ArticleSensors (Basel, Switzerland)2018
Fusion of Heart Rate, Respiration and Motion Measurements from a Wearable Sensor System to Enhance Energy Expenditure Estimation.
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 19 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
19 citing papers in PubMed.
- A Smart Headband for Multimodal Physiological Monitoring in Human Exercises.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- OpenMetabolics: Estimating energy expenditure using a smartphone worn in a pocket.Communications engineering · 2026Article
- From past to future: a review of methods for assessing physical activity energy expenditure.Journal of health, population, and nutrition · 2025Article
- Oxygen Uptake Prediction for Timely Construction Worker Fatigue Monitoring Through Wearable Sensing Data Fusion.Sensors (Basel, Switzerland) · 2025Article
- Sensors: future tools for detecting young patient's stress during a dental invasive versus a non-invasive dental treatment-a pilot study.European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry · 2025Article
- Combined Impact of Heart Rate Sensor Placements with Respiratory Rate and Minute Ventilation on Oxygen Uptake Prediction.Sensors (Basel, Switzerland) · 2024Article
- The State-of-the-Art Sensing Techniques in Human Activity Recognition: A Survey.Sensors (Basel, Switzerland) · 2022Article
- Comparison of the Validity and Generalizability of Machine Learning Algorithms for the Prediction of Energy Expenditure: Validation Study.JMIR mHealth and uHealth · 2021Article
- Sensing leg movement enhances wearable monitoring of energy expenditure.Nature communications · 2021Article
- Ordinal Statistical Models of Physical Activity Levels from Accelerometer Data.International journal of exercise science · 2021Article
- Biosensors in Occupational Safety and Health Management: A Narrative Review.International journal of environmental research and public health · 2020Review
- Data Analytics and Applications of the Wearable Sensors in Healthcare: An Overview.Sensors (Basel, Switzerland) · 2020Article
- Article
- Textile-Friendly Interconnection between Wearable Measurement Instrumentation and Sensorized Garments-Initial Performance Evaluation for Electrocardiogram Recordings.Sensors (Basel, Switzerland) · 2019Article
- An Active Self-Driven Piezoelectric Sensor Enabling Real-Time Respiration Monitoring.Sensors (Basel, Switzerland) · 2019Article
- Streaming Data Fusion for the Internet of Things.Sensors (Basel, Switzerland) · 2019Article
- Software and Hardware Requirements and Trade-Offs in Operating Systems for Wearables: A Tool to Improve Devices' Performance.Sensors (Basel, Switzerland) · 2019Article
- P-Ergonomics Platform: Toward Precise, Pervasive, and Personalized Ergonomics using Wearable Sensors and Edge Computing.Sensors (Basel, Switzerland) · 2019Article
- A Novel Wearable Device for Continuous Ambulatory ECG Recording: Proof of Concept and Assessment of Signal Quality.Biosensors · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
This paper presents a new method that integrates heart rate, respiration, and motion information obtained from a wearable sensor system to estimate energy expenditure. The system measures electrocardiography, impedance pneumography, and acceleration from upper and lower limbs. A multilayer perceptron neural network model was developed, evaluated, and compared to two existing methods, with data from 11 subjects (mean age, 27 years, range, 21⁻65 years) who performed a 3-h protocol including submaximal tests, simulated work tasks, and periods of rest. Oxygen uptake was measured with an indirect calorimeter as a reference, with a time resolution of 15 s. When compared to the reference, the new model showed a lower mean absolute error (MAE = 1.65 mL/kg/min, R² = 0.92) than the two existing methods, i.e., the flex-HR method (MAE = 2.83 mL/kg/min, R² = 0.75), which uses only heart rate, and arm-leg HR+M method (MAE = 2.12 mL/kg/min, R² = 0.86), which uses heart rate and motion information. As indicated, this new model may, in combination with a wearable system, be useful in occupational and general health applications.
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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.