{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T16:01:57Z","timestamp":1792512117349,"version":"4.5.0"},"reference-count":17,"publisher":"Wiley","license":[{"start":{"date-parts":[[2018,7,12]],"date-time":"2018-07-12T00:00:00Z","timestamp":1531353600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Healthcare Engineering"],"published-print":{"date-parts":[[2018,7,12]]},"abstract":"<jats:p>The adaptive algorithm satisfies the present needs on technology for diagnosis biosignals as lung sound signals (LSSs) and accurate techniques for the separation of heart sound signals (HSSs) and other background noise from LSS. This study investigates an improved adaptive noise cancellation (ANC) based on normalized last-mean-square (NLMS) algorithm. The parameters of ANC-NLMS algorithm are the filter length <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mfenced open=\"(\" close=\")\" separators=\"|\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:mfenced><\/mml:mrow><\/mml:math> parameter, which is determined in <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:msup><mml:mrow><mml:mn>2<\/mml:mn><\/mml:mrow><mml:mrow><mml:mi>n<\/mml:mi><\/mml:mrow><\/mml:msup><\/mml:mrow><\/mml:math> sequence of 2, 4, 8, 16, \u2026 , 2048, and the step size (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M3\"><mml:mrow><mml:msub><mml:mrow><mml:mi>\u03bc<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>n<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math>), which is automatically randomly identified using variable <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M4\"><mml:mrow><mml:msub><mml:mrow><mml:mi>\u03bc<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>n<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> (VSS) optimization. Initially, the algorithm is subjected experimentally to identify the optimal <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M5\"><mml:mrow><mml:msub><mml:mrow><mml:mi>\u03bc<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>n<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> range that works with 11 <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M6\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> values as a specific case. This case is used to study the improved performance of the proposed method based on the signal-to-noise ratio and mean square error. Moreover, the performance is evaluated four times for four <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M7\"><mml:mrow><mml:msub><mml:mrow><mml:mi>\u03bc<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>n<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> values, each of which with all <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M8\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> to obtain the output <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M9\"><mml:mrow><mml:msub><mml:mrow><mml:mtext>SNR<\/mml:mtext><\/mml:mrow><mml:mrow><mml:mtext>out<\/mml:mtext><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> matrix (4\u2009\u00d7\u200911). The improvement level is estimated and compared with the <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M10\"><mml:mrow><mml:msub><mml:mrow><mml:mtext>SNR<\/mml:mtext><\/mml:mrow><mml:mrow><mml:mtext>in<\/mml:mtext><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> prior to the application of the proposed algorithm and after <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M11\"><mml:mrow><mml:msub><mml:mrow><mml:mtext>SNR<\/mml:mtext><\/mml:mrow><mml:mrow><mml:mtext>outs<\/mml:mtext><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math>. The proposed method achieves high-performance ANC-NLMS algorithm by optimizing VSS when it is close to zero at determining <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M12\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math>, at which the algorithm shows the capability to separate HSS from LSS. Furthermore, the <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M13\"><mml:mrow><mml:msub><mml:mrow><mml:mtext>SNR<\/mml:mtext><\/mml:mrow><mml:mrow><mml:mtext>out<\/mml:mtext><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> of normal LSS starts to improve at <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M14\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> of 64 and <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M15\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> limit of 1024. The <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M16\"><mml:mrow><mml:msub><mml:mrow><mml:mtext>SNR<\/mml:mtext><\/mml:mrow><mml:mrow><mml:mtext>out<\/mml:mtext><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> of abnormal LSS starts from a <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M17\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> value of 512 to more than 2048 for all determined <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M18\"><mml:mrow><mml:msub><mml:mrow><mml:mi>\u03bc<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>n<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math>. Results revealed that the <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M19\"><mml:mrow><mml:msub><mml:mrow><mml:mtext>SNR<\/mml:mtext><\/mml:mrow><mml:mrow><mml:mtext>out<\/mml:mtext><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> of the abnormal LSS is small (negative value), whereas that in the normal LSS is large (reaches a positive value). Finally, the designed ANC-NLMS algorithm can separate HSS from LSS. This algorithm can also achieve a good performance by optimizing VSS at the determined 11 <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M20\"><mml:mrow><mml:msub><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><mml:mrow><mml:mi>j<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> values. Additionally, the steps of the proposed method and the obtained <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M21\"><mml:mrow><mml:msub><mml:mrow><mml:mtext>SNR<\/mml:mtext><\/mml:mrow><mml:mrow><mml:mtext>out<\/mml:mtext><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math> may be used to classify LSS by using a computer.<\/jats:p>","DOI":"10.1155\/2018\/9732762","type":"journal-article","created":{"date-parts":[[2018,7,12]],"date-time":"2018-07-12T20:16:44Z","timestamp":1531426604000},"page":"1-10","source":"Crossref","is-referenced-by-count":16,"title":["Performance of Adaptive Noise Cancellation with Normalized Last-Mean-Square Based on the Signal-to-Noise Ratio of Lung and Heart Sound Separation"],"prefix":"10.1155","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2532-7443","authenticated-orcid":true,"given":"Noman Q.","family":"Al-Naggar","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Faculty of Engineering, University of Science and Technology, Sana\u2019a, Yemen"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed H.","family":"Al-Udyni","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Faculty of Engineering, University of Science and Technology, Sana\u2019a, Yemen"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.4137\/ccrpm.s530"},{"key":"2","first-page":"4373","volume":"9","year":"2010","journal-title":"International Journal of Engineering Science and Technology"},{"issue":"2","key":"3","first-page":"559","volume":"65","year":"2014","journal-title":"Journal of Theoretical and Applied Information Technology"},{"issue":"4","key":"4","first-page":"2601","volume":"4","year":"2015","journal-title":"International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.4236\/jbise.2013.69106"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jestch.2017.02.005"},{"key":"8","first-page":"106","volume":"2","year":"2013","journal-title":"International Journal on Advanced Computer Theory and Engineering"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2013.10.009"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1186\/s12938-017-0315-1"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1186\/1743-0003-4-29"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.5829\/idosi.mejsr.2015.23.08.22417"},{"key":"13","year":"2013"},{"key":"15","year":"2008"},{"key":"16","volume-title":"Convergence evaluation of a random step-size NLMS adaptive algorithm in system identification and channel equalization","year":"2011"},{"key":"17","year":"2004"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.4172\/2155-9538.1000195"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.protcy.2016.08.127"}],"container-title":["Journal of Healthcare Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/jhe\/2018\/9732762.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jhe\/2018\/9732762.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jhe\/2018\/9732762.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,7,12]],"date-time":"2018-07-12T20:16:46Z","timestamp":1531426606000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/jhe\/2018\/9732762\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,12]]},"references-count":17,"alternative-id":["9732762","9732762"],"URL":"https:\/\/doi.org\/10.1155\/2018\/9732762","relation":{},"ISSN":["2040-2295","2040-2309"],"issn-type":[{"value":"2040-2295","type":"print"},{"value":"2040-2309","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,12]]}}}