A system that uses biometric data to facilitate learning is provided herein. The system receives at least two data points via a biometric sensor. Information is extracted from the at least two data points and a set of features are identified. Data analysis is then performed on the set of features.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for using biometric data to facilitate learning comprising: a data acquisition engine to obtain at least two data points from biometric sources; a data aggregation engine to gather a filtered biometric data set by extracting information from the at least two data points; a signal processing engine to identify a set of features selected from the filtered biometric data set; and a data analysis engine to correlate the set of features selected to at least two learning characteristics. 2. The system of claim 1, wherein the signal processing engine uses the set of features to generate a feature matrix and performs feature reduction on the feature matrix. 3. The system of claim 2, wherein the data analysis engine applies a machine learning modeling executed by a processor to the feature matrix and outputs discovered correlations. 4. The system of claim 2, wherein the data analysis engine applies a predictive model to the feature matrix to identify relationships between the set of features and a learning characteristic. 5. The system of claim 1, wherein the data aggregation engine removes unnecessary sensor data from the at least two data points. 6. A non-transitory computer-readable storage medium encoded with instructions that, when executed by a processor performs a method, causes the process to: receive at least two data points via a biometric sensor; extract a collection of learning data from the at least two data points; identify a set of features from the collection of learning data and perform feature reduction on the set of features; and analyze the set of features after the feature reduction to correlate the set of features to at least two learning characteristics. 7. The non-transitory computer-readable storage medium of claim 6, wherein the set of features are mapped to the at least two learning characteristics and a classifier is trained to distinguish between the at least two learning characteristics. 8. The non-transitory computer-readable storage medium of claim 6, wherein the set of features are analyzed using the collection of learning data without applying additional functions. 9. The non-transitory computer-readable storage medium of claim 6, wherein at least one of the at least two data points are obtained from the biometric sensors selected from a facial sensor and a wearable device. 10. A method to use biometric data to facilitate learning comprising: obtaining at least two types of biometric data via a sensing device; extracting a collection of learning data from the at least two types of biometric data; selecting a set of features to represent the collection of learning data and removing features from the set of features to form a subset of the set of features; and performing data analysis on the subset of the set of features. 11. The method of claim 10, further comprising applying data fusion technology on the subset of the set of features to categorize the collection of learning data for each learner. 12. The method of claim 10, wherein performing data analysis comprises identifying hidden patterns in the subset of the set of features to obtain a learning characteristic. 13. The method of claim 10, wherein performing data analysis comprises performing predictive modeling on the subset of the set of features to obtain a learning characteristic. 14. The method of claim 10, further comprising removing non-related biometric data to create the set of features. 15. The method of claim 14, further comprising manipulating the set of features by extracting the subset of the set of features identified as corresponding to learning characteristics.