Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity
Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. Firs...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
She, Jinhua [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Anmerkung: |
© Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of automation and computing - Berlin : Springer, 2004, 12(2014), 1 vom: 29. Dez., Seite 62-69 |
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| Übergeordnetes Werk: |
volume:12 ; year:2014 ; number:1 ; day:29 ; month:12 ; pages:62-69 |
| Links: |
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| DOI / URN: |
10.1007/s11633-014-0824-3 |
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SPR021289441 |
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| 520 | |a Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. | ||
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| 650 | 4 | |a Karvonen formula |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a exercise intensity |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a maximum heart rate |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a pedaling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a statistical analysis |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Nakamura, Hitoshi |4 aut | |
| 700 | 1 | |a Makino, Koji |4 aut | |
| 700 | 1 | |a Ohyama, Yasuhiro |4 aut | |
| 700 | 1 | |a Hashimoto, Hiroshi |4 aut | |
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10.1007/s11633-014-0824-3 doi (DE-627)SPR021289441 (SPR)s11633-014-0824-3-e DE-627 ger DE-627 rakwb eng She, Jinhua verfasserin aut Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. Borg CR10 scale (dpeaa)DE-He213 Karvonen formula (dpeaa)DE-He213 exercise intensity (dpeaa)DE-He213 maximum heart rate (dpeaa)DE-He213 pedaling (dpeaa)DE-He213 statistical analysis (dpeaa)DE-He213 Nakamura, Hitoshi aut Makino, Koji aut Ohyama, Yasuhiro aut Hashimoto, Hiroshi aut Enthalten in International journal of automation and computing Berlin : Springer, 2004 12(2014), 1 vom: 29. Dez., Seite 62-69 (DE-627)521466962 (DE-600)2260473-X 1751-8520 nnns volume:12 year:2014 number:1 day:29 month:12 pages:62-69 https://dx.doi.org/10.1007/s11633-014-0824-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2014 1 29 12 62-69 |
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10.1007/s11633-014-0824-3 doi (DE-627)SPR021289441 (SPR)s11633-014-0824-3-e DE-627 ger DE-627 rakwb eng She, Jinhua verfasserin aut Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. Borg CR10 scale (dpeaa)DE-He213 Karvonen formula (dpeaa)DE-He213 exercise intensity (dpeaa)DE-He213 maximum heart rate (dpeaa)DE-He213 pedaling (dpeaa)DE-He213 statistical analysis (dpeaa)DE-He213 Nakamura, Hitoshi aut Makino, Koji aut Ohyama, Yasuhiro aut Hashimoto, Hiroshi aut Enthalten in International journal of automation and computing Berlin : Springer, 2004 12(2014), 1 vom: 29. Dez., Seite 62-69 (DE-627)521466962 (DE-600)2260473-X 1751-8520 nnns volume:12 year:2014 number:1 day:29 month:12 pages:62-69 https://dx.doi.org/10.1007/s11633-014-0824-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2014 1 29 12 62-69 |
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10.1007/s11633-014-0824-3 doi (DE-627)SPR021289441 (SPR)s11633-014-0824-3-e DE-627 ger DE-627 rakwb eng She, Jinhua verfasserin aut Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. Borg CR10 scale (dpeaa)DE-He213 Karvonen formula (dpeaa)DE-He213 exercise intensity (dpeaa)DE-He213 maximum heart rate (dpeaa)DE-He213 pedaling (dpeaa)DE-He213 statistical analysis (dpeaa)DE-He213 Nakamura, Hitoshi aut Makino, Koji aut Ohyama, Yasuhiro aut Hashimoto, Hiroshi aut Enthalten in International journal of automation and computing Berlin : Springer, 2004 12(2014), 1 vom: 29. Dez., Seite 62-69 (DE-627)521466962 (DE-600)2260473-X 1751-8520 nnns volume:12 year:2014 number:1 day:29 month:12 pages:62-69 https://dx.doi.org/10.1007/s11633-014-0824-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2014 1 29 12 62-69 |
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10.1007/s11633-014-0824-3 doi (DE-627)SPR021289441 (SPR)s11633-014-0824-3-e DE-627 ger DE-627 rakwb eng She, Jinhua verfasserin aut Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. Borg CR10 scale (dpeaa)DE-He213 Karvonen formula (dpeaa)DE-He213 exercise intensity (dpeaa)DE-He213 maximum heart rate (dpeaa)DE-He213 pedaling (dpeaa)DE-He213 statistical analysis (dpeaa)DE-He213 Nakamura, Hitoshi aut Makino, Koji aut Ohyama, Yasuhiro aut Hashimoto, Hiroshi aut Enthalten in International journal of automation and computing Berlin : Springer, 2004 12(2014), 1 vom: 29. Dez., Seite 62-69 (DE-627)521466962 (DE-600)2260473-X 1751-8520 nnns volume:12 year:2014 number:1 day:29 month:12 pages:62-69 https://dx.doi.org/10.1007/s11633-014-0824-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2014 1 29 12 62-69 |
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10.1007/s11633-014-0824-3 doi (DE-627)SPR021289441 (SPR)s11633-014-0824-3-e DE-627 ger DE-627 rakwb eng She, Jinhua verfasserin aut Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. Borg CR10 scale (dpeaa)DE-He213 Karvonen formula (dpeaa)DE-He213 exercise intensity (dpeaa)DE-He213 maximum heart rate (dpeaa)DE-He213 pedaling (dpeaa)DE-He213 statistical analysis (dpeaa)DE-He213 Nakamura, Hitoshi aut Makino, Koji aut Ohyama, Yasuhiro aut Hashimoto, Hiroshi aut Enthalten in International journal of automation and computing Berlin : Springer, 2004 12(2014), 1 vom: 29. Dez., Seite 62-69 (DE-627)521466962 (DE-600)2260473-X 1751-8520 nnns volume:12 year:2014 number:1 day:29 month:12 pages:62-69 https://dx.doi.org/10.1007/s11633-014-0824-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2014 1 29 12 62-69 |
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Enthalten in International journal of automation and computing 12(2014), 1 vom: 29. Dez., Seite 62-69 volume:12 year:2014 number:1 day:29 month:12 pages:62-69 |
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International journal of automation and computing |
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She, Jinhua @@aut@@ Nakamura, Hitoshi @@aut@@ Makino, Koji @@aut@@ Ohyama, Yasuhiro @@aut@@ Hashimoto, Hiroshi @@aut@@ |
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She, Jinhua |
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She, Jinhua misc Borg CR10 scale misc Karvonen formula misc exercise intensity misc maximum heart rate misc pedaling misc statistical analysis Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity |
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Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity Borg CR10 scale (dpeaa)DE-He213 Karvonen formula (dpeaa)DE-He213 exercise intensity (dpeaa)DE-He213 maximum heart rate (dpeaa)DE-He213 pedaling (dpeaa)DE-He213 statistical analysis (dpeaa)DE-He213 |
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Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity |
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Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity |
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She, Jinhua Nakamura, Hitoshi Makino, Koji Ohyama, Yasuhiro Hashimoto, Hiroshi |
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selection of suitable maximum-heart-rate formulas for use with karvonen formula to calculate exercise intensity |
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Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity |
| abstract |
Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 |
| abstractGer |
Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 |
| abstract_unstemmed |
Abstract The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, HRmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating HRmax was the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days. A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing HRmax formulas, at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the HRmax formulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined. © Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015 |
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Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity |
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https://dx.doi.org/10.1007/s11633-014-0824-3 |
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Nakamura, Hitoshi Makino, Koji Ohyama, Yasuhiro Hashimoto, Hiroshi |
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10.1007/s11633-014-0824-3 |
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2024-07-03T21:37:21.219Z |
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| score |
7.4004107 |