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Fusion of heart rat...
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Lu, KeKTH,Skolan för kemi, bioteknologi och hälsa (CBH),Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden
(författare)
Fusion of heart rate, respiration and motion measurements from a wearable sensor system to enhance energy expenditure estimation
- Artikel/kapitelEngelska2018
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2018-09-14
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MDPI AG,2018
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LIBRIS-ID:oai:DiVA.org:kth-236691
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https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-236691URI
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https://doi.org/10.3390/s18093092DOI
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http://kipublications.ki.se/Default.aspx?queryparsed=id:139421347URI
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Språk:engelska
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Sammanfattning på:engelska
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Export Date: 22 October 2018; Article; Correspondence Address: Ke, L.; School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, Sweden; email: kelu@kth.se; Funding details: 18454; Funding details: Dnr 150039; Funding text: Funding: This work was supported by AFA Insurance under Grant Dnr 150039, EIT Health under project no. 18454 “Wellbeing, Health and Safety @ Work”, and CSC Scholarship Council. QC 20181112
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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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Yang, LiyunKarolinska Institutet,KTH,Ergonomi(Swepub:kth)u1cdwezt
(författare)
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Seoane, F.Karolinska Institutet
(författare)
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Abtahi, Farhad,1981-Karolinska Institutet,KTH,Skolan för kemi, bioteknologi och hälsa (CBH),Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden(Swepub:kth)u17ajigh
(författare)
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Forsman, MikaelKarolinska Institutet,KTH,Ergonomi,Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden(Swepub:kth)u1iq0ct2
(författare)
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Lindecrantz, K.Karolinska Institutet
(författare)
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KTHSkolan för kemi, bioteknologi och hälsa (CBH)
(creator_code:org_t)
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Ingår i:Sensors: MDPI AG18:91424-8220
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