A diagnostic model of nerve root compression localization in lower lumbar disc herniation based on random forest algorithm and surface electromyography

This study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using random forest (RF) algorithm for localization diagnosis of compressed nerve root in LD...

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Published in:	Frontiers in human neuroscience Vol. 17; p. 1176001
Main Authors:	Wang, Hujun, Wang, Yingpeng, Li, Yingqi, Wang, Congxiao, Qie, Shuyan
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Research Foundation 04.07.2023 Frontiers Media S.A
Subjects:	Algorithms Cerebral palsy Compression Contraindications Data processing Diagnosis diagnosis model Disease Electromyography Gait Intervertebral discs Localization lumbar disc herniation Machine learning Magnetic resonance imaging Muscle contraction nerve root compression Neuroscience Patients random forest Rehabilitation Software surface electromyography Surgery Beijing China United States > US China random forest diagnosis model surface electromyography nerve root compression lumbar disc herniation
ISSN:	1662-5161, 1662-5161
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Abstract	This study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using random forest (RF) algorithm for localization diagnosis of compressed nerve root in LDH patients. Fifty-eight patients with LDH and thirty healthy subjects were recruited. The SEMG of tibialis anterior (TA) and lateral gastrocnemius (LG) were collected bilaterally during walking. The peak root mean square (RMS-peak), RMS-peak time, mean power frequency (MPF), and median frequency (MF) were analyzed. A diagnostic model based on SEMG parameters using RF algorithm was established to locate compressed nerve root, and repeated reservation experiments were conducted for verification. The study evaluated the diagnostic efficiency of the model using accuracy, precision, recall rate, F1-score, Kappa value, and area under the receiver operating characteristic (ROC) curve. The results showed that delayed activation of TA and decreased activation of LG were observed in the L5 group, while decreased activation of LG and earlier activation of LG were observed in the S1 group. The RF model based on eight SEMG parameters showed an average accuracy of 84%, with an area under the ROC curve of 0.93. The RMS peak time of TA was identified as the most important SEMG parameter. These findings suggest that the RF model can assist in the localization diagnosis of compressed nerve roots in LDH patients, and the SEMG parameters can provide further references for optimizing the diagnosis model in the future.
AbstractList	This study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using random forest (RF) algorithm for localization diagnosis of compressed nerve root in LDH patients.ObjectiveThis study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using random forest (RF) algorithm for localization diagnosis of compressed nerve root in LDH patients.Fifty-eight patients with LDH and thirty healthy subjects were recruited. The SEMG of tibialis anterior (TA) and lateral gastrocnemius (LG) were collected bilaterally during walking. The peak root mean square (RMS-peak), RMS-peak time, mean power frequency (MPF), and median frequency (MF) were analyzed. A diagnostic model based on SEMG parameters using RF algorithm was established to locate compressed nerve root, and repeated reservation experiments were conducted for verification. The study evaluated the diagnostic efficiency of the model using accuracy, precision, recall rate, F1-score, Kappa value, and area under the receiver operating characteristic (ROC) curve.MethodsFifty-eight patients with LDH and thirty healthy subjects were recruited. The SEMG of tibialis anterior (TA) and lateral gastrocnemius (LG) were collected bilaterally during walking. The peak root mean square (RMS-peak), RMS-peak time, mean power frequency (MPF), and median frequency (MF) were analyzed. A diagnostic model based on SEMG parameters using RF algorithm was established to locate compressed nerve root, and repeated reservation experiments were conducted for verification. The study evaluated the diagnostic efficiency of the model using accuracy, precision, recall rate, F1-score, Kappa value, and area under the receiver operating characteristic (ROC) curve.The results showed that delayed activation of TA and decreased activation of LG were observed in the L5 group, while decreased activation of LG and earlier activation of LG were observed in the S1 group. The RF model based on eight SEMG parameters showed an average accuracy of 84%, with an area under the ROC curve of 0.93. The RMS peak time of TA was identified as the most important SEMG parameter.ResultsThe results showed that delayed activation of TA and decreased activation of LG were observed in the L5 group, while decreased activation of LG and earlier activation of LG were observed in the S1 group. The RF model based on eight SEMG parameters showed an average accuracy of 84%, with an area under the ROC curve of 0.93. The RMS peak time of TA was identified as the most important SEMG parameter.These findings suggest that the RF model can assist in the localization diagnosis of compressed nerve roots in LDH patients, and the SEMG parameters can provide further references for optimizing the diagnosis model in the future.ConclusionThese findings suggest that the RF model can assist in the localization diagnosis of compressed nerve roots in LDH patients, and the SEMG parameters can provide further references for optimizing the diagnosis model in the future. This study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using random forest (RF) algorithm for localization diagnosis of compressed nerve root in LDH patients. Fifty-eight patients with LDH and thirty healthy subjects were recruited. The SEMG of tibialis anterior (TA) and lateral gastrocnemius (LG) were collected bilaterally during walking. The peak root mean square (RMS-peak), RMS-peak time, mean power frequency (MPF), and median frequency (MF) were analyzed. A diagnostic model based on SEMG parameters using RF algorithm was established to locate compressed nerve root, and repeated reservation experiments were conducted for verification. The study evaluated the diagnostic efficiency of the model using accuracy, precision, recall rate, F1-score, Kappa value, and area under the receiver operating characteristic (ROC) curve. The results showed that delayed activation of TA and decreased activation of LG were observed in the L5 group, while decreased activation of LG and earlier activation of LG were observed in the S1 group. The RF model based on eight SEMG parameters showed an average accuracy of 84%, with an area under the ROC curve of 0.93. The RMS peak time of TA was identified as the most important SEMG parameter. These findings suggest that the RF model can assist in the localization diagnosis of compressed nerve roots in LDH patients, and the SEMG parameters can provide further references for optimizing the diagnosis model in the future. Objective: This study aimed to investigate the muscle activation of patients with Lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using Random Forest (RF) algorithm for localization diagnosis of compressed nerve root in LDH patients.Methods: Fifty-eight patients with LDH and thirty healthy subjects were recruited. The SEMG of Tibialis Anterior (TA) and lateral gastrocnemius (LG) were collected bilaterally during walking. The peak root mean square (RMS-peak), RMS-peak time, mean power frequency (MPF), and mean frequency (MF) were analyzed. A diagnostic model based on SEMG parameters using RF algorithm was established to locate compressed nerve root, and repeated reservation experiments were conducted for verification. The study evaluated the diagnostic efficiency of the model using accuracy, precision, recall rate, F1-score, Kappa value, and area under the ROC curve.The results showed that delayed activation of TA and decreased activation ofLG were observed in the L5 group, while decreased activation of LG and earlier activation of LG were observed in the S1 group. The RF model based on eight SEMG parameters showed an average accuracy of 84%, with an area under the ROC curve of 0.93. The RMS peak time of TA was identified as the most important SEMG parameter.: These findings suggest that the RF model can assist in the localization diagnosis of compressed nerve roots in LDH patients, and the SEMG parameters can provide further references for optimizing the diagnosis model in the future. ObjectiveThis study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and establish a diagnostic model based on SEMG parameters using random forest (RF) algorithm for localization diagnosis of compressed nerve root in LDH patients.MethodsFifty-eight patients with LDH and thirty healthy subjects were recruited. The SEMG of tibialis anterior (TA) and lateral gastrocnemius (LG) were collected bilaterally during walking. The peak root mean square (RMS-peak), RMS-peak time, mean power frequency (MPF), and median frequency (MF) were analyzed. A diagnostic model based on SEMG parameters using RF algorithm was established to locate compressed nerve root, and repeated reservation experiments were conducted for verification. The study evaluated the diagnostic efficiency of the model using accuracy, precision, recall rate, F1-score, Kappa value, and area under the receiver operating characteristic (ROC) curve.ResultsThe results showed that delayed activation of TA and decreased activation of LG were observed in the L5 group, while decreased activation of LG and earlier activation of LG were observed in the S1 group. The RF model based on eight SEMG parameters showed an average accuracy of 84%, with an area under the ROC curve of 0.93. The RMS peak time of TA was identified as the most important SEMG parameter.ConclusionThese findings suggest that the RF model can assist in the localization diagnosis of compressed nerve roots in LDH patients, and the SEMG parameters can provide further references for optimizing the diagnosis model in the future.
Author	Wang, Yingpeng Wang, Congxiao Li, Yingqi Qie, Shuyan Wang, Hujun
AuthorAffiliation	Department of Rehabilitation, Beijing Rehabilitation Hospital, Capital Medical University , Beijing , China
AuthorAffiliation_xml	– name: Department of Rehabilitation, Beijing Rehabilitation Hospital, Capital Medical University , Beijing , China
Author_xml	– sequence: 1 givenname: Hujun surname: Wang fullname: Wang, Hujun – sequence: 2 givenname: Yingpeng surname: Wang fullname: Wang, Yingpeng – sequence: 3 givenname: Yingqi surname: Li fullname: Li, Yingqi – sequence: 4 givenname: Congxiao surname: Wang fullname: Wang, Congxiao – sequence: 5 givenname: Shuyan surname: Qie fullname: Qie, Shuyan
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/37469999$$D View this record in MEDLINE/PubMed
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Cites_doi	10.1111/os.12362 10.1007/s11999-014-3674-y 10.1016/0022-510x(89)90237-2 10.1016/j.spinee.2013.02.007 10.1023/A:1010933404324 10.1016/j.jelekin.2013.06.006 10.1038/s41598-020-77150-7 10.21037/jss.2016.01.05 10.1097/BRS.0b013e3181b1c99f 10.3390/s140508235 10.1016/j.pmr.2012.08.011 10.3174/ajnr.A4498 10.1016/j.gaitpost.2017.01.010 10.1109/TBME.2006.873680 10.1016/j.jelekin.2008.09.002 10.1186/s12938-018-0443-2 10.1016/j.clineuro.2013.11.018 10.1007/s00586-015-4375-2 10.3233/BMR-181308 10.1097/00005373-196103000-00008 10.3174/ajnr.A4173 10.1016/j.jelekin.2007.09.006 10.2340/16501977-1034 10.1097/AJP.0000000000000179 10.1097/MD.0000000000017865 10.1016/j.clinbiomech.2008.08.006 10.1093/fampra/cmv097 10.19650/j.cnki.cjsi.J1905757 10.1007/s00586-011-2109-7
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Keywords	random forest diagnosis model surface electromyography nerve root compression lumbar disc herniation
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 These authors have contributed equally to this work Edited by: Redha Taiar, Université de Reims Champagne-Ardenne, France Reviewed by: Sherwan Hamawandi, Hawler Medical University, Iraq; Anastasia Keller, University of California, San Francisco, United States; Yutong Gu, Fudan University, China
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References	Hallal (B13) 2013; 23 Ramos (B24) 2016; 25 Brinjikji (B5); 36 Furlan (B11) 2009; 34 Rønager (B25) 1989; 94 Breiman (B4) 2001; 45 Wang (B30) 2014; 117 Dedering (B8) 2012; 21 Merletti (B20) 2008; 18 Supuk (B27) 2014; 14 Al-Khawaja (B2) 2016; 2 Gurdjian (B12) 1961; 1 Brinjikji (B6); 36 Du (B10) 2018; 17 Li (B16) 2018; 10 Molinari (B21) 2006; 53 Barr (B3) 2013; 24 Merletti (B19) 2009; 24 Wang (B29) 2020; 10 Djordjevic (B9) 2015; 31 Lee (B15) 2012; 44 de Schepper (B7) 2016; 33 Li (B17) 2015; 473 Qie (B23) 2020; 33 Lo (B18) 2017; 53 Wakeling (B28) 2009; 19 He (B14) 2020; 35 Shi (B26) 2020; 7 Al Nezari (B1) 2013; 13 Park (B22) 2019; 98
References_xml	– volume: 10 start-page: 47 year: 2018 ident: B16 article-title: Diagnosis of compressed nerve root in lumbar disc herniation patients by surface electromyography. publication-title: Orthop. Surg. doi: 10.1111/os.12362 – volume: 473 start-page: 1896 year: 2015 ident: B17 article-title: How should we grade lumbar disc herniation and nerve root compression? A systematic review. publication-title: Clin. Orthop. Relat. Res. doi: 10.1007/s11999-014-3674-y – volume: 94 start-page: 283 year: 1989 ident: B25 article-title: Power spectrum analysis of the EMG pattern in normal and diseased muscles. publication-title: J. Neurol. Sci. doi: 10.1016/0022-510x(89)90237-2 – volume: 13 start-page: 657 year: 2013 ident: B1 article-title: Neurological examination of the peripheral nervous system to diagnose lumbar spinal disc herniation with suspected radiculopathy: a systematic review and meta-analysis. publication-title: Spine J. doi: 10.1016/j.spinee.2013.02.007 – volume: 45 start-page: 5 year: 2001 ident: B4 article-title: Random forests. publication-title: Mach. Learn. doi: 10.1023/A:1010933404324 – volume: 23 start-page: 1145 year: 2013 ident: B13 article-title: Electromyographic patterns of lower limb muscles during apprehensive gait in younger and older female adults. publication-title: J. Electromyogr. Kinesiol. doi: 10.1016/j.jelekin.2013.06.006 – volume: 10 year: 2020 ident: B29 article-title: Dysfunctional muscle activities and co-contraction in the lower-limb of lumbar disc herniation patients during walking. publication-title: Sci. Rep. doi: 10.1038/s41598-020-77150-7 – volume: 2 start-page: 21 year: 2016 ident: B2 article-title: Surgical treatment of far lateral lumbar disc herniation: a safe and simple approach. publication-title: J. Spine Surg. doi: 10.21037/jss.2016.01.05 – volume: 34 start-page: 1929 year: 2009 ident: B11 article-title: 2009 updated method guidelines for systematic reviews in the Cochrane back review group. publication-title: Spine doi: 10.1097/BRS.0b013e3181b1c99f – volume: 14 start-page: 8235 year: 2014 ident: B27 article-title: Design, development and testing of a low-cost sEMG system and its use in recording muscle activity in human gait. publication-title: Sensors. doi: 10.3390/s140508235 – volume: 24 start-page: 79 year: 2013 ident: B3 article-title: Electrodiagnosis of lumbar radiculopathy. publication-title: Phys. Med. Rehabil. Clin. N. Am. doi: 10.1016/j.pmr.2012.08.011 – volume: 36 start-page: 2394 ident: B5 article-title: MRI findings of disc degeneration are more prevalent in adults with low back pain than in asymptomatic controls: a systematic review and meta-analysis. publication-title: Am. J. Neuroradiol. doi: 10.3174/ajnr.A4498 – volume: 53 start-page: 110 year: 2017 ident: B18 article-title: Functional implications of muscle co-contraction during gait in advanced age. publication-title: Gait Posture doi: 10.1016/j.gaitpost.2017.01.010 – volume: 53 start-page: 1309 year: 2006 ident: B21 article-title: Electrical manifestations of muscle fatigue during concentric and eccentric isokinetic knee flexion-extension movements. publication-title: IEEE Trans. Biomed. Eng. doi: 10.1109/TBME.2006.873680 – volume: 18 start-page: 879 year: 2008 ident: B20 article-title: Analysis of motor units with high-density surface electromyography. publication-title: J. Electromyogr. Kinesiol. doi: 10.1016/j.jelekin.2008.09.002 – volume: 17 year: 2018 ident: B10 article-title: Co-contraction characteristics of lumbar muscles in patients with lumbar disc herniation during different types of movement. publication-title: Biomed. Eng. Online doi: 10.1186/s12938-018-0443-2 – volume: 117 start-page: 33 year: 2014 ident: B30 article-title: Foot drop resulting from degenerative lumbar spinal diseases: clinical characteristics and prognosis. publication-title: Clin. Neurol. Neurosurg. doi: 10.1016/j.clineuro.2013.11.018 – volume: 25 start-page: 1435 year: 2016 ident: B24 article-title: Are lumbar multifidus fatigue and transversus abdominis activation similar in patients with lumbar disc herniation and healthy controls? A case control study. publication-title: Eur. Spine J. doi: 10.1007/s00586-015-4375-2 – volume: 33 start-page: 589 year: 2020 ident: B23 article-title: Electromyography activities in patients with lower lumbar disc herniation. publication-title: J. Back Musculoskelet. Rehabil. doi: 10.3233/BMR-181308 – volume: 1 start-page: 158 year: 1961 ident: B12 article-title: Herniated lumbar intervertebral discs – an analysis of 1176 operated cases. publication-title: J. Trauma doi: 10.1097/00005373-196103000-00008 – volume: 35 start-page: 585 year: 2020 ident: B14 article-title: Research on gait evaluation based on random forest algorithm. publication-title: Chin. J. Rehabil. Med. – volume: 36 start-page: 811 ident: B6 article-title: Systematic literature review of imaging features of spinal degeneration in asymptomatic populations. publication-title: Am. J. Neuroradiol. doi: 10.3174/ajnr.A4173 – volume: 19 start-page: 199 year: 2009 ident: B28 article-title: Patterns of motor recruitment can be determined using surface EMG. publication-title: J. Electromyogr. Kinesiol. doi: 10.1016/j.jelekin.2007.09.006 – volume: 44 start-page: 845 year: 2012 ident: B15 article-title: Physical examination, magnetic resonance image, and electrodiagnostic study in patients with lumbosacral disc herniation or spinal stenosis. publication-title: J. Rehabil. Med. doi: 10.2340/16501977-1034 – volume: 31 start-page: 893 year: 2015 ident: B9 article-title: Relationship between electromyographic signal amplitude and thickness change of the trunk muscles in patients with and without low back pain. publication-title: Clin. J. Pain doi: 10.1097/AJP.0000000000000179 – volume: 98 year: 2019 ident: B22 article-title: Compressive peroneal neuropathy by an intraneural ganglion cyst combined with L5 radiculopathy: a case report. publication-title: Medicine doi: 10.1097/MD.0000000000017865 – volume: 24 start-page: 122 year: 2009 ident: B19 article-title: Technology and instrumentation for detection and conditioning of the surface electromyographic signal: state of the art. publication-title: Clin. Biomech. doi: 10.1016/j.clinbiomech.2008.08.006 – volume: 33 start-page: 51 year: 2016 ident: B7 article-title: Prevalence of spinal pathology in patients presenting for lumbar MRI as referred from general practice. publication-title: Fam. Pract. doi: 10.1093/fampra/cmv097 – volume: 7 year: 2020 ident: B26 article-title: Fast classification of lower limb movements based on LMS-random forest for electromyographic signals publication-title: J. Instrumentation doi: 10.19650/j.cnki.cjsi.J1905757 – volume: 21 start-page: 646 year: 2012 ident: B8 article-title: Lumbar muscle fatigue and subjective health measurements in patients with lumbar disc herniation 2 years after surgery. publication-title: Eur. Spine J. doi: 10.1007/s00586-011-2109-7
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Snippet	This study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG) and... Objective: This study aimed to investigate the muscle activation of patients with Lumbar disc herniation (LDH) during walking by surface electromyography... ObjectiveThis study aimed to investigate the muscle activation of patients with lumbar disc herniation (LDH) during walking by surface electromyography (SEMG)...
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StartPage	1176001
SubjectTerms	Algorithms Cerebral palsy Compression Contraindications Data processing Diagnosis diagnosis model Disease Electromyography Gait Intervertebral discs Localization lumbar disc herniation Machine learning Magnetic resonance imaging Muscle contraction nerve root compression Neuroscience Patients random forest Rehabilitation Software surface electromyography Surgery
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Title	A diagnostic model of nerve root compression localization in lower lumbar disc herniation based on random forest algorithm and surface electromyography
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Volume	17
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