基于APP夜磨牙症非接触型监测方法研究

发布时间：2018-06-12 17:51

本文选题：磨牙症 + 传感器　；参考：《山西医科大学》2017年硕士论文

【摘要】：目的:为探究磨牙症的监测方法,运用非接触型无线传输监测系统,采集磨牙症患者睡眠状态下磨牙时下颌骨振动产生的生物信号,分析其特征及与睡眠周期的关系,为磨牙症启动及结束机理提供依据。方法:筛选符合标准的夜磨牙症受试者20例,应用非接触型无线传输监测系统连续监测3日,监测装置于受试者枕下采集磨牙时下颌骨振动的生物信号,经可折叠线缆与主体控制器连接,内部完成A/D转换成数字电信号,并进行数据储存,安装手机(Application APP)绑定设备蓝牙,完成监测设备的wifi配置,与云端建立链接,上传数据至手机及云端,电脑APP下载处理分析每日数据;监测的同时开启录音设备,采集受试者整夜睡眠时声音信号,分别提取同一时间相对应的磨牙声音信号及振动信号,作为声谱组及振动组,记录每日总磨牙时间、最长磨牙时间、整夜磨牙频率及睡眠周期,以声音信号为基准运用统计学方法验证该监测方法的稳定性及一致性。结果:1.获得受试者每晚睡眠状态下的原始波形曲线,依此设计滤波算法得到过滤处理后的磨牙波形曲线,分析整理得到整夜磨牙频率、磨牙时间、运动幅值;2.配对t检验分析:声谱组和振谱组受试者每日总磨牙时间及最长磨牙时间相比,两组间差异无统计学意义(P0.05);3.声谱组和振谱组每日整夜磨牙频率相比无显著差异(p0.05),两组具有较高的一致性;4.声谱组及振谱组3日的总磨牙时间及最长磨牙时间(各60对数据)配对t检验无统计学意义(p0.05),且经一致性检验Bland-Altman分析:每组仅有2/(60)3.3%个点位于95%一致性界限外,两组具有较高的一致性;5.亦可分析出每晚睡眠状态下睡眠周期、心率及体动变化指示图,尚无规律可寻,有待于扩展病例继续深入研究;6.依据睡眠周期变化指示图,测得20例受试者每日磨牙事件主要集中于(Rapid eye movement REM)期及浅睡眠期。结论:1.非接触型磨牙症监测系统实现了磨牙信息的数字化表达与信息存储分析,携带便捷;2.针对睡眠状态下磨牙时下颌骨振动信号进行监测,为监测研究磨牙症的启动及结束机理提了提供了新的方法;3.与声音信号相比一致性较高,且二者的波性特征均表现为“双峰波”,说明本监测系统不仅提供了稳定的监测结果而且可靠性较大。
[Abstract]:Objective: to investigate the monitoring method of molars, a non-contact wireless transmission monitoring system was used to collect the biological signals produced by mandibular vibration of molars during sleep in patients with molars, and to analyze the relationship between the characteristics and sleep cycles. To provide the basis for the initiation and ending mechanism of molars. Methods: twenty patients with night-molar disease were selected and monitored by non-contact wireless transmission monitoring system for 3 consecutive days. The monitoring device collected the biological signals of mandibular vibration under the occipital. After the folding cable is connected to the main controller, the internal Ar / D is converted into digital electrical signal, and data is stored, the mobile phone application app) binding device is installed, the wifi configuration of the monitoring device is completed, and the link with the cloud is established. Upload data to mobile phone and cloud, download and analyze daily data by computer app, turn on recording equipment while monitoring, collect sound signals of subjects sleeping all night, extract corresponding sound signals and vibration signals of molars at the same time. As acoustic spectrum group and vibration group, the total molar time, the longest molar time, the frequency of molars all night and the sleep cycle were recorded. The stability and consistency of the method were verified by statistical method based on sound signal. The result is 1: 1. The original waveform curve of the subjects under the condition of sleep every night was obtained, and the filtering algorithm was designed to get the waveform curve of the molars after filtering. The frequency of the molars, the time of the molars and the amplitude of motion were obtained by analyzing and arranging the waveforms of the molars after filtering. Paired t-test analysis: the total molar time and the longest molar time of the subjects in the sonographic group and the vibrational group were not significantly different between the two groups (P 0.05). There was no significant difference in the frequency of molars between the sonographic group and the vibrational spectrum group (P 0.05), and there was a high consistency between the two groups. The total molar time and the longest molar time (60 pairs of data each) in the sonographic group and the vibratory spectrum group had no statistical significance (p 0.05), and the Bland-Altman analysis showed that only 2 / 60 points were located outside the 95% consistency limit in each group, and Bland-Altman analysis showed that the total molar time and the longest molar time (60 pairs of data) in each group were above the 95% consistency limit. The two groups had high consistency. It can also be used to analyze the indicators of sleep cycle, heart rate and body movement under the condition of sleep every night, but there is no regular pattern to be found, which needs to be further studied in extended cases. According to the indicator diagram of sleep cycle change, the daily molar events in 20 subjects were mainly concentrated in the rapid eye movement period and the shallow sleep stage. Conclusion 1. The monitoring system of non-contact molars realizes the digital expression and information storage of molars, which is easy to carry. Monitoring the vibration signal of mandible during sleep provides a new method for monitoring the initiation and ending mechanism of molars. Compared with sound signals, the characteristics of both of them are "bimodal waves", which indicates that this monitoring system not only provides stable monitoring results, but also has greater reliability.
【学位授予单位】：山西医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R781.2;R318.0

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