Content-Based Classification of Alpha Wave Music

音樂治療是利用音樂來幫助病人改善他們身心靈的健康。當人們放鬆閉眼休息的時候，人的腦部訊號會產生一種頻率介於8~14Hz間的α (alpha)波。許多的醫學相關研究報告指出，有一些特定的音樂可以與人腦的α波產生共振，並增強此波的產生。如此，這些α波音樂可以幫助人們更加的放鬆紓壓，當人們需要休息時，將可以有很大的幫助。這也就是為什麼人們在放鬆或紓壓時，經常喜歡聽著音樂的緣故。目前對這些α波音樂的分類，都是靠專家做人工辨別。雖然也已經有許多的音樂分類研究被發表，但多是依音樂的風格與流派在分類，例如：搖滾、古典、爵士、鄉村等等。至今還沒有對α波音樂的分類方法研究被提出來。這個研究報告，我們將探討如何對α波音樂做分析分類。 我們的研究成果，希望能幫助發展音樂分類系統更為擴大應用與實用可行，以及期望能對音樂治療方面也有所助益。

The music therapy uses music to help patients to improve or maintain their physical and spiritual health. When people relax with closed eyes, an alpha wave in the frequency range of 8–12Hz appears with brain signals. There were many medical reports proofed that some specific music can resonate with the alpha wave. Therefore, these alpha wave music can improve more relaxing for people and is very helpful when they need to take a rest. That's why people like to listen music when relaxing. Currently, these of specific music are classified manually by expertise only. The existing music classification approaches are almost all categorized by styles and genres, such as pop, classical, jazz, folk, etc. Accordingly, till now, there is no research report studied about classification of alpha wave music. In this research, we will investigate the content-based features of the alpha wave music, and develop the classification method for alpha wave music. We expect our effort can help to expand the applications and develop the more realistic of music classification system as well as to aid music therapy.