A method for detecting signs of atrial fibrillation in normal sinus rhythm includes acquiring electrocardiogram data of a patient, generating preprocessed electrocardiogram data based on at least some specific regions from the electrocardiogram data, and determining a patient's risk of developing atrial fibrillation using the preprocessed electrocardiogram data and a pretrained atrial fibrillation determination model.

A method for detecting signs of atrial fibrillation in normal sinus rhythm includes acquiring electrocardiogram data of a patient, generating preprocessed electrocardiogram data based on at least some specific regions from the electrocardiogram data, and determining a patient's risk of developing atrial fibrillation using the preprocessed electrocardiogram data and a pretrained atrial fibrillation determination model.

Described herein are systems and methods for characterizing a subject's ejection fraction (EF) status, heart failure status, and/or sleep apnea status. In particular, described herein are systems and methods for characterizing a subject's EF status, heart failure status, and/or sleep apnea status through use of a wearable electrocardiogram (ECG) device having LII and LIII leads, and software configured to incorporate data from the ECG device and assess the subject's EF status, heart failure status, and/or sleep apnea status.

Described herein are systems and methods for characterizing a subject's ejection fraction (EF) status, heart failure status, and/or sleep apnea status. In particular, described herein are systems and methods for characterizing a subject's EF status, heart failure status, and/or sleep apnea status through use of a wearable electrocardiogram (ECG) device having LII and LIII leads, and software configured to incorporate data from the ECG device and assess the subject's EF status, heart failure status, and/or sleep apnea status.

Systems and Methods are disclosed for detecting acute coronary syndrome (ACS) events, arrythmias, heart rate abnormalities, medication problems such as non-compliance or ineffective amount or type of medication, and demand/supply related cardiac ischemia. The system may have both implanted and external components that communicate with a Physicians's programmer, and smart-devices for monitoring and alerting to detected medically relevant events or states. At least one processor provides event detection using statistical threshold criteria calculated upon at least a portion of a patient's data/distributions and set for a patient or based upon what a doctor determines as abnormal for a patient. A power management system provides at least 2 strategies of evaluating power level including at least obtaining a voltage measure and measuring and calculating a cumulative capacity measure and comparing these two measure to their respective thresholds.

Systems and Methods are disclosed for detecting acute coronary syndrome (ACS) events, arrythmias, heart rate abnormalities, medication problems such as non-compliance or ineffective amount or type of medication, and demand/supply related cardiac ischemia. The system may have both implanted and external components that communicate with a Physicians's programmer, and smart-devices for monitoring and alerting to detected medically relevant events or states. At least one processor provides event detection using statistical threshold criteria calculated upon at least a portion of a patient's data/distributions and set for a patient or based upon what a doctor determines as abnormal for a patient. A power management system provides at least 2 strategies of evaluating power level including at least obtaining a voltage measure and measuring and calculating a cumulative capacity measure and comparing these two measure to their respective thresholds.

Systems and Methods are disclosed for detecting acute coronary syndrome (ACS) events, arrythmias, heart rate abnormalities, medication problems such as non-compliance or ineffective amount or type of medication, and demand/supply related cardiac ischemia. The system may have both implanted and external components that communicate with a Physicians's programmer, and smart-devices for monitoring and alerting to detected medically relevant events or states. At least one processor provides event detection using statistical threshold criteria calculated upon at least a portion of a patient's data/distributions and set for a patient or based upon what a doctor determines as abnormal for a patient. Cardiovascular condition is tracked using histogram, trend, and summary information related to heart rate and/or cardiac features such as S-T segment measures of heartbeats. Heartbeats with elevated rates, and below a high range, provide medically relevant detections including medication non-compliance. Novel methods of power management and patient monitoring are disclosed.

Systems and Methods are disclosed for detecting acute coronary syndrome (ACS) events, arrythmias, heart rate abnormalities, medication problems such as non-compliance or ineffective amount or type of medication, and demand/supply related cardiac ischemia. The system may have both implanted and external components that communicate with a Physicians's programmer, and smart-devices for monitoring and alerting to detected medically relevant events or states. At least one processor provides event detection using statistical threshold criteria calculated upon at least a portion of a patient's data/distributions and set for a patient or based upon what a doctor determines as abnormal for a patient. Cardiovascular condition is tracked using histogram, trend, and summary information related to heart rate and/or cardiac features such as S-T segment measures of heartbeats. Heartbeats with elevated rates, and below a high range, provide medically relevant detections including medication non-compliance. Novel methods of power management and patient monitoring are disclosed.

Disclosed herein, in some aspects, are systems and methods for detecting, monitoring, and managing a cardiac health status for a subject using ECG data. In some embodiments, the system receives health parameter measurements from one or more devices that are then used by a cardiac health tool (CHT) to determine a cardiac health status. Exemplary health parameter measurements include electrocardiogram (ECG) data from an ECG device and/or weight (from a weight scale for example). As described herein, in some embodiments, determining the cardiac health status includes a) detecting a cardiac condition in the subject, b) predicting a risk of a subject developing a cardiac condition (cardiac condition risk), and/or c) temporal monitoring of a cardiac health status for a subject. In some embodiments, the cardiac health tool is configured to determine the efficacy of a treatment or therapy applied to reduce the severity and/or risk of a cardiac condition.

Disclosed herein, in some aspects, are systems and methods for detecting, monitoring, and managing a cardiac health status for a subject using ECG data. In some embodiments, the system receives health parameter measurements from one or more devices that are then used by a cardiac health tool (CHT) to determine a cardiac health status. Exemplary health parameter measurements include electrocardiogram (ECG) data from an ECG device and/or weight (from a weight scale for example). As described herein, in some embodiments, determining the cardiac health status includes a) detecting a cardiac condition in the subject, b) predicting a risk of a subject developing a cardiac condition (cardiac condition risk), and/or c) temporal monitoring of a cardiac health status for a subject. In some embodiments, the cardiac health tool is configured to determine the efficacy of a treatment or therapy applied to reduce the severity and/or risk of a cardiac condition.