CardioBound is an AI-powered cardiac arrhythmia detection and risk stratification wearable designed to make preventive heart care affordable and accessible. Cardiovascular disease remains the leading cause of death worldwide, and millions of individuals (particularly adults over 55 and from underserved communities) lack access to early diagnostic tools. The gold standard for arrhythmia detection include Holter monitors and implantable loop recorders which are prohibitively expensive, invasive, and have short-term monitoring durations. The wearable device leverages four medical-grade sensors: (1) ECG for detecting electrical heart activity, (2) PPG for determining pulse rate and blood circulation, (3) IMU for motion tracking, and (4) a temperature sensor. The sensor array processes this physiological information through three custom computational signal processing techniques and a hybrid CNN-LSTM algorithm for low-latency arrhythmia detection. Additionally, CardioBound conducts predictive risk stratification using an XGBoost machine learning model. Patient data is converted to actionable and clear insights through an easily accessible Flutter mobile application for patients. CardioBound utilizes cost-effective hardware in combination with remote patient monitoring to provide long term preventive care. With its ability to connect clinical accuracy to community accessibility, CardioBound allows for the early intervention of cardiac issues and reduces systemic healthcare inequalities.
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