Objective Monitoring of Energy Intake and Ingestive Behavior in a Free Living Pop

客观监测自由生活人群的能量摄入和摄入行为

• 批准号: 8135327
• 负责人: EDWARD S SAZONOV
• 金额: $ 17.54万
• 依托单位: UNIVERSITY OF ALABAMA IN TUSCALOOSA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8135327
• 关键词: Adult; Algorithms; Anorexia; Behavior; Behavior Therapy; Cardiovascular Diseases; Cellular Phone; Characteristics; Child; Chronic Disease; Clinical; Computational algorithm; Computers; Consumption; Data; Deglutition; Detection; Development; Devices; Diagnostic; Diet; Diet Records; Eating; Elderly; Energy Intake; Energy Metabolism; Etiology; Event; Feeding behaviors; Food; Frequencies; General Population; Goals; Human; Hyperphagia; Individual; Ingestion; Intervention Studies; Life; Liquid substance; Malignant Neoplasms; Mastication; Measurement; Measures; Methodology; Methods; Metric; Monitor; Multimedia; Non-Insulin-Dependent Diabetes Mellitus; Nutritionist; Obesity; Overweight; Patient Self-Report; Pattern; Persons; Population; Reporting; Research; Research Personnel; Risk; Solid; Technology; Therapeutic; Time; Weight; Weight Gain; World Health Organization; base; design; drinking; food consumption; improved; innovation; monitoring device; physical property; public health relevance; sensor; tool

DESCRIPTION (provided by applicant): Rates of overweight and obesity are increasing globally. The World Health Organization estimated that there were approximately 1.6 billion overweight and at least 400 million obese adults worldwide in 2005. Overweight and obesity increase the risk of developing chronic diseases such as type 2 diabetes, cardiovascular disease and cancer. Overweight and obesity result from an imbalance between energy intake and energy expenditure but the etiology of that imbalance and the underlying mechanisms are still incompletely understood. The devices for monitoring of energy expenditure are well developed and accurate and have been successfully employed in intervention studies. In contrast, methods for monitoring energy intake are inaccurate, tedious, and cumbersome. For example, dietary self-report has been used intensively for the measurement of food intake, but there are numerous shortcomings, particularly in regards to long-term use. Using cameras to assess food intake appears to be comparable to diet but even when multimedia diet records that include tape recorders and cameras are used, it appears that people still underreport their food intake. There is an urgent need for innovative strategies for accurately assessing free-living energy and food intake in humans. The goal of this study is to develop an accurate and objective methodology of assessing free- living ingestive behavior and energy intake. The results of our previous study show that metrics derived from measured chewing and swallowing events can be used to reliably (>95% accuracy) identify each occurrence of food ingestion with fine time granularity of 30s; differentiate between ingestion of solids and liquids (>90% accuracy) and predict the mass of ingested solids and liquids (>90% solids, >80% liquids). We also showed that swallowing instances can be automatically identified by a computer algorithm from the data captured by a miniature microphone. The overall goal of this R21 proposal is to make the next step in methodology development for monitoring of energy intake in free living conditions. Specifically, we will develop methods such that chews and swallowing events can provide additional information about a meal: predict number of distinct foods consumed in the course of meal; estimate mass for each distinct food; predict caloric content of the food based on automatically obtained mass estimates and user - entered food type. This study is expected to validate the methodology under conditions maximally close to unrestricted food intake in free living conditions. The proposed technology is inexpensive and provides unique information about eating patterns which enable research, clinical and consumer applications for diagnostic of ingestive behaviors leading to weight gain (excessive snacking, night eating, evening and weekend overeating) and accurate estimation of daily caloric intake. PUBLIC HEALTH RELEVANCE: The combination of the proposed methods in a miniature wearable device can enable objective diagnostics and monitoring of ingestive behavior and caloric intake in free living population, and can be used by researchers, nutritionists and general population. Applications of the proposed device include 1) study of patterns of food consumption that are indicative of obesity (for use by researchers); 2) a diagnostic tool (for use by a nutritionist/heath adviser) and a behavioral modification tool for correcting known behaviors leading to weight gain (snacking, night eating, weekend or evening overeating); 3) a diagnostic and monitoring tool for caloric intake. The main advantage over existing methods is objective estimation of food intake occurrence and food intake mass (reduction or elimination of underreporting). The sensors can be easily worn by individuals of all sizes, and thus can be used in a wide range of populations (e.g., children, elderly, normal weight individuals, obese individuals, and persons with anorexia). We envision that these sensors will improve our assessment of energy intake in free-living individuals and be useful as a therapeutic tool for behavioral modification of energy intake.

描述（由申请人提供）：全球超重和肥胖率正在增加。世界卫生组织估计，2005年全世界大约有16亿超重和至少4亿肥胖成年人。超重和肥胖会增加患2型糖尿病、心血管疾病和癌症等慢性疾病的风险。超重和肥胖是由于能量摄入和能量消耗之间的不平衡造成的，但这种不平衡的病因和潜在机制仍然不完全清楚。用于监测能量消耗的装置是发达和准确的，并已成功地用于干预研究。相比之下，用于监测能量摄入的方法是不准确的、繁琐的和麻烦的。例如，饮食自我报告已被广泛用于测量食物摄入量，但存在许多缺点，特别是在长期使用方面。使用相机来评估食物摄入量似乎与饮食相当，但即使使用包括录音机和相机在内的多媒体饮食记录，人们似乎仍然少报了他们的食物摄入量。迫切需要创新的策略来准确评估人类的自由生活能量和食物摄入量。本研究的目的是建立一个准确、客观的方法来评估自由生活的摄食行为和能量摄入。我们之前的研究结果表明，从测量的咀嚼和吞咽事件中得出的指标可以用于可靠地（> 95%准确度）识别每次发生的食物摄入，时间粒度为30秒;区分固体和液体的摄入（> 90%准确度），并预测摄入的固体和液体的质量（> 90%固体，> 80%液体）。我们还表明，吞咽情况可以通过计算机算法从微型麦克风捕获的数据中自动识别。这项R21提案的总体目标是在自由生活条件下监测能量摄入的方法开发方面迈出下一步。具体地，我们将开发方法，使得咀嚼和吞咽事件可以提供关于膳食的附加信息：预测在膳食过程中消耗的不同食物的数量;估计每种不同食物的质量;基于自动获得的质量估计和用户输入的食物类型来预测食物的卡路里含量。这项研究预计将在最接近自由生活条件下不受限制的食物摄入的条件下验证该方法。所提出的技术是廉价的，并且提供了关于饮食模式的独特信息，其使得能够用于诊断导致体重增加的摄入行为（过量吃零食、夜间进食、晚上和周末暴饮暴食）的研究、临床和消费者应用以及每日热量摄入的准确估计。 公共卫生关系：所提出的方法在微型可穿戴设备中的组合可以实现对自由生活人群中的摄食行为和热量摄入的客观诊断和监测，并且可以由研究人员、营养学家和普通人群使用。拟议设备的应用包括1）研究表明肥胖的食物消费模式（供研究人员使用）; 2）诊断工具（供营养师/健康顾问使用）和行为矫正工具，用于纠正导致体重增加的已知行为（吃零食、晚上吃饭、周末或晚上暴饮暴食）; 3）热量摄入的诊断和监测工具。与现有方法相比，其主要优点是客观估计食物摄入量和食物摄入量（减少或消除漏报）。传感器可以容易地由所有尺寸的个体佩戴，并且因此可以用于广泛的人群（例如，儿童、老年人、正常体重个体、肥胖个体和厌食症患者）。我们设想，这些传感器将改善我们对自由生活个体能量摄入的评估，并可作为能量摄入行为改变的治疗工具。

项目成果

Automatic identification of the number of food items in a meal using clustering techniques based on the monitoring of swallowing and chewing.

• DOI: 10.1016/j.bspc.2011.11.004
• 发表时间: 2012-09-01
• 期刊: BIOMEDICAL SIGNAL PROCESSING AND CONTROL
• 影响因子: 5.1
• 作者: Lopez-Meyer, Paulo;Schuckers, Stephanie;Makeyev, Oleksandr;Fontana, Juan M.;Sazonov, Edward
• 通讯作者: Sazonov, Edward

Automatic ingestion monitor: a novel wearable device for monitoring of ingestive behavior.

• DOI: 10.1109/tbme.2014.2306773
• 发表时间: 2014-06
• 期刊: IEEE transactions on bio-medical engineering
• 作者: Fontana JM;Farooq M;Sazonov E
• 通讯作者: Sazonov E

A novel approach for food intake detection using electroglottography.

• DOI: 10.1088/0967-3334/35/5/739
• 发表时间: 2014-05
• 期刊: Physiological measurement
• 影响因子: 3.2
• 作者: Farooq M;Fontana JM;Sazonov E
• 通讯作者: Sazonov E

Automatic food intake detection based on swallowing sounds.

基于吞咽声音的自动食物摄入检测。

• DOI: 10.1016/j.bspc.2012.03.005
• 发表时间: 2012
• 期刊: Biomedical signal processing and control
• 影响因子: 5.1
• 作者: Makeyev,Oleksandr;Lopez-Meyer,Paulo;Schuckers,Stephanie;Besio,Walter;Sazonov,Edward
• 通讯作者: Sazonov,Edward