Why the study?
Validation of the artificial intelligence-based Vigo platform was conducted to evaluate the reproducibility of a real-time multi-vital remote monitoring solution.
Does the Vigo platform multi-vital monitoring solution accurately correlate with standard vital measurement methods in healthy volunteers?
Does the Vigo platform multi-vital monitoring solution accurately correlate with standard vital measurement methods in healthy volunteers?
The Vigo platform multi-vital monitoring solution demonstrated strong correlation with standard measurement methods for vital signs and ECG parameters in healthy volunteers over 24 hours.
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Supports Vigo platform correlation in healthy volunteers; leaves open validation in clinical populations.
Background: Recently the combination of telehealth with remote patient monitoring has paved the way for enhanced and augmented health-care services. Its benefits include obtaining efficient, cost and time saving data and minimizing error factors by remote monitoring methods. The validation of multi-vital artificial intelligence-based software (Vigo platform) was conducted to correlate reproducibility of real time vital recording solution. Methods: IEC approval and informed consents were obtained. Seventeen healthy participants were deployed on the multi-vital monitoring (MVM) solution in a controlled environment and continued for 24 hours. The vitals were measured by the standard methods periodically at intervals of 0, 2, 4, 6, 8, 10, 12 and 24 hours. ECG was measured at 0, 4, 8, 12 and 24 hours. Results: A total of 20 healthy volunteers were screened out of which seventeen volunteers participated as three volunteers withdrew consent. All the seventeen volunteers were males of mean age 21±3years and mean BMI 22.9±1.7Kg/m2. Vital parameters included Heart rate, Pulse rate, Respiratory rate, Temperature, Systolic blood pressure, Diastolic blood pressure and ECG Measures including P-wave, PR- interval, QRS-complex, RR-interval, QT-interval, ST-Segment, T-wave were strongly and significantly correlated internally (p>0.01) and 100% correlated externally (p>0.01). Conclusion: It was found that all the vital parameters and ECG measures were strongly matched and significantly correlated internally and externally. This work supports remote monitoring technology as part of remote patient care and decentralized research. Thus, software solution Vigo platform that was developed in this work may become a route to patients’ safety.
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Patibandla et al. (2023) studied this question.
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