First-Check-V and Vascular Check 1

First-Check-V and Vascular Check 1 are designed to explore the use of artificial intelligence (AI), plethysmographic technologies, and big data analytics for vascular signal analysis. These systems are being developed to support research into real-time hemodynamic data processing and pattern recognition for potential future applications in vascular health.

AI and Big Data in Vascular Research

Cardiovascular function is closely related to the mechanical properties and elasticity of the arterial system. Changes in vascular stiffness can affect blood flow dynamics and are an increasingly important area of study in cardiovascular research.

The First-Check-V concept utilizes AI-assisted algorithms and large-scale data analytics to investigate:
– how hemodynamic waveforms can be characterized in real time,
– how arterial pulse patterns may be associated with stiffness-related parameters,
– how data-driven pattern recognition may contribute to future vascular research models.

By leveraging big data analytics, the platform is designed to compare recorded pulse signals with large anonymized datasets to support research into vascular pattern classification and signal-based modeling.

Technological Framework (Under Development)

The First-Check-V development platform integrates:
– Advanced Plethysmography (APG) concepts for pulse-wave characterization,
– MGP-related analytical models as part of ongoing research into vascular biochemistry,
– Real-time signal acquisition for waveform analysis,
– AI-assisted algorithms to investigate stiffness-related data correlations,
– Big Data pipelines for large-scale comparative signal modeling.

These components are being studied exclusively within an R&D context to evaluate technical performance, usability, and analytical feasibility.

Current research efforts focus on exploring:
– real-time waveform processing,
– hemodynamic pattern recognition,
– data-driven insights for future vascular research tools.