clinical safety and efficacy testing of a medical device kardi ai, an ecg telemetry monitoring system

Conditions: Atrial Fibrillation (AF); Atrial Premature Complexes; Ventricular Premature Complexes; Bradycardia; Tachycardia; Supraventricular Tachycardia; Wide QRS Tachycardia

Summary: the goal of this clinical trial is to evaluate the safety and efficacy of medical device kardi ai, an ecg telemetry monitoring device in adult population. the main questions it aims to answer are: * what is the sensitivity and specificity of kardi ai device for all monitored heart rythm disorders (combined) * what is the sensitivity and specificity of kardi ai device for each of the monitored heart rythm disorders * what is the quality of the ecg recordings participants will receive kardi ai medical device. they will use it to collect ecg recordings from at least 5 different days and in total collect records of at least 10 hours duration.

the primary objective of the study is to correctly find the given heart rythm disorders using kardi ai across all measurements compared to an experienced cardiologist. the primary objective will be evaluated across all heart rhythm disorders together, using the statistics used in the evaluation of diagnostic tests (sensitivity, specificity, if applicable, positive predictive values and negative predictive values predictive values of the test). study procedure: 1. familiarisation of the subject with the clinical trial 2. signing the informed consent 3. handover of the kardi ai medical device (packaging hardware components of the polar h10 chest strap, including instructions for use and qr codes for installation of the kardi ai app), registration of the subject in the physician's electronic case report form. 4. installation and commissioning of the mobile pohone application by the subject. 5. independent measurement of the subject in the home environment. measurements should be done at least 3 times per week for the duration of at least two hours each. as part of the ecg recording for the purpose of the clinical trial, measurements will be taken on at least five different days; and the total recording time must be at least 10 hours. if bradycardia is suspected, at least one measurement must be taken overnight for at least 6 hours. 6. raw data for each measurement in the kardi ai mobile app will be transmitted to the kardi ai cloud, where it will be analyzed by ai, including evaluation of the following 7 heart rhythm disorders: * atrial fibrillation * supraventricular tachycardia * wide-complex tachycardia * increased number of supraventricular extrasystoles * increased number of ventricular extrasystoles * tachycardia\>220 bpm * bradycardia\<40 bpm 7. kpis calculated by ai will be automatically transmitted via api to the edc system, where the results of each measurement will be stored in a separate form under the specific code of the subject. 8. individual ecg recordings will be annotated by the physician. the heart rhythm disorders found in the measurements will be recorded by the physician in the electronic case report form. 9. once the data collection is complete, the results obtained by the ai and the results from the physician will be compared by a statistician. the accuracy and correctness of the ecg interpretation will be evaluated between the kardi ai system vs. the physician-based ecg annotation. 10. upon completion of the data collection, a questionnaire related to the individual satisfaction with the kardi ai system will be completed by each subject of the trial.

Eligibility criteria:
inclusion criteria: * age above 18 years * signed informed consent/willingness to cooperate * confirmed or suspected heart rhythm disorder of a cardiac rhythm disorder * ability to use a smartphone and mobile app kardi ai * the subject's mobile phone meets the minimum requirements for the kardi ai app to work exclusion criteria: * confirmed pregnancy * allergic reactions to standard substances used in manufacture of clothing or other textiles * superficial wound or skin irritation at the site of the chest belt attachment

Keywords: ai heart rhythm disorders ecg ekg atrial fibrillation