Statistical and Salient Features Analysis on Acoustic Signal For Medical and Educational Applications

Abstract

In this report, statistical and salient features have been extracted for acoustic signals in medical and educational applications. In recent 2 to 3 years, the whole world has witnessed a lockdown in the COVID-19 situation. The world's communication was down physically during this period, but they had connected through online communication. However, the main reason is that in this COVID-19 situation, online education is becoming much more popular. Now, most people are familiar with online education. However, most learners faced a common problem. The instructor's voice is not clear. When the instructor recorded the audio or live online education, the audio signal is mixed with unwanted noise like instrumental, environmental, etc. Telemedicine has become a major part also in this pandemic and doctors can communicate with the patient over voice and instruct them what to do in critical situations when a patient is unable to go to the hospital or the circumstance is not letting the patient go to the hospital. In both cases, students and patients or doctors face the same kind of problem, as a result, both medical and educational sides are being focused. In this work, especially the notch filter which has been used provides a better result as a solution and it eliminates the 60 Hz instrumented signal. The graphs are used for comparison and it is being clarified why the notch filter is used and how it performs.