Technologies and Systems for Assessing Human Energy Metabolism and Nutritional Rehabilitation

Recruiting now

Conditions studied: Energy Metabolism, Nutrition, Healthy

In brief

The objective of this observational study is to integrate the doubly labeled water (DLW) database from healthy individuals with multimodal data-including, but not limited to, weight, height, age, sex, race, elevation-from cohorts undergoing rehabilitation following movement impairments or neurological injuries. Machine learning algorithms will be used to develop injury-specific predictive models of energy requirements. The primary research question is: How does energy metabolism change during the rehabilitation process in individuals recovering from traumatic brain injury, stroke, or major surgical procedures? To answer this, participants will undergo a comprehensive set of assessments, including measurements of height and weight, body composition, resting metabolic rate, physical activity levels, total energy expenditure, psychological health, food intake and hunger ratings, sleep quality, cognitive performance, non-invasive brain function monitoring, and gait analysis. Fecal and blood samples will also be collected for untargeted metabolomics analysis.

Key facts

Study ID
NCT07056504
Run by
Shenzhen Institutes of Advanced Technology ,Chinese Academy of Sciences
People needed
80
Starts
2025-07-09
Expected to finish
2025-12-31
Last updated by the study team
2025-09-02

Who can join

Age: 20 and older, up to 70. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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