Bio-signal Monitoring Can Tell Common Diseases

/ / All, Digital Health

In these days, breath, temperature, heartbeat rate, blood sugar level, and other human body signals can be analyzed by AI and consequently indicate or predict our health status and diseases.
Sepsis, a common deceasing factor of patients, is the best example which can be accurately recognized by varied temperature, blood pressure drop, reaction reduction, and raised breath rate.
According to researchers from University of Ontario Institute of Technology, premature infants who are about to be subjected to sepsis displayed the reduction of heart rate variability.
In terms of intensive care patients, TREWScore (Targeted Real-Time Early Warning Score) was developed with EHR big data and this allowed predicting sepsis shock about 28.2 hours earlier.

Additionally, Medtronic and IBM Watson displayed an AI, Sugar IQ, which allowed diabetic patients to constantly manage and predict their blood sugar level.
Sugar IQ suggests insight to control blood sugar level after when it analyze every monitored blood sugar and insulin level variance.
It makes patients to improve their good habit by providing proper information for individuals after when all of informative patterns are identified.

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