ArticleJournal of health, population, and nutrition2025
From past to future: a review of methods for assessing physical activity energy expenditure.
Article in Journal of health, population, and nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Recalibrating Resting Energy Expenditure Prediction Equations in Asian Older Adults with Multimorbidity.Nutrients · 2026Article
- The Impact of Burnout on Body Composition in Medical Staff.Medicina (Kaunas, Lithuania) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundPhysical activity energy expenditure (PAEE) assessment is important for helping individuals maintain energy balance. This study adopts a technological evolution perspective to systematically examine the historical evolution and current progress of PAEE assessment methods, aiming to clarify future development directions.
methodsThis study employs a narrative review methodology. The "Past" section presents a chronological account of the historical development of the PAEE assessment methodology, whereas the "Present" section synthesizes recent advances in the application of intelligent technologies to PAEE assessment based on a systematic literature search. Relevant literature was identified through comprehensive searches of the Web of Science, PubMed, IEEE Xplore, and China National Knowledge Infrastructure (CNKI) databases.
resultsThe historical evolution of PAEE assessment methods can be divided into three periods: initial emergence (late 18th century to mid-19th century), gradual exploration (late 19th century to early 20th century), and steady development (mid-20th century to late 20th century). PAEE assessment enters the intelligent era now, with the application of artificial intelligence (AI) technology primarily focused on two main areas: machine learning (ML) and computer vision (CV). However, there are still some shortcomings. Therefore, future efforts should focus on advancing technological innovations in intelligent PAEE assessment, expanding the application scenarios of intelligent PAEE assessment, and mitigating the ethical risks associated with intelligent PAEE assessment to enhance the effect of AI in PAEE assessment.
conclusionsThe historical evolution of PAEE assessment has undergone three stages: initial formation, gradual exploration, and steady development. Currently, the application of AI technology in PAEE assessment is mainly concentrated in the two major fields of ML and CV, but it still faces many challenges. In the future, it will be necessary to promote technological innovation, expand application scenarios, and mitigate ethical risks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.