| The sleep quality at night affects people’s daily life and physical health.With the rapid development of society,people’s life style changes gradually.In order to have enough energy to cope with daily life and work,people also have more attention and higher requirements for the sleep quality.At the same time,due to the continuous development of science and technology,the cost of living increased significantly.People’s daily needs continue to increase and upgrade,which also bring more pressure for themselves and their families.Today,many middle-aged and elderly people have insomnia,sleep apnea and other sleep disorders.The sleep quality of people related to the daily work of the state,good health,and even life safety.Good sleep is an important guarantee for maintaining physical and mental health.In the process of sleep,the normal steady breathing and heartbeat can promote blood circulation,provide adequate oxygen for the body to support metabolism and improve sleep quality.High-quality sleep can enhance their immunity and prolong cell activity.Meanwhile,it is essential for young people’s physical and mental health conditions.Moreover,at night,the adequate and healthy sleep of the elderly people can make the body and mind get enough rest for the daily life and provide protection for tomorrow work.For the sleep health issues of elderly people,the thesis designs a sleep monitoring mattress,which has a alarm system with providing long auscultation and analysis of the symptoms and signs when elderly people slept.The thesis collected the signal of human body using the hardware system and extracted the cardiac shock signal for research by empirical mode decomposition method.Empirical Mode Decomposition is a new kind of signal processing technology.Its good adaptability is very suitable for the analysis of nonlinear and nonstationary signals.Based on the traditional EMD signal processing method,this thesis improved the old method in order to adapt the characteristics of the study data and achieved the better decomposition performance.The improved empirical mode decomposition signal processing method is used to decompose the collected data.The analysis of heart rate variability was performed on the processed cardiac shock signals.Heart rate variability,which indicates a small fluctuation of the human body’s normal heartbeat cycle,contains a lot of information about human cardiovascular diseases.The information on heart rate variability obtained by heart shock signal analysis can help to realize daily sleep monitoring and detection in order to prevent the vascular disease.The thesis introduced the principles of EMD algorithm,the basic concepts of instantaneous frequency components,the detailed decomposition steps and the definition of Hilbert transform.Furthermore,the method of adding Gaussian white noise is applied to solve the problems of modal aliasing in the decomposition process.In the aspect of algorithm improvement,the envelope fitting method is optimized.On the other hand,the method of dealing with boundary effects such as the most relevant waveform fitting method is analyzed.Finally,the boundary flying problem is solved by fitting the upper and lower envelope boundary points.Then,the eight groups of vibration signal of experimenters were decomposed by t he improved empirical mode decomposition algorithm,and the pure heart impact signal was extracted and analyzed in the three aspects of time domain,frequency domain and nonlinear heart rate variability. |
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