基于智能手表数据的人物特征分析技术研究
发布时间：2018-11-03 16:54
【摘要】：智能手表作为可穿戴设备的一种,功能齐全、使用便捷,在健康监测等方面有重要的作用。智能手表的监测数据可以应用于电子取证案件,帮助侦查人员分析人物特征,为侦破案件提供有效的证据或者线索。但是,由于智能手表是近两年爆发式增长的电子产品,目前还没有智能手表数据提取、解析的专门设备,限制了智能手表数据在电子取证领域的广泛应用。因此,本文目的是初步探索智能手表数据的提取与解析方法并进行手表数据的人物特征分析实验研究,为电子数据的取证分析提供借鉴。本文主要采用文献研究法和实验研究法。文献研究法通过阅读相关文献掌握智能手表运动和健康监测的基本工作原理,国内外的发展现状。实验研究法借助FL—900手机取证塔、Oxygen Forensic Analyst和IBM SPSS Statistics 22.0进行智能手表健康和运动监测数据的提取、解析及数据分析的实验研究。本文根据智能手表的用户倾向性,共选取25名20~30岁的青年实验对象,每人佩戴手表一周左右,历时总计7个月进行智能手表数据的人物特征分析实验。实验一是基础性研究实验,主要测试数据提取、解析方法的可行性和手表数据的内容及存储位置。实验二区别清醒状态和睡眠状态,清醒状态:心率不稳定,卡路里消耗大部分在8~15之间,心率变异系数在10%以上;睡眠状态:心率在一段时间内呈水平状,卡路里消耗大部分在4~8之间,心率变异系数在10%以下。实验三区别喝酒状态和正常状态,酒后心率总体上高于正常状态,平均心率高于正常状态约10%,变异系数低于正常状态约30%。实验四区别运动状态和正常状态,运动前和运动后的步数、卡路里、心率数值都相对较小,运动过程中步数、卡路里、心率数值较大,当心率和步数同时出现数值在100以上且占比最大时,考虑处于运动或健身状态。通过基本状态的研究可以有效掌握智能手表用户案发时的状态,为犯罪现场重现提供电子数据支撑。
[Abstract]:As a wearable device, smartwatch has full function, convenient use, and plays an important role in health monitoring and so on. Smart watch monitoring data can be used in electronic forensics cases to help investigators analyze character characteristics and provide effective evidence or clues for detection cases. However, because smartwatch is a explosive growth of electronic products in recent two years, there is no special equipment for data extraction and analysis of smart watches, which limits the wide application of smart watch data in the field of electronic forensics. Therefore, the purpose of this paper is to preliminarily explore the method of extracting and analyzing the data of smart watch and to carry out the experimental research on the character characteristic analysis of the watch data, which can provide reference for the forensic analysis of electronic data. This article mainly uses the literature research method and the experimental research method. The literature research method grasps the basic working principle of smart watch movement and health monitoring by reading the relevant documents, and the development status at home and abroad. The experimental research method uses FL-900 mobile phone forensics tower, Oxygen Forensic Analyst and IBM SPSS Statistics 22.0 to extract, analyze and analyze the data of smart watch health and movement monitoring. According to the user orientation of smart watches, 25 young people aged 20 or 30 years were selected to wear watches for a week or so for a total of 7 months. Experiment one is the basic research experiment, which mainly tests the data extraction, the feasibility of analytical method and the content and storage location of watch data. Experiment 2 distinguishes awake state from sleep state: heart rate is unstable, calorie consumption is mostly between 815 and coefficient of heart rate variability is more than 10%; Sleep state: heart rate is horizontal for a period of time, calorie consumption is mostly between 4g / 8 and HRV is less than 10%. In experiment 3, the drinking state and the normal state were distinguished, the drunk heart rate was higher than the normal state, the average heart rate was about 10 times higher than the normal state, and the coefficient of variation was about 30% lower than the normal state. Experiment 4 distinguishes the movement state from the normal state, the number of steps, calories, heart rate are relatively small before and after exercise, the number of steps, calories, heart rate are larger during exercise. When the heart rate and the number of steps at the same time more than 100 and the largest proportion, consider in exercise or fitness state. Through the research of basic state, we can effectively grasp the state of smart watch user at the time of crime, and provide electronic data support for crime scene reproduction.
【学位授予单位】：中国政法大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：D918
本文编号：2308379
[Abstract]:As a wearable device, smartwatch has full function, convenient use, and plays an important role in health monitoring and so on. Smart watch monitoring data can be used in electronic forensics cases to help investigators analyze character characteristics and provide effective evidence or clues for detection cases. However, because smartwatch is a explosive growth of electronic products in recent two years, there is no special equipment for data extraction and analysis of smart watches, which limits the wide application of smart watch data in the field of electronic forensics. Therefore, the purpose of this paper is to preliminarily explore the method of extracting and analyzing the data of smart watch and to carry out the experimental research on the character characteristic analysis of the watch data, which can provide reference for the forensic analysis of electronic data. This article mainly uses the literature research method and the experimental research method. The literature research method grasps the basic working principle of smart watch movement and health monitoring by reading the relevant documents, and the development status at home and abroad. The experimental research method uses FL-900 mobile phone forensics tower, Oxygen Forensic Analyst and IBM SPSS Statistics 22.0 to extract, analyze and analyze the data of smart watch health and movement monitoring. According to the user orientation of smart watches, 25 young people aged 20 or 30 years were selected to wear watches for a week or so for a total of 7 months. Experiment one is the basic research experiment, which mainly tests the data extraction, the feasibility of analytical method and the content and storage location of watch data. Experiment 2 distinguishes awake state from sleep state: heart rate is unstable, calorie consumption is mostly between 815 and coefficient of heart rate variability is more than 10%; Sleep state: heart rate is horizontal for a period of time, calorie consumption is mostly between 4g / 8 and HRV is less than 10%. In experiment 3, the drinking state and the normal state were distinguished, the drunk heart rate was higher than the normal state, the average heart rate was about 10 times higher than the normal state, and the coefficient of variation was about 30% lower than the normal state. Experiment 4 distinguishes the movement state from the normal state, the number of steps, calories, heart rate are relatively small before and after exercise, the number of steps, calories, heart rate are larger during exercise. When the heart rate and the number of steps at the same time more than 100 and the largest proportion, consider in exercise or fitness state. Through the research of basic state, we can effectively grasp the state of smart watch user at the time of crime, and provide electronic data support for crime scene reproduction.
【学位授予单位】：中国政法大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：D918
【相似文献】
相关硕士学位论文 前1条
1 王春露;基于智能手表数据的人物特征分析技术研究[D];中国政法大学;2017年
，本文编号：2308379
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