The purpose of this study is to find out if there are any patterns in the way people's bodies react to physical activities and their voices when they have heart failure, a disease where the heart cannot function sufficiently. To do this, the investigators will use a smartwatch that can measure multiple signals like the participant's heart rate and movement. Investigators will ask participants with and without heart failure to wear the Watch HOP (from HOP-Child Technologies Inc.) and sensors during physical tasks at their clinic visit at the McGill University Health Centre. Researchers will also record the participants' voices between their visits. The key signals can help find who is at risk for heart failure or develop new ways to monitor and treat it.

Heart Failure (HF) is a multi-faceted and life-threatening syndrome characterized by significant morbidity and mortality, poor functional capacity and quality of life, and high costs. Logistic and economic difficulties prove screening for HF challenging for some populations, such as people with reduced mobility and the elderly. Sensor technologies and data processing algorithms, including artificial intelligence, represent an opportunity to systematically identify patients suffering from HF as a complementary tool for echocardiography. The ability to compute digital biomarkers using complex models from wearable data requires identifying the key parameters that are associated with the presence of HF. A multisensorial wearable device can be utilized to develop digital biomarkers for population-based screening of HF. The present study aims to evaluate the best signals from a wearable device to identify digital signals (aka digital biomarkers) that are most associated with HF, including all ejection fraction types.

For this study, investigators will recruit 27 participants with HF and 27 without HF. The primary objective of this study is to analyze the key physiological parameters recorded from the platform devices that can develop a digital biomarker for the presence of prevalent HF and its markers like NTproBNP, KCCQ, and 6MWD

Inclusion Criteria:

1. Able to follow up with the study protocol schedule

2. Life expectancy > 1 year

3. Case group only

   1. Clinical signs and/or symptoms of heart failure caused by a structural and/or functional cardiac abnormality, as defined by Bozkurt et al. [2021], diagnosed at the cardiovascular clinic
   2. NT-proBNP levels > 125 pg/L or objective evidence of cardiogenic pulmonary or systemic congestion
   3. One of the following;

   i. For HFpEF, LVEF ≥ 50% ii. For HFmrEF, LVEF 41-49% iii. For HFrEF, LVEF ≤ 40%

4. Control group only

   1. Absence of known clinical heart failure history.
   2. Absence of criteria above in the case group.

Exclusion Criteria:

1. Any person who does not meet the above criteria or who refuses to participate

2. Undergoing chemotherapy or dialysis

3. In addition, the following list of criteria are specific to accurate wrist wearable measurements:

   1. Skin burns or rashes on the measurement locations (wrist for wearable, finger for oximeter, chest for Polar ECG)
   2. Patients with tremors
   3. Recent use of dermatological creams, ointments, or lotions at the recording area

1. Case group will be enrolled from the cardiology clinics at the Royal Victoria Hospital (located at MUHC). Patients will be screened for on the clinic lists on a daily basis. The attending physician will be asked if the patient is suitable for enrollment. The participant will be approached, and the informed consent will be taken before enrollment.
2. Control group will be recruited from both the cardiology clinics (patients without heart failure) and Cortois Cardiovascular Signature Program, also at the Royal Victoria Hospital. Patients will be screened for on the clinic lists on a daily basis. The attending physician will be asked if the patient is suitable for enrollment. The participant will be approached, and the informed consent will be taken before enrollment.