人們通常會透過聽音樂,來振奮精神、放鬆身心或是幫助睡眠。當人類處於不同的心理狀態,會檢測到不同的的腦電波頻率。而有些音樂可以與人類的腦波產生共振,從而對人的心理狀態產生更好的效果。在腦波中,α波為人們在閉眼休息放鬆時所檢測到的腦波頻率。有幾個醫學報告證明,一些特定的音樂,稱為α波音樂,可以與α波產生共鳴並加強它。因此,當人們休息並同時聽α波音樂時,實現更好的放鬆是非常有幫助的。然而,α波音樂在市場上並不流行,因為它只能通過專業知識人工分類。到目前為止,關於α波音樂自動分類的研究還很少。本研究分析了音樂特徵,並嘗試通過機器學習方法對α波音樂進行分類。
People usually listen music to refresh, relax and help sleep. While humans are in various states of minds, there are different frequencies of brain waves detected. Some music can resonate with human brain waves to achieve the better effect on someone's state of mind. Among brain waves, the alpha wave predominantly appears when people are in wakeful relaxation with closed eyes. There has been several medical reports demonstrated that some specific music, called alpha wave music, can resonate with the alpha wave and strengthen it. Therefore, when people take the rest and listen to the alpha wave music at the same time, it can be very helpful to achieve better relaxing. However, the alpha wave music album is not popular on the market because it only can be classified manually by expertise. Until now, there is still very little research on the automatic identification of alpha wave music. This study analyses the music characterizations and tries to categorize the alpha wave music by machine learning approaches.