[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100621510":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":15,"locations":25,"responsibleParty":43,"collaborators":10,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":10,"eligibilityCriteria":53,"healthyVolunteers":54,"sex":55,"minAge":56,"maxAge":57,"enrollmentInfo":58,"targetDuration":10,"studyType":61,"phases":10,"briefSummary":62,"conditions":63,"keywords":65,"overallStatus":28,"whyStopped":10,"lastUpdateSubmitDate":69,"lastUpdatePostDateStruct":70,"startDateStruct":73,"completionDateStruct":75,"leadSponsor":77,"locationsCount":78},{"fullName":5,"class":6},"Shenzhen Institutes of Advanced Technology ,Chinese Academy of Sciences","OTHER",[8,12],{"label":9,"type":10,"description":11,"interventionNames":10},"Control",null,"21.5≤BMI\\\u003C25, age between 25-40 years old, 100subjects.",{"label":13,"type":10,"description":14,"interventionNames":10},"Superlean","15\\\u003CBMI≤18.5, age between 25-40 years old, 100 subjects.",[16,21],{"name":17,"role":18,"phone":19,"phoneExt":10,"email":20},"John Roger Speakman, PhD","CONTACT","15810868669","j.speakman@abdn.ac.uk",{"name":22,"role":18,"phone":23,"phoneExt":10,"email":24},"Ying Yu, PhD","18513508048","y.yu@siat.ac.cn",[26],{"facility":27,"status":28,"city":29,"state":30,"zip":10,"country":31,"countryCode":32,"cosmosGeoPoint":33,"geoPoint":38,"contacts":39},"Shenzhen Institute of Advanced Technology","RECRUITING","Shenzhen","Guangdong","China","CN",{"type":34,"coordinates":35},"Point",[36,37],114.0683,22.54554,{"lat":37,"lon":36},[40],{"name":41,"role":18,"phone":42,"phoneExt":10,"email":20},"John Speakman, PhD","13466654659",{"type":44,"investigatorFullName":45,"investigatorTitle":46,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","John R. Speakman","Professor","100621510","assessment-of-food-intake-using-both-3d-scanning-method-and-a-photographic-method-100621510",false,"NCT07371559","Assessment of Food Intake Using Both 3D Scanning Method and a Photographic Method","Assessment of Calories in the Diets Using 3D Scanning and a Photographic Method","Inclusion Criteria:\n\nRecently measured body mass index (BMI): normal control group (21.5 ≤ BMI \\\u003C 25); Recently measured body mass index (BMI): healthy underweight group (15 \\\u003C BMI ≤ 18.5); Must be able to choose the food as requested.\n\nExclusion Criteria:\n\nMetabolic diseases; Recent weight loss due to various disease causes; Ongoing treatment for weight loss; Eating disorders; Pregnant or lactating women; Infectious diseases such as HIV, Hepatitis; Diabetes mellitus.",true,"ALL","22 Years","40 Years",{"count":59,"type":60},200,"ESTIMATED","OBSERVATIONAL","This project aims to develop a new and more accurate method to assess energy intake in the diet by collaborating with Astravis company in Switzerland, integrating image recognition and intelligent applications, to improve the accuracy of energy assessment in the food, and to explore the application in dietary research.The researchers will recruit 200 volunteers.",[64],"Data Collection",[66,67,68],"food intake","food preference","food energy assessment","2026-01-19",{"date":71,"type":72},"2026-01-28","ACTUAL",{"date":74,"type":60},"2026-01-31",{"date":76,"type":60},"2026-12-31",{"name":5,"class":6},1]