Скачать или смотреть Mobile SDK v3.1: Real-Time ECG Monitor & Audio Analyzer - SciChart

Build medical and scientific mobile applications that save lives and solve complex problems. With the release of SciChart Mobile SDK v3.1, we have revitalized our demo suite to show exactly how to deploy high-performance charting for Patient Monitoring and Signal Processing.

In this video, we showcase two powerful use cases: a Vital Signs ECG/EKG Monitor and a real-time Audio Spectrum Analyzer. Whether you are targeting iOS, Android, or building custom hardware on Raspberry Pi/Arduino, SciChart provides the hardware-accelerated rendering engine needed to visualize high-frequency sensor data instantly.

What you'll see:
– Vital Signs Demo: Creating a realistic ECG/EKG heart rate monitor
– Medical Applications: Visualizing data for ventilators, digital stethoscopes, and blood pressure monitors – Audio Analyzer Demo: Real-time Spectrograms and Frequency Analysis
– Scientific Applications: Radio Frequency (RF) analysis and signal processing
– Cross-Platform Support: Running on iOS, Android, and Xamarin (Swift, Kotlin, C#)

Why Developers Choose SciChart for Medical & Scientific Apps
– Time to Market: Shortcut development with ready-made, industry-standard examples
– Hardware Acceleration: Smooth rendering even on lower-power custom Android hardware
– Precision: Accurate visualization for mission-critical diagnostics
– Broad Compatibility: Support for Swift, Objective-C, Java, Kotlin, and Xamarin

View iOS Chart Features: http://www.scichart.com/ios-chart-fea...
View Android Chart Features: https://www.scichart.com/android-char...
Download the SDK (30-Day Free Trial): https://www.scichart.com/downloads

Contact Us: https://www.scichart.com/contact-us

SciChart empowers developers to build the next generation of medical devices and scientific tools. Don't build your visualization from scratch—use the world's most powerful mobile chart library.

#MobileDev #MedTech #ECGMonitor #SpectrumAnalyzer #SciChart #Xamarin #AndroidDev #iOSDev #DigitalHealth #SignalProcessing