Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography
Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the ac...
Ausführliche Beschreibung
Autor*in: |
Kim, Young Jin [verfasserIn] Cho, Yang Sun [verfasserIn] Park, Ga Young [verfasserIn] Choi, Ahnryul [verfasserIn] Youn, Su Hyun [verfasserIn] Sim, Taeyong [verfasserIn] Oh, Seung Eel [verfasserIn] Yang, Heegoo [verfasserIn] Park, Hyunjoon [verfasserIn] Lee, Dongjune [verfasserIn] Lee, Dae-weon [verfasserIn] Mun, Joung Hwan [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2013 |
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Übergeordnetes Werk: |
Enthalten in: International journal of precision engineering and manufacturing - Sŏul : KSPE, 2009, 14(2013), 7 vom: Juli, Seite 1193-1199 |
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Übergeordnetes Werk: |
volume:14 ; year:2013 ; number:7 ; month:07 ; pages:1193-1199 |
Links: |
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DOI / URN: |
10.1007/s12541-013-0162-3 |
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Katalog-ID: |
SPR026092581 |
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245 | 1 | 0 | |a Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography |
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520 | |a Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). | ||
650 | 4 | |a Depth of muscle relaxation |7 (dpeaa)DE-He213 | |
650 | 4 | |a Electromyography |7 (dpeaa)DE-He213 | |
650 | 4 | |a Facial nerve |7 (dpeaa)DE-He213 | |
650 | 4 | |a Muscle relaxation |7 (dpeaa)DE-He213 | |
650 | 4 | |a Principal component analysis |7 (dpeaa)DE-He213 | |
700 | 1 | |a Cho, Yang Sun |e verfasserin |4 aut | |
700 | 1 | |a Park, Ga Young |e verfasserin |4 aut | |
700 | 1 | |a Choi, Ahnryul |e verfasserin |4 aut | |
700 | 1 | |a Youn, Su Hyun |e verfasserin |4 aut | |
700 | 1 | |a Sim, Taeyong |e verfasserin |4 aut | |
700 | 1 | |a Oh, Seung Eel |e verfasserin |4 aut | |
700 | 1 | |a Yang, Heegoo |e verfasserin |4 aut | |
700 | 1 | |a Park, Hyunjoon |e verfasserin |4 aut | |
700 | 1 | |a Lee, Dongjune |e verfasserin |4 aut | |
700 | 1 | |a Lee, Dae-weon |e verfasserin |4 aut | |
700 | 1 | |a Mun, Joung Hwan |e verfasserin |4 aut | |
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2013 |
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10.1007/s12541-013-0162-3 doi (DE-627)SPR026092581 (SPR)s12541-013-0162-3-e DE-627 ger DE-627 rakwb eng 600 ASE Kim, Young Jin verfasserin aut Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). Depth of muscle relaxation (dpeaa)DE-He213 Electromyography (dpeaa)DE-He213 Facial nerve (dpeaa)DE-He213 Muscle relaxation (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Cho, Yang Sun verfasserin aut Park, Ga Young verfasserin aut Choi, Ahnryul verfasserin aut Youn, Su Hyun verfasserin aut Sim, Taeyong verfasserin aut Oh, Seung Eel verfasserin aut Yang, Heegoo verfasserin aut Park, Hyunjoon verfasserin aut Lee, Dongjune verfasserin aut Lee, Dae-weon verfasserin aut Mun, Joung Hwan verfasserin aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 14(2013), 7 vom: Juli, Seite 1193-1199 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:14 year:2013 number:7 month:07 pages:1193-1199 https://dx.doi.org/10.1007/s12541-013-0162-3 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 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_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_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 14 2013 7 07 1193-1199 |
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10.1007/s12541-013-0162-3 doi (DE-627)SPR026092581 (SPR)s12541-013-0162-3-e DE-627 ger DE-627 rakwb eng 600 ASE Kim, Young Jin verfasserin aut Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). Depth of muscle relaxation (dpeaa)DE-He213 Electromyography (dpeaa)DE-He213 Facial nerve (dpeaa)DE-He213 Muscle relaxation (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Cho, Yang Sun verfasserin aut Park, Ga Young verfasserin aut Choi, Ahnryul verfasserin aut Youn, Su Hyun verfasserin aut Sim, Taeyong verfasserin aut Oh, Seung Eel verfasserin aut Yang, Heegoo verfasserin aut Park, Hyunjoon verfasserin aut Lee, Dongjune verfasserin aut Lee, Dae-weon verfasserin aut Mun, Joung Hwan verfasserin aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 14(2013), 7 vom: Juli, Seite 1193-1199 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:14 year:2013 number:7 month:07 pages:1193-1199 https://dx.doi.org/10.1007/s12541-013-0162-3 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 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_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_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 14 2013 7 07 1193-1199 |
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10.1007/s12541-013-0162-3 doi (DE-627)SPR026092581 (SPR)s12541-013-0162-3-e DE-627 ger DE-627 rakwb eng 600 ASE Kim, Young Jin verfasserin aut Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). Depth of muscle relaxation (dpeaa)DE-He213 Electromyography (dpeaa)DE-He213 Facial nerve (dpeaa)DE-He213 Muscle relaxation (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Cho, Yang Sun verfasserin aut Park, Ga Young verfasserin aut Choi, Ahnryul verfasserin aut Youn, Su Hyun verfasserin aut Sim, Taeyong verfasserin aut Oh, Seung Eel verfasserin aut Yang, Heegoo verfasserin aut Park, Hyunjoon verfasserin aut Lee, Dongjune verfasserin aut Lee, Dae-weon verfasserin aut Mun, Joung Hwan verfasserin aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 14(2013), 7 vom: Juli, Seite 1193-1199 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:14 year:2013 number:7 month:07 pages:1193-1199 https://dx.doi.org/10.1007/s12541-013-0162-3 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 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_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_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 14 2013 7 07 1193-1199 |
allfieldsGer |
10.1007/s12541-013-0162-3 doi (DE-627)SPR026092581 (SPR)s12541-013-0162-3-e DE-627 ger DE-627 rakwb eng 600 ASE Kim, Young Jin verfasserin aut Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). Depth of muscle relaxation (dpeaa)DE-He213 Electromyography (dpeaa)DE-He213 Facial nerve (dpeaa)DE-He213 Muscle relaxation (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Cho, Yang Sun verfasserin aut Park, Ga Young verfasserin aut Choi, Ahnryul verfasserin aut Youn, Su Hyun verfasserin aut Sim, Taeyong verfasserin aut Oh, Seung Eel verfasserin aut Yang, Heegoo verfasserin aut Park, Hyunjoon verfasserin aut Lee, Dongjune verfasserin aut Lee, Dae-weon verfasserin aut Mun, Joung Hwan verfasserin aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 14(2013), 7 vom: Juli, Seite 1193-1199 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:14 year:2013 number:7 month:07 pages:1193-1199 https://dx.doi.org/10.1007/s12541-013-0162-3 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 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_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_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 14 2013 7 07 1193-1199 |
allfieldsSound |
10.1007/s12541-013-0162-3 doi (DE-627)SPR026092581 (SPR)s12541-013-0162-3-e DE-627 ger DE-627 rakwb eng 600 ASE Kim, Young Jin verfasserin aut Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). Depth of muscle relaxation (dpeaa)DE-He213 Electromyography (dpeaa)DE-He213 Facial nerve (dpeaa)DE-He213 Muscle relaxation (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 Cho, Yang Sun verfasserin aut Park, Ga Young verfasserin aut Choi, Ahnryul verfasserin aut Youn, Su Hyun verfasserin aut Sim, Taeyong verfasserin aut Oh, Seung Eel verfasserin aut Yang, Heegoo verfasserin aut Park, Hyunjoon verfasserin aut Lee, Dongjune verfasserin aut Lee, Dae-weon verfasserin aut Mun, Joung Hwan verfasserin aut Enthalten in International journal of precision engineering and manufacturing Sŏul : KSPE, 2009 14(2013), 7 vom: Juli, Seite 1193-1199 (DE-627)609403109 (DE-600)2515436-9 2005-4602 nnns volume:14 year:2013 number:7 month:07 pages:1193-1199 https://dx.doi.org/10.1007/s12541-013-0162-3 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 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_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_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 14 2013 7 07 1193-1199 |
language |
English |
source |
Enthalten in International journal of precision engineering and manufacturing 14(2013), 7 vom: Juli, Seite 1193-1199 volume:14 year:2013 number:7 month:07 pages:1193-1199 |
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Enthalten in International journal of precision engineering and manufacturing 14(2013), 7 vom: Juli, Seite 1193-1199 volume:14 year:2013 number:7 month:07 pages:1193-1199 |
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Article |
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topic_facet |
Depth of muscle relaxation Electromyography Facial nerve Muscle relaxation Principal component analysis |
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600 |
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false |
container_title |
International journal of precision engineering and manufacturing |
authorswithroles_txt_mv |
Kim, Young Jin @@aut@@ Cho, Yang Sun @@aut@@ Park, Ga Young @@aut@@ Choi, Ahnryul @@aut@@ Youn, Su Hyun @@aut@@ Sim, Taeyong @@aut@@ Oh, Seung Eel @@aut@@ Yang, Heegoo @@aut@@ Park, Hyunjoon @@aut@@ Lee, Dongjune @@aut@@ Lee, Dae-weon @@aut@@ Mun, Joung Hwan @@aut@@ |
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2013-07-01T00:00:00Z |
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609403109 |
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3600 |
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SPR026092581 |
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As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. 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Kim, Young Jin |
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Kim, Young Jin ddc 600 misc Depth of muscle relaxation misc Electromyography misc Facial nerve misc Muscle relaxation misc Principal component analysis Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography |
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600 ASE Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography Depth of muscle relaxation (dpeaa)DE-He213 Electromyography (dpeaa)DE-He213 Facial nerve (dpeaa)DE-He213 Muscle relaxation (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 |
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ddc 600 misc Depth of muscle relaxation misc Electromyography misc Facial nerve misc Muscle relaxation misc Principal component analysis |
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ddc 600 misc Depth of muscle relaxation misc Electromyography misc Facial nerve misc Muscle relaxation misc Principal component analysis |
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Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography |
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Kim, Young Jin |
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International journal of precision engineering and manufacturing |
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Kim, Young Jin Cho, Yang Sun Park, Ga Young Choi, Ahnryul Youn, Su Hyun Sim, Taeyong Oh, Seung Eel Yang, Heegoo Park, Hyunjoon Lee, Dongjune Lee, Dae-weon Mun, Joung Hwan |
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Kim, Young Jin |
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10.1007/s12541-013-0162-3 |
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development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography |
title_auth |
Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography |
abstract |
Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). |
abstractGer |
Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). |
abstract_unstemmed |
Abstract Permanent facial nerve damage is one of the most critical complications that can occur during otologic and neurosurgical procedures. As a result, facial nerve monitoring equipment is now used in most of otologic surgeries. The monitoring devices used for this purpose usually evaluate the activity of facial muscle in response to stimulation to the facial nerve. For these purposes, electromyography and the train-of-four (TOF) method is commonly used clinically, but these approaches have an important limitation: this qualitative method only depends on visual information of finger movement. Thus, in this study, a new factor that can be used to quantitatively the stage of muscle relaxation at the facial nerve was developed based on the degree of muscle relaxation and electro-stimulation. Ketamine intravenous anesthesia and isoflurane inhalation anesthesia was given to 13 rabbits. A 28 G unipolar needle-electrode was inserted at an exposed facial nerve, and stimulated (0.1 mA–5.0 mA) with an electrical stimulator. Also, the degree of muscle relaxation based electromyographic signal acquisition was performed while increasing the dose of neuromuscular blockades. After data noise reduction and normalization, the collected EMG signals were divided into 33 variables, and a new evaluation factor was developed using statistical methods based on multiple linear regression models and principal component analysis. A new evaluation factor was identified that can be used to quantitatively estimate each phase in muscle relation. The evaluating factors that were calculated in accordance with the electrical simulation resulted in improved results (r = 0.96) when compared to the existing assessment methods. (T1 ratio r = 0.72; T4/T1 ration r = 0.52). |
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container_issue |
7 |
title_short |
Development of quantitative evaluation factors for determining the level of facial muscle relaxation in rabbits using facial muscle electromyography |
url |
https://dx.doi.org/10.1007/s12541-013-0162-3 |
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Cho, Yang Sun Park, Ga Young Choi, Ahnryul Youn, Su Hyun Sim, Taeyong Oh, Seung Eel Yang, Heegoo Park, Hyunjoon Lee, Dongjune Lee, Dae-weon Mun, Joung Hwan |
author2Str |
Cho, Yang Sun Park, Ga Young Choi, Ahnryul Youn, Su Hyun Sim, Taeyong Oh, Seung Eel Yang, Heegoo Park, Hyunjoon Lee, Dongjune Lee, Dae-weon Mun, Joung Hwan |
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|
score |
7.3982677 |