Digital Endpoints: Heart

Real-World Assessment of Cardiac Outcomes

Real-World Assessment of Cardiac Outcomes

Cardiac outcome measures such as heart rate, arrhythmia, and interbeat intervals are essential indicators of cardiorespiratory diseases. At the same time, heart rate variability (HRV) provides a non-invasive way to study the autonomic nervous system (ANS) and detect a change in a patient's physiologic state.

Wearable Technology

ECG: Wearable electrode sensors are used to measure the heart's electrical activity during each cardiac cycle. The heart's high-resolution voltage is plotted against time to create an electrocardiogram (ECG) and identify heart rhythm abnormalities. The accuracy and complexity of cardiac outcomes derived from ECG technology mainly depend on the number and placement of electrodes. Wearable ECG technology can be implemented in shirt, patch, and strap form factors and range from single to 12-lead.

PPG: PPG sensors provide an alternative form factor to measure pulse rate as a surrogate for heart rate and HRV measures at rest. PPG may also be used to assess decompensation via derived SpO2. Wearable PPG sensors may include the wrist, ring, patch worn form factors, and more standard finger clip sensors that can be used for spot checks and short recording durations.

Outcome Measures

Resting Heart Rate

Sensor Modalities: ECG, PPG

Clinical Use Examples: Identify a response biomarker such as tachycardia events in high-risk patients receiving nutritional intervention for heart health.

Active Heart Rate

Sensor Modalities: ECG

Clinical Use Examples: Monitoring biomarker for outpatient and in-clinic cardiac rehabilitation adherence.

Monitoring biomarker for assessing aerobic capacity during activities of daily living in a longitudinal study of aging.

Heart Rate Variability (HRV)

Sensor Modalities: ECG

Clinical Use Examples: Response biomarker for assessing stress and resiliency in patients receiving treatment for PTSD.

Monitoring Biomarker for assessing the progression of cardiac autonomic neuropathy in patients with type 2 diabetes.

QT Interval

Sensor Modalities: ECG

Clinical Use Examples: Identifying congenital QT interval prolongation as a response biomarker in rare diseases.

Identifying acquired QT interval prolongation as a safety biomarker related to an adverse medication side effect.

Examples of HRV Measures using VivoSense® Software

HRV data from ECG of a single subject visualized in VivoSense.

HRV data from ECG of a single subject visualized in VivoSense.

  • Top - RR interval.
  • Middle - RMSSD measure of HRV time domain.
  • Bottom - Poincare, and Power Spectrum plots.
In this example, multiple HRV regions are identified and outcome measures visualized.

HRV data from ECF of a single subject visualized in Vivosense.

HRV data from ECF of a single subject visualized in Vivosense.

  • Top - RR Interval.
  • Middle - RMSSD measure of HRV time domain.
  • Bottom - LF/HF measure of the HRV frequency domain.
In this example, different subject activities (Base Camp, Sleep, Ascent) are identified and visualized.

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