ArticleSensors (Basel, Switzerland)2018
Quantitative Contact-Less Estimation of Energy Expenditure from Video and 3D Imagery.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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Who cites it
4 citing papers in PubMed.
- From past to future: a review of methods for assessing physical activity energy expenditure.Journal of health, population, and nutrition · 2025Article
- Ambient and Wearable Sensor Technologies for Energy Expenditure Quantification of Ageing Adults.Sensors (Basel, Switzerland) · 2022Article
- Depth-Camera Based Energy Expenditure Estimation System for Physical Activity Using Posture Classification Algorithm.Sensors (Basel, Switzerland) · 2021Article
- Quantifying Physical Activity in Young Children Using a Three-Dimensional Camera.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Measurement of energy expenditure is an important tool in sport science and medicine, especially when trying to estimate the extent and intensity of physical activity. However, most approaches still rely on sensors or markers, placed directly on the body. In this paper, we present a novel approach using a fully contact-less, fully automatic method, that relies on computer vision algorithms and widely available and inexpensive imaging sensors. We rely on the estimation of the optical and scene flow to calculate Histograms of Oriented Optical Flow (HOOF) descriptors, which we subsequently augment with the Histograms of Absolute Flow Amplitude (HAFA). Descriptors are fed into regression model, which allows us to estimate energy consumption, and to a lesser extent, the heart rate. Our method has been tested both in lab environment and in realistic conditions of a sport match. Results confirm that these energy expenditures could be derived from purely contact-less observations. The proposed method can be used with different modalities, including near infrared imagery, which extends its future potential.
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Registered trials
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