In today’s modern world with a population of more than 7.5 billion people, the advancement in predicting and diagnosing patients has become preeminent. The most common problem doctors face across the globe in treating the patient is identifying the disease at the eleventh hour or even later. This is not the sole problem of the patients themselves. At the time when the patient consults with the doctor for the disease, mostly it will be untreatable or will be treated just to get side effects post treatment. In the 21st century, while treatment has been modernized and a cure for thousands of diseases has been found compared to the past 4-5 decades, still Coronary Artery Disease (CAD) tolls nearly 15.5% of annual deaths which is nearly 8.8 Million in 2015. This rate is said to be increased quarterly by now. However untreated CAD or treating CAD in the annihilate stage ends up in chest pain, and arrhythmia and even becomes fatal with heart failure

[1]. However, this ratio can be changed to a nominal level if the symptoms or the disease are identified at an earlier stage. In this chapter, we will discuss one of the effective methods for identifying Cardiovascular Diseases at an earlier stage using smart wearables and other non-invasive products. Smart wearables from smartwatches to smart suits and other medical products like non-invasive medical patches will be discussed on how the data collected from these devices helps in predicting CAD after performing exploratory data analysis on the collected dataset. This area of research is currently limited to predicting cardiovascular diseases as only the dataset for CAD is been found with the most accurate data which is easier to discover patterns, spot anomalies, test hypotheses, and check assumptions with the help of summary statistics and graphical representations.

• Smart Wearables,
• Disease Prediction,
• Exploratory Data Analysis,
• Cardiovascular Disease,
• User interface design,
• Coronary Artery Disease

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