Accurate and reliable classification/measurement of body position relative to gravity. | "The results of the clinical investigation demonstrate an effectiveness profile that is similar to the predicate devices." (Exact accuracy metrics are not provided in this summary.) |
| Surface Electromyography (EMG) | Accurate and reliable measurement of surface electromyography. | The document states comparison to the CMAP Pro (K113074) predicate device found equivalence in technological characteristics related to EMG data gathering, implying acceptable performance. (Specific performance metrics are not given.) |
| Limb/Body Movements (Sleep/Daily Living) | Accurate and reliable monitoring and analysis of physiological motion during daily living and sleep. | The document states comparison to the MotionWatch and PRO-Diary (K132764) predicate device found equivalence in technological characteristics related to measuring and analyzing physiological motion, implying acceptable performance. (Specific performance metrics are not given.) |
| Safety | Compliance with relevant electrical safety and EMC standards. | "Safety testing demonstrated the device complies with IEC 60601-1 Edition 3.1, IEC 60601-1-11:2015, IEC 60601-1-6, IEC 62366:2015, IEC 60601-2-40:2016." and "EMC testing was conducted and demonstrated the device complies with IEC 60601-1-2 Edition 4. and FCC CFR 47 Part 15 Subpart C for wireless communication." |
| Biocompatibility | No adverse biological reactions when in contact with the body. | "Biocompatibility testing included cytotoxicity, irritation, and sensitization according to the recommendations of ISO 10993-1, Biological evaluation of medical devices – Part 1: Evaluation and testing." (Implies compliance was achieved). |
| Software Functionality | Software operates as intended without critical errors impacting safety or effectiveness. | "Software V&V testing was performed... and demonstrated safety and effectiveness of the device." (Software was determined to be a "moderate level of concern"). |
2. Sample Size and Data Provenance for the Test Set:
- Sample Size for Test Set: 30 healthy volunteers were used for the human clinical investigation.
- Data Provenance: The document states "A human clinical investigation was performed on 30 healthy volunteers." It does not specify the country of origin, but given the FDA submission, it's likely the study was conducted in the US or in a manner compliant with US regulations. The study was a prospective clinical investigation.
3. Number of Experts and Qualifications for Ground Truth:
The document does not specify the number or qualifications of experts used to establish ground truth for the physiological measurements. It only mentions that the study evaluated the device's performance at measuring various physiological parameters. For physiological measurements, ground truth is typically established by comparative methods using validated reference instruments.
4. Adjudication Method for the Test Set:
The document does not mention any adjudication method for the test set, as this typically applies to subjective interpretations (e.g., image reading) rather than direct physiological measurements validated against a reference.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No, a MRMC comparative effectiveness study was not done. This type of study is more common for diagnostic imaging AI systems where human readers interpret images with or without AI assistance.
- The BioStamp nPoint is a physiological data collection device, not an AI-assisted diagnostic tool for human interpretation. Therefore, a MRMC study is not applicable in this context.
6. Standalone (Algorithm Only) Performance:
The document describes the device as a "wireless remote monitoring system" with an "algorithm package that delivers processed metrics." The clinical investigation on 30 healthy volunteers evaluated the "performance of the device at measuring heart rate, heart rate variability, respiratory rate, activity (including step count and activity classification), and posture (body position relative to gravity)." This implies that the standalone performance of the device's algorithms in processing the raw sensor data into these metrics was assessed. The results were compared to predicate devices, suggesting the performance was deemed acceptable.
7. Type of Ground Truth Used:
The ground truth for the human clinical investigation would have been established by comparison to established, accurate, and preferably gold-standard reference methods or devices for measuring each physiological parameter (e.g., a reference ECG for heart rate, a capnograph or spirometer for respiration rate, or direct observation/other validated accelerometry for activity/step count). The document does not explicitly state the specific ground truth methods but refers to "effectiveness profile that is similar to the predicate devices," implying a comparison to known, validated physiological measurements.
8. Sample Size for the Training Set:
The document does not provide information regarding the sample size for a training set. This is not unexpected, as the device is for physiological data collection, and while it uses "algorithms," the context doesn't indicate a machine learning model that would require a large, independently defined "training set" in the sense of a dataset used to train a deep learning algorithm. If the algorithms are signal processing or rule-based, a separate "training set" may not exist in the same way.
9. How Ground Truth for Training Set was Established:
As no training set is described, this information is not applicable/provided.
§ 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).