ViSi Mobile Continuous Vital Signs Monitoring Even Better With Machine Learning

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ViSi Mobile, used for non-invasive continuous vital signs monitoring, to identify early patient deterioration and prevent alarm fatigue is enhanced to now utilize advanced machine learning.

Sotera Wireless, a medical technology company in San Diego, California, has released its sixth (6th) version of software for the ViSI Mobile Vital Signs Monitoring System. The new version of software (Version 6.0.1) focuses on improving clinical workflow and patient recovery time in the general care / post-surgical areas of the hospital. The ViSi Mobile Vital Signs Monitoring System provides accurate, continuous, and non-invasive vital signs monitoring for patients in care units that are designed for patient recovery and the prevention of physiological deterioration.

More details can be found at

The newly released software (6.0.1) utilizes advanced machine learning and delivers increased efficiencies to the clinical staff as they treat patients.

The discrete measurement of specific cardiac variables allows “smart technology” to reduce alarm fatigue and improve QRS output. (The QRS complex is the combination of three of the graphical deflections seen on a typical electrocardiogram. It is usually the central and most visually obvious part of the tracing; in other words, it’s the main spike seen on an ECG line.) By incorporating advancements that provide increased insight into cardiac and vascular profiles, cardiac data output is improved and physiological changes to the patient’s circulatory system are detected immediately.

Early detection of changes in a continuous non-invasive blood pressure measurement are key factors in recognizing early physiological deterioration. This new version of software contains enhanced detection algorithms that allow machine learning to monitor the blood pressure profile and brings enhanced efficiencies to the patient setup and parameter limits.

ViSi Mobile improves the automated vital signs collection process; seamlessly transcribing data into a patient’s electronic medical records by utilizing more efficient coding algorithms. Relieving the administrative burden of active charting allows clinical teams to focus on treatment plans, the patient’s recovery, and the “patient experience” while in the recovery unit.

Poor signal quality in some hospital units slows the patient set-up of continuous vital sign monitors. Using advanced machine learning algorithms to improve data classification, the latest ViSi Mobile software reduces setup time and shortens calibration of its novel, continuous non-invasive blood pressure measurement.

Up to 75% of adverse events and preventable deaths occur outside the ICU. Vital sign collection typically is ordered according to unit policy and not according to patient need. Dangerous patient deterioration can occur in the interim between a physical vital sign spot check: which can be as long as four (4) to six (6) hours. ViSi Mobile addresses this “gap” in coverage with continuous non-invasive monitoring.

Dr. Devin McCombie, CEO of Sotera Wireless said, “Our goal is to help hospitals improve patient safety and clinical workflow. Our newest software release allows ViSi Mobile to do these things even better by utilizing our database of more than 20 million hours of patient data to more accurately help the clinical staff recognize potential concerns.”

Interested parties in the US can find more information by visiting

* AHA database, 2013 2 I2_Presentation_Diagnostics_Haraden.pdf