{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T13:10:54Z","timestamp":1779887454714,"version":"3.53.1"},"reference-count":30,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T00:00:00Z","timestamp":1678838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>In the clinical context, the assessment of pain in patients with inadequate communication skills is standardly performed externally by trained medical staff. Automated pain recognition (APR) could make a significant contribution here. Hereby, pain responses are captured using mainly video cams and biosignal sensors. Primary, the automated monitoring of pain during the onset of analgesic sedation has the highest relevance in intensive care medicine. In this context, facial electromyography (EMG) represents an alternative to recording facial expressions <jats:italic>via<\/jats:italic> video in terms of data security. In the present study, specific physiological signals were analyzed to determine, whether a distinction can be made between pre-and post-analgesic administration in a postoperative setting. Explicitly, the significance of the facial EMG regarding the operationalization of the effect of analgesia was tested.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p><jats:italic>N<\/jats:italic>\u2009=\u200938 patients scheduled for surgical intervention where prospectively recruited. After the procedure the patients were transferred to intermediate care. Biosignals were recorded and all doses of analgesic sedations were carefully documented until they were transferred back to the general ward.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Almost every biosignal feature is able to distinguish significantly between \u2018<jats:italic>before<\/jats:italic>\u2019 and \u2018<jats:italic>after<\/jats:italic>\u2019 pain medication. We found the highest effect sizes (<jats:italic>r<\/jats:italic>\u2009=\u20090.56) for the facial EMG.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The results of the present study, findings from research based on the BioVid and X-ITE pain datasets, staff and patient acceptance indicate that it would now be appropriate to develop an APR prototype.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmed.2023.1038154","type":"journal-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T04:34:34Z","timestamp":1678854874000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["The impact of analgesic on EMG and other biosignals in a postoperative setting"],"prefix":"10.3389","volume":"10","author":[{"given":"Sascha","family":"Gruss","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Schmid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steffen","family":"Walter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benedikt","family":"Schick","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lena","family":"Holler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eberhard","family":"Barth","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"ref1","volume-title":"Schmerzkomponenten. 2., neu be. Schmerzkompendium","author":"Gallacchi","year":"2005"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"2258","DOI":"10.1097\/00003246-200112000-00004","article-title":"Assessing pain in critically ill sedated patients by using a behavioral pain scale","volume":"29","author":"Payen","year":"2001","journal-title":"Crit Care Med"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1109\/TAFFC.2019.2946774","article-title":"Automatic recognition methods supporting pain assessmentL: a survey","volume":"13","author":"Werner","year":"2019","journal-title":"IEEE Trans Affect Comput"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1007\/s00482-020-00473-x","article-title":"From external assessment of pain to automated multimodal measurement of pain intensity: narrative review of state of research and clinical perspectives","volume":"34","author":"Frisch","year":"2020","journal-title":"Schmerz"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1109\/TAFFC.2016.2537327","article-title":"Automatic pain assessment with facial activity descriptors","volume":"8","author":"Werner","year":"2017","journal-title":"IEEE Trans Affect Comput"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1016\/j.imavis.2014.02.008","article-title":"Classification and weakly supervised pain localization using multiple segment representation","volume":"32","author":"Sikka","year":"2014","journal-title":"Image Vis Comput"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1109\/ACII.2015.7344578","article-title":"Pain level recognition using kinematics and muscle activity for physical rehabilitation in chronic pain","volume-title":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII).","author":"Olugbade","year":"2015"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"5698","DOI":"10.1145\/2858036.2858302","article-title":"Musically Informed Sonification for Chronic Pain Rehabilitation: Facilitating Progress & Avoiding Musically Informed Sonification for Chronic Pain Rehabilitation: Facilitating Progress & Avoiding Over-Doing","volume-title":"Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems","author":"Newbold","year":"2016"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"3903","DOI":"10.1145\/3025453.3025947","article-title":"Supporting Everyday Function in Chronic Pain Using Wearable Technology","volume-title":"Proceedings of the 2017 CHI Conference on human factors in computing systems","author":"Singh","year":"2017"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1109\/TAFFC.2019.2892090","article-title":"Multi-modal pain intensity recognition based on the SenseEmotion database","volume":"12","author":"Thiam","year":"2019","journal-title":"IEEE Trans Affect Comput"},{"key":"ref11","first-page":"290","article-title":"Twofold-multimodal pain recognition with the X-ITE pain database","author":"Werner","year":"2019"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1016\/0304-3959(82)90146-4","article-title":"Autonomic indices and reactive pain reports on the McGill pain questionnaire","volume":"14","author":"Dowling","year":"1982","journal-title":"Pain"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1054\/jpai.2001.25529","article-title":"Sensory and affective dimensions of phasic pain are indistinguishable in the self-report and psychophysiology of normal laboratory subjects","volume":"2","author":"Chapman","year":"2001","journal-title":"J Pain"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1016\/j.pain.2010.11.032","article-title":"Autonomic responses to heat pain: heart rate, skin conductance, and their relation to verbal ratings and stimulus intensity","volume":"152","author":"Loggia","year":"2011","journal-title":"Pain"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"1807","DOI":"10.1016\/j.pain.2012.04.008","article-title":"Differentiating between heat pain intensities: the combined effect of multiple autonomic parameters","volume":"153","author":"Treister","year":"2012","journal-title":"Pain"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"e0140330","DOI":"10.1371\/journal.pone.0140330","article-title":"Pain intensity recognition rates via biopotential feature patterns with support vector machines","volume":"10","author":"Gruss","year":"2015","journal-title":"PLoS One"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1111\/j.1365-2044.2008.05834.x","article-title":"Monitoring of sympathetic tone to assess postoperative pain: skin conductance vs surgical stress index","volume":"64","author":"Ledowski","year":"2009","journal-title":"Anaesthesia"},{"key":"ref18","doi-asserted-by":"crossref","DOI":"10.4108\/icst.pervasivehealth.2015.259166","article-title":"Data fusion for automated pain recognition","author":"Walter","year":"2015"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1007\/s00482-020-00468-8","article-title":"Multimodal recognition of pain intensity and pain modality with machine learning","volume":"34","author":"Walter","year":"2020","journal-title":"Schmerz"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1007\/s00482-016-0105-x","article-title":"Mimische Aktivit\u00e4t differenzierter Schmerzintensit\u00e4ten: Korrelation der Merkmale von Facial Action Coding System und Elektromyographie","volume":"30","author":"Limbrecht-Ecklundt","year":"2016","journal-title":"Schmerz"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"957","DOI":"10.1136\/gutjnl-2018-317058","article-title":"Virtual reality in GI endoscopy: intuitive zoom for improving diagnostics and training","volume":"68","author":"Hann","year":"2019","journal-title":"Gut"},{"key":"ref22","volume-title":"Medikamente in der Schmerztherapie: Analgetika, Koanalgetika und Adjuvanzien von A-Z","author":"Artner","year":"2018"},{"key":"ref23","volume-title":"Pharmakologie und Toxikologie","author":"Karow","year":"2018"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"e59057","DOI":"10.3791\/59057","article-title":"Multimodal signals for analyzing pain responses to thermal and electrical stimuli","author":"Gruss","year":"2019","journal-title":"JoVe"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"2176","DOI":"10.1016\/j.ins.2007.12.013","article-title":"The application of the Hilbert spectrum to the analysis of electromyographic signals","volume":"178","author":"Andrade","year":"2008","journal-title":"Inf Sci"},{"key":"ref26","first-page":"1157","article-title":"Quantitative investigation of QRS detection rules using MIT\/BIH arrhythmia database","author":"Hamilton","year":"1987","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1111\/1467-8721.ep10768783","article-title":"Statistical Power Analysis","volume":"1","author":"Statistical","year":"1992","journal-title":"Curr Dir Psychol Sci"},{"key":"ref28","volume-title":"Statistical Power Analysis for the Behavioral Sciences","author":"Cohen","year":"1988"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"566278","DOI":"10.3389\/fmed.2020.566278","article-title":"\u201cWhat about automated pain recognition for routine clinical use?\u201d a survey of physicians and nursing staff on expectations, requirements and acceptance","volume":"7","author":"Walter","year":"2020","journal-title":"Front Med"},{"key":"ref30","doi-asserted-by":"crossref","DOI":"10.1109\/CYBConf.2013.6617456","article-title":"The biovid heat pain database: data for the advancement and systematic validation of an automated pain recognition","author":"Walter","year":"2013"}],"container-title":["Frontiers in Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2023.1038154\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T04:34:42Z","timestamp":1678854882000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2023.1038154\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,15]]},"references-count":30,"alternative-id":["10.3389\/fmed.2023.1038154"],"URL":"https:\/\/doi.org\/10.3389\/fmed.2023.1038154","relation":{},"ISSN":["2296-858X"],"issn-type":[{"value":"2296-858X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,15]]},"article-number":"1038154"}}