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Heart rate variability analysis using neural network models for automatic detection of lifestyle activities

机译:使用神经网络模型进行心率变异性分析以自动检测生活方式活动

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The quality of life and individual well-being are crucial factors in disease prevention. Particularly, healthy lifestyle lessens the risk and occurrence of main diseases, such as cardiovascular diseases and metabolic disorders. Since a patient has an active role in being a co-producer of his/her health, innovative devices and technologies have been devoted to helping folks in self-evaluation and expected to play a key role to maintain their well-being. In this work, we present a very promising assessment tool for health, Heart Rate Variability (HRV). HRV is the difference in time between one heartbeat and the next. HRV measurement is simple and non-invasive, it is derived from recording of electrocardiogram (ECG) on free-moving subjects. The main aim of this work is to investigate the dynamics in the autonomic regulation of the heart rate by using frequency and temporal analysis to correlate between the HRV and these physiological patterns.
机译:生活质量和个人福祉是疾病预防的关键因素。特别地,健康的生活方式减少了诸如心血管疾病和代谢紊乱等主要疾病的风险和发生。由于患者在成为其健康的共同生产者中扮演着积极的角色,因此创新的设备和技术致力于帮助人们进行自我评估,并有望在维持其健康方面发挥关键作用。在这项工作中,我们提出了一种非常有前途的健康评估工具,即心率变异性(HRV)。 HRV是一个心跳与下一个心跳之间的时间差。 HRV测量是简单且无创的,它源自对自由活动对象的心电图(ECG)记录。这项工作的主要目的是通过使用频率和时间分析来将HRV与这些生理模式相关联,以研究心律自主调节的动力学。

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