A method for detecting anomaly and discovering pattern in a signal using symbolic representation of the signal, the method comprising a processor implemented steps of: sensing the signal from a person using a sensor, wherein the signal is a time series signal with a plurality of time points; finding a plurality of maxima points and a plurality of minima points in the signal, wherein the plurality of maxima points and the plurality of minima points are following morphology of the signal; deriving a plurality of features using the plurality of maxima points and the plurality of minima points which are adjacent to each other, wherein the plurality of features comprises amplitude difference and number of sampling points between minima to maxima points which are adjacent to each other and amplitude difference and number of sampling points between maxima to minima points which are adjacent to each other; performing a proximity based clustering on the plurality of features to get cluster centroid values corresponding to each of the plurality of features; representing the cluster centroid values in the form of a plurality of symbols in the descending order of the cluster centroid values in terms of the amplitude difference and the number of sampling points corresponding to minima to maxima points and maxima to minima points; representing the signal into a symbolic form using the plurality of symbols, wherein the symbolic form comprising one or more strings of symbols; representing the string of symbols using minima to maxima points and maxima to minima points encoded by their corresponding occurrences of cluster centroid values in their consecutive order of occurrences, wherein the encoding of occurrence of consecutive minima to maxima points and consecutive maxima to minima points are based on a pair of symbols known as pattern atoms, deriving a dissimilarity metric, wherein the dissimilarity metric is a function of: regularity of the strings of symbols, and a distance measure between the string of symbols for detecting anomalous patterns; and detecting the anomalous pattern in the signal using the dissimilarity metric. sensing the signal from a person using a sensor, wherein the signal is a time series signal with a plurality of time points; finding a plurality of maxima points and a plurality of minima points in the signal, wherein the plurality of maxima points and the plurality of minima points are following morphology of the signal; deriving a plurality of features using the plurality of maxima points and the plurality of minima points which are adjacent to each other, wherein the plurality of features comprises amplitude difference and number of sampling points between minima to maxima points which are adjacent to each other and amplitude difference and number of sampling points between maxima to minima points which are adjacent to each other; performing a proximity based clustering on the plurality of features to get cluster centroid values corresponding to each of the plurality of features; representing the cluster centroid values in the form of a plurality of symbols in the descending order of the cluster centroid values in terms of the amplitude difference and the number of sampling points corresponding to minima to maxima points and maxima to minima points; representing the signal into a symbolic form using the plurality of symbols, wherein the symbolic form comprising one or more strings of symbols; representing the string of symbols using minima to maxima points and maxima to minima points encoded by their corresponding occurrences of cluster centroid values in their consecutive order of occurrences, wherein the encoding of occurrence of consecutive minima to maxima points and consecutive maxima to minima points are based on a pair of symbols known as pattern atoms, deriving a dissimilarity metric, wherein the dissimilarity metric is a function of: regularity of the strings of symbols, and a distance measure between the string of symbols for detecting anomalous patterns; and regularity of the strings of symbols, and a distance measure between the string of symbols for detecting anomalous patterns; and detecting the anomalous pattern in the signal using the dissimilarity metric.