mobiCARE

Wearable ECG patch

It can measure ECG signals for up to nine consecutive days.

It allows for a quick and convenient check of the ECG waveform analyzed by the deep learning algorithm.

AI and medical technologists analyze the ECG waveforms,
and an arrhythmia specialist reviews them to provide the
final report.

Measured data can be uploaded via mobile phones or PCs, and the ECG
diary can be conveniently recorded through the app.

Analysis program for professionals

ECG analysis report

Mobile app & ECG diary

AI algorithm of the mobiCARE™

The algorithm monitors biomarkers that provide accurate electrocardiogram analysis, detecting 14 types of arrhythmias, beat information, activity levels, and heart rate variability through AI algorithms.

Sufficient and validated ECG data

Secured anonymized data from over 80,000 patients

Obtained specific ECG data through clinical studies

Precise ECG analysisAI algorithm

Detects 14+ arrhythmias

Provides various ECG analysis functions such as HRV calculation

Establishes automatic data acquisition and learning pipelines

Ensures secure data management through a data security system

Manages the entire process from development to deployment of ML algorithms.

Optimization of deep learning & machine learning algorithms

Email:
contact@mobicare.mn

Outpatient ElectrocardiogramAnalysis Services

Provides analysis via wearable ECG patches and a clinically validated AI algorithmic reading program.

Detection of Morphological Characteristics of Atrial Fibrillation Using Semantic Segmentation

Ensemble Learning Method for In-Hospital Cardiac Arrest Prediction

Evaluation of the Diagnostic Performance and Efficacy of Wearable Electrocardiogram…

Comparison of adhesive single-lead ECG device and Holter test for atrial fibrillation monitoring