基于心率变异性分析的睡眠音乐推荐系统

现有睡眠监测研究主要是针对睡眠质量提出非干扰式监测方法的研究,而缺乏对睡眠质量主动调节方法的研究。基于心率变异性(HRV)分析的精神状态以及睡眠分期研究主要集中在这两种信息的获取上,而这两种信息的获取需要佩戴专业医疗设备,并且这些研究缺乏对信息的应用以及调整。音乐可以作为一种解决睡眠问题的非药物类方法,但现有音乐推荐方法并未考虑个体睡眠及精神状态的差异。针对以上问题提出了一种基于移动设备的精神压力和睡眠状态的音乐推荐系统。首先,用手表采集光体积扫描计信号来提取特征并计算心率;其次,将采集的信号通过蓝牙传递给手机,手机通过这些信号评估人的精神压力以及睡眠状态来播放调整音乐;最后,根据个体每晚的入眠时间进行音乐推荐。实验结果表明,在使用睡眠音乐推荐系统后,用户睡眠总时长相较于使用前增长11.0%。

Heart rate variability analysis based sleep music recommendation system

The existing sleep monitoring researches mainly focus on non-interfering monitoring methods for sleep quality, and lack research on active adjustment methods of sleep quality. The researches of mental state and sleep staging based on Heart Rate Variability (HRV) analysis focus on the acquisition of these two kinds of information, which needs people wearing professional medical equipment, and the researches lack the application and adjustment of the information. Music can be used as a non-pharmaceutical method to solve sleep problems, but existing music recommendation methods do not consider the differences in individual sleep and mental states. A music recommendation system according to mental stress and sleep state by mobile devices was proposed to solve above problems. Firstly, the photoplethysmography signals were collected by the watch to extract features and calculate the heart rate. Then, the collected signals were transmitted to the mobile phone via bluetooth, and these signals were used by the mobile phone to evaluate the person’s mental stress and sleep state to play the adjusted music. Finally, the music was recommended according to the sleep time per night of the individual. The experimental results show that after using the sleep music recommendation system, the total sleep time of users increases by 11.0%.