(294 days)
QP-160AK Trend program (K092573)
No
The device description explicitly states the algorithm "applies a set of rules to estimate the background pattern based on upper and lower margins of the aEEG signal," which describes a rule-based or deterministic approach rather than AI/ML. There is no mention of training data being used to learn patterns.
No.
The device analyzes and identifies background patterns in aEEG signals; it does not provide any diagnostic conclusions, treatment, or therapy.
No
The device description explicitly states: "The device does not provide any diagnostic conclusion about the patient's condition." and "The software does not make any final decisions that result in any automatic diagnosis or treatment." Instead, it analyzes and identifies background patterns in aEEG, which are then "reviewed and interpreted by qualified clinical practitioners."
Yes
The device description explicitly states "BPc™ is a software only product". The summary also clarifies that the software does not handle data acquisition or review, focusing solely on analysis of the aEEG signal provided from external electrodes.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVDs analyze specimens derived from the human body. The device analyzes aEEG signals, which are electrical signals recorded from the brain. While these signals are from the human body, they are not considered a "specimen" in the typical sense of an IVD (like blood, urine, tissue, etc.).
- The device's function is pattern classification of a physiological signal. It identifies and categorizes patterns within the aEEG signal. This is distinct from analyzing the chemical, biological, or immunological properties of a specimen.
- The intended use explicitly states it does not provide a diagnostic conclusion. IVDs are typically used to aid in the diagnosis of a disease or condition by providing information about a patient's health status based on the analysis of a specimen. This device's output requires interpretation by a qualified clinical practitioner and does not automatically lead to a diagnosis.
The device falls under the category of a medical device that analyzes physiological signals, rather than an in vitro diagnostic device.
N/A
Intended Use / Indications for Use
The Background Pattern Classification algorithm is intended for:
· Neonatal patients, defined as from birth to 28 days post-delivery, and corresponding to a post-conceptual age of 37 to 46 weeks, in clinical environments such as the intensive care unit, operating room, and for clinical research.
• To analyze and identify background patterns in aEG, including continuous and discontinuous activity, burst suppression, low voltage, and inactive patterns. The aEEG must be obtained from a pair of parietal electrodes located at positions corresponding with P3 and P4 of the International 10/20 System. The background pattern classification algorithm must be reviewed and interpreted by qualified clinical practitioners.
The device does not provide any diagnostic conclusion about the patient's condition.
Product codes (comma separated list FDA assigned to the subject device)
OMA, ORT
Device Description
BPc™ is a software only product that identifies background patterns seen on aEEG signal recorded from a pair of parietal electrodes (P3-P4) in neonates, defined as from birth to 28 days post-delivery, and corresponding to a post-conceptual age of 37 to 46 weeks. The classification of aEEG background pattern into one of five different classes is done in accordance with the scoring scheme described in the following table:
- Continuous (C): Continuous activity with lower (minimum) amplitude around (5 to) 7 to 10 µV and maximum amplitude of 10 to 25 (to 50) µV.
- Discontinuous (DC): Discontinuous background with minimum amplitude variable, but below 5 µV, and maximum amplitude above 10 µV.
- Burst-suppression (BSA): Discontinuous background with minimum amplitude without variability at 0 to 1 (2) µV and bursts with amplitude >25 µV. BS+ denotes burst density >100 bursts/h, and BS- means burst density
§ 882.1400 Electroencephalograph.
(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).
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Food and Drug Administration 10903 New Hampshire Avenue Document Control Center - WO66-G609 Silver Spring, MD 20993-0002
June 3, 2016
Natus Medical Incorporated DBA Excel-tech Ltd. (Xltek) Sanjay Mehta Senior Manager Quality and Regulatory Affairs 2568 Bristol Circle Oakville, CA L6H5S1
Re: K152301
Trade/Device Name: Background Pattern Classification (BPc 114) Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OMA, ORT Dated: April 22, 2016 Received: May 5, 2016
Dear Sanjay Mehta:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food. Drug. and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices. good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device
1
related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to
http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
You may obtain other general information on your responsibilities under the Act from the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.
Sincerely yours,
Michael J.Hoffmann -A
for Carlos L. Peña, PhD, MS Director Division of Neurological and Physical Medicine Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K152301
Device Name
Background Pattern Classification
Indications for Use (Describe)
The Background Pattern Classification algorithm is intended for:
· Neonatal patients, defined as from birth to 28 days post-delivery, and corresponding to a post-conceptual age of 37 to 46 weeks, in clinical environments such as the intensive care unit, operating room, and for clinical research.
• To analyze and identify background patterns in aEG, including continuous and discontinuous activity, burst suppression, low voltage, and inactive patterns. The aEEG must be obtained from a pair of parietal electrodes located at positions corresponding with P3 and P4 of the International 10/20 System. The background pattern classification algorithm must be reviewed and interpreted by qualified clinical practitioners.
The device does not provide any diagnostic conclusion about the patient's condition.
Type of Use (Select one or both, as applicable)
| ☑ Prescription Use (Part 21 CFR 801 Subpart D) |
|---|
| ☐ Over-The-Counter Use (21 CFR 801 Subpart C) |
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510K Summarv
Date: June 3rd ., 2016
Submitted by: Natus Medical Incorporated DBA Excel-Tech Ltd. (XLTEK) 2568 Bristol Circle Oakville, Ontario Canada L6H5S1
Contact Person:
Sanjay Mehta Senior Manager, Quality Assurance and Regulatory Affairs Natus Medical Incorporated Tel.: (905) 829-5300 ext 388 Fax .: (905) 829-5304 E-mail: Sanjay.mehta@natus.com
Propietary Name : Background Pattern Classification Algorithm (BPc™)
Common Name: aEEG software
Classification Name (Number): Amplitude Integrated Electroencephalograph (882.1400), Burst Suppression Detection Software for Electroencephalograph( 882.1400).
Product code: OMA; ORT Device Class: II
Predicate Devices: QP-160AK Trend program (K092573)
Description
BPc™ is a software only product that identifies background patterns seen on aEEG signal recorded from a pair of parietal electrodes (P3-P4) in neonates, defined as from birth to 28 days post-delivery, and corresponding to a post-conceptual age of 37 to 46 weeks. The classification of aEEG background pattern into one of five different classes is done in accordance with the scoring scheme described in the following table:
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Classification of aEEG Patterns in Term Neonates
Describes the dominating type of electrocortical activity in the aEEG trace.
-
- Continuous (C): Continuous activity with lower (minimum) amplitude around (5 to) 7 to 10 µV and maximum amplitude of 10 to 25 (to 50) µV.
-
- Discontinuous (DC): Discontinuous background with minimum amplitude variable, but below 5 µV, and maximum amplitude above 10 µV.
-
- Burst-suppression (BSA): Discontinuous background with minimum amplitude without variability at 0 to 1 (2) µV and bursts with amplitude >25 µV. BS+ denotes burst density >100 bursts/h, and BS- means burst density 25 µV. BS+ denotes burst density >100 bursts/h, and BS- means burst density