BCI AND MACHINE LEARNING IN THE FIELD OF MEDICINE

BCI AND MACHINE LEARNING IN THE FIELD OF MEDICINE

A Anaswara Sreelakshmi (IMCA-195) Student, Department of Computer Applications SCMS School of Technology and Management

Kochi, India

IMCA-195@scmsgroup.org

Ms. Jisha Liju Daniel

Associate Professor, Department of Computer Applications SCMS School of Technology and Management

Kochi, India jishaliju@scmsgroup.org

Abstract—Brain computer interface (BCI) has shown great potential for use in medical applications, allowing for direct communication between the brain and external devices. Various algorithms have been utilized in BCI for medical applications, including Common Spatial Patterns (CSP), Support Vector Machines (SVM), Deep Learning, Hidden Markov Models (HMMs), and Linear Discriminant Analysis (LDA). These algorithms have been used for tasks such as decoding movements, classifying mental states, and controlling prosthetic devices. The choice of algorithm will depend on the specific BCI application and the type of data being analyzed.
Keywords—;BCI;CSP;SVM;HMM LDA.