The Component Neuromonitoring System supports the front line of care with intuitive displays, convenient access to prior data, and instructional tools.
Multimodal Monitoring for Effective Care
Data collected by the CNS Monitor from various physiological monitors and therapeutic devices are time-synchronized and integrated on customized displays. Trended displays allow you to see and track changes over time. These insights help you make informed decisions about patient care.
Ease of Use for Efficient Care
The Component Neuromonitoring System (CNS) makes it easy to record, view, and share meaningful information. Point-of-care instruction provides tutorials that clearly explain how to set up the CNS Monitor and connect external devices for data collection. Once the devices are connected, you no longer have to worry about missing measurements because all the data will be recorded by the CNS Monitor.
At any point during monitoring, you can review prior data, comparing them to the patient's present status and visualizing the responses to treatment and care. Events can be marked in real-time or retrospectively for review by any user. Screenshot images can be archived on the monitor and saved to a USB drive for sharing with colleagues. These features simplify communication and consultation in your busy hospital.
Embedded multimedia provides learning opportunities for users with varied backgrounds and skills. Use the CNS Monitor to learn theories of operation of the connected devices, or take a mini-course in EEG.
"The future of multi-modal neuromonitoring lies in the ability to capture, store, and analyze multiple parameters in an effort to improve patient outcomes. The CNS has unique features including multi-parameter data display and trending on a single screen, real-time and retrospective data review, clinical event markers, educational tutorials, and video EEG monitoring. This state-of-the-art technology has become a standard of neuromonitoring and data collection in our Neuroscience ICU."Tracey Berlin, MSN-Ed, RN, CCRN, CNRN
Neuroscience Technology Specialist
University of New Mexico Hospital