Patient’s companion app supports data transmission and filling scheduled questionnaires.
To assess the relationship of recorded heart rhythm disturbances to sleep-disordered breathing, which is essential for the correct choice of appropriate treatment of rhythm disturbances.
For the follow-up of patients with suspected sleep-disordered breathing (SBS), especially obese patients, with suspected breathing disorders (e.g., chronic obstructive pulmonary disease – COPD), treatment-resistant hypertension, after CNS stroke, etc.
Analyze the correlation of reported symptoms (such as palpitations, irregular heartbeat, shortness of breath, dizziness, fainting, loss of consciousness, fatigue) with the presence of arrhythmias and make a preliminary assessment of the type of arrhythmia.
In the diagnosis of atrial fibrillation (AF); both in patients reporting symptoms suggestive of AF and in asymptomatic patients at high risk for this arrhythmia.
To evaluate arrhythmias and to differentiate between atrial fibrillation, arrhythmias of supraventricular and ventricular origin and, in case of bradyarrhythmias, to differentiate between sinus node automatic failure and atrioventricular conduction disturbances.
The apnea and deflation detector detects declines in airflow through the cannula. In combination with other signals, our solution allows not only to diagnose but also to guide the patient more effectively in the therapeutic process.
Telemedicine sensors and detectors trained with machine learning techniques will be useful for diagnosis, but their predictive value for quantitative assessment of arrhythmia severity. It can be useful for therapeutic decision making and during treatment evaluation should be emphasized.