Sökning: WFRF:(Forsman Mikael)
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Fusion of heart rat...
Fusion of heart rate, respiration and motion measurements from a wearable sensor system to enhance energy expenditure estimation
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- Lu, Ke (författare)
- KTH,Skolan för kemi, bioteknologi och hälsa (CBH),Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden
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- Yang, Liyun (författare)
- Karolinska Institutet,KTH,Ergonomi
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- Seoane, F. (författare)
- Karolinska Institutet
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- Abtahi, Farhad, 1981- (författare)
- Karolinska Institutet,KTH,Skolan för kemi, bioteknologi och hälsa (CBH),Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden
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- Forsman, Mikael (författare)
- Karolinska Institutet,KTH,Ergonomi,Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden
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- Lindecrantz, K. (författare)
- Karolinska Institutet
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(creator_code:org_t)
- 2018-09-14
- 2018
- Engelska.
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 18:9
- Relaterad länk:
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https://doi.org/10.3...
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https://www.mdpi.com...
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https://urn.kb.se/re...
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https://doi.org/10.3...
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http://kipublication...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences (hsv//eng)
Nyckelord
- Accelerometer
- Energy expenditure
- Impedance pneumography
- Neural network
- Wearable device
- Accelerometers
- Heart
- Neural networks
- Energy expenditure estimation
- Mean absolute error
- Motion measurements
- Multi-layer perceptron neural networks
- Wearable devices
- Wearable sensor systems
- Wearable sensors
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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