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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 qua
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