Machine Learning Techniques for Remote Healthcare

In this chapter, popular machine learning techniques are discussed in the context of remote healthcare. In this domain the main challenges are low computational complexity and hardware implementation, and not just conventional way of mathematical analysis of machine learning algorithms. Statistical view-point of different machine learning techniques, standard parametric and nonparametric algorithms for classification and clustering are briefly discussed. A practical 12-lead Electrocardiogram (ECG) signal based myocardial scar classification example has also been shown as a representative example. Complexity of few classification algorithms, online implementation issues for statistical feature extraction and some open research problems have also been introduced briefly.