Mobile Food Intake Visualization and Voice Recognize (FIVR)

移动食物摄入量可视化和语音识别 (FIVR)

• 批准号: 7340845
• 负责人: Rick Weiss
• 金额: $ 103.97万
• 依托单位: VIOCARE, INC.
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7340845
• 关键词: Accounting; Algorithms; Cellular Phone; Characteristics; Clip; Computer Vision Systems; Data; Data Sources; Databases; Detection; Diet; Diet Records; Diet Research; Dietary intake; Disease; Eating; Electronics; Energy Intake; Environment; Epidemiologic Studies; Film; Food; Food Patterns; Frequencies; Image; Image Analysis; Imagery; Individual; Intake; Internet; Label; Learning; Life; Measurement; Measures; Metabolic; Methods; Modeling; Multimedia; Nutrient; Nutritional Study; Outcome; Patient Self-Report; Phase; Population; Preparation; Process; Protocols documentation; Public Health; Qualitative Evaluations; Quantitative Evaluations; Questionnaires; Reliance; Reminder Systems; Research; Research Personnel; Standards of Weights and Measures; Surveys; System; Systems Analysis; Techniques; Technology; Testing; Time; Visual; Voice; Water; base; cost; experience; feeding; graphical user interface; innovative technologies; novel; programs; size; speech recognition; technology development; tool; voice recognition; ward

DESCRIPTION (provided by applicant): Inadequate dietary intake assessment tools hamper studying relationships between diet and disease. Methods suitable for use in large epidemiologic studies (e.g., dietary recall, food diaries, and food frequency questionnaires) are subject to considerable inaccuracy, and more accurate methods (e.g., metabolic ward studies, doubly-labeled water) are prohibitively costly and/or labor-intensive for use in population-based studies. A simple, inexpensive and convenient, yet valid, dietary measurement tool is needed to provide more accurate determination of dietary intake in populations. We therefore propose a three-phase project to develop and test a new assessment tool called FIVR (Food Intake Visualization and Voice Recognizer) that uses a novel combination of innovative technologies: advanced voice recognition, visualization techniques, and adaptive user modeling in an electronic system to automatically record and evaluate food intake. FIVR uses cell phones to capture both voice recordings and photographs of dietary intake in real-time. These dual sources of data are sent to a database server for recognition processing for real-time food recognition and portion size measurement through speech recognition and image analysis. The user model will allow for enhanced identification of food and method of preparation in situations that images alone might not produce accurate results as the system learns through experience and adapts to the individual's food patterns. Objectives are to fuse existing voice and image recognition techniques into a system that will recognize foods by food type and unique characteristics and determine volume by film clip showing an image from at least two angles. The item identified will be matched to an appropriate food item and amount within a food composition database and nutrient intake computed. Researchers will be able to view the resulting analysis through an adapted version of the dietary analysis program, ProNutra. The proposed protocol will incorporate three discrete phases: 1) technology development, integration, and testing; 2) validity testing with a controlled diet (metabolic ward study); and 3) real-world utility testing. Validity of the data collected will be judged by how closely the nutrient calculations match the known composition of the metabolic ward diets consumed. FIVR has the potential to establish a method of highly accurate dietary intake assessment suitable for cost-effective use at the population level, and thereby advance crucial public health objectives.

描述（由申请人提供）： 饮食摄入量评估工具不足以障碍研究饮食与疾病之间的关系。适用于大型流行病学研究（例如，饮食召回，食物日记和食品频率问卷）的方法可能存在相当大的尚不合理，并且更准确的方法（例如，代谢病房研究，双标记的水）是昂贵的和/或劳动力的基于人群的研究。需要一种简单，便宜，方便但有效的饮食测量工具，以更准确地确定人群中的饮食摄入量。因此，我们提出了一个三相项目，以开发和测试一种称为FIVR（食品摄入可视化和语音识别器）的新评估工具，该工具使用创新技术的新型组合：高级语音识别，可视化技术以及电子系统中的自适应用户建模，以自动记录和评估食品的摄入量。 FIVR使用手机实时捕获饮食摄入量的语音录音和照片。这些双重数据源被发送到数据库服务器，以通过语音识别和图像分析来实时食物识别和部分大小测量。用户模型将允许在系统通过经验学习并适应个人食物模式的情况下，可以增强对食物和制备方法的识别和制备方法。目标是将现有的语音和图像识别技术融合到一个系统中，该系统将通过食物类型和独特的特征识别食物，并通过胶片剪辑确定体积，以显示至少两个角度的图像。所确定的项目将与适当的食品和量相匹配。研究人员将能够通过Pronutra的饮食分析计划的改编版来查看所得分析。提出的协议将结合三个离散阶段：1）技术开发，集成和测试； 2）通过受控饮食进行有效性测试（代谢病房研究）； 3）现实世界实用程序测试。收集到的数据的有效性将以养分计算与所消耗的代谢病房饮食的已知成分相匹配的程度来判断。 FIVR有可能建立一种适合在人群水平上使用具有成本效益的饮食摄入量评估的方法，从而提高关键的公共卫生目标。