{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T18:18:50Z","timestamp":1791915530160,"version":"4.3.4"},"reference-count":83,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T00:00:00Z","timestamp":1682035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Pain is a complex and subjective experience, and traditional methods of pain assessment can be limited by factors such as self-report bias and observer variability. Voice is frequently used to evaluate pain, occasionally in conjunction with other behaviors such as facial gestures. Compared to facial emotions, there is less available evidence linking pain with voice. This literature review synthesizes the current state of research on the use of voice recognition and voice analysis for pain detection in adults, with a specific focus on the role of artificial intelligence (AI) and machine learning (ML) techniques. We describe the previous works on pain recognition using voice and highlight the different approaches to voice as a tool for pain detection, such as a human effect or biosignal. Overall, studies have shown that AI-based voice analysis can be an effective tool for pain detection in adult patients with various types of pain, including chronic and acute pain. We highlight the high accuracy of the ML-based approaches used in studies and their limitations in terms of generalizability due to factors such as the nature of the pain and patient population characteristics. However, there are still potential challenges, such as the need for large datasets and the risk of bias in training models, which warrant further research.<\/jats:p>","DOI":"10.3390\/bioengineering10040500","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T07:51:17Z","timestamp":1682063477000},"page":"500","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["A Review of Voice-Based Pain Detection in Adults Using Artificial Intelligence"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7845-7356","authenticated-orcid":false,"given":"Sahar","family":"Borna","sequence":"first","affiliation":[{"name":"Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clifton R.","family":"Haider","sequence":"additional","affiliation":[{"name":"Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55902, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karla C.","family":"Maita","sequence":"additional","affiliation":[{"name":"Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ricardo A.","family":"Torres","sequence":"additional","affiliation":[{"name":"Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francisco R.","family":"Avila","sequence":"additional","affiliation":[{"name":"Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John P.","family":"Garcia","sequence":"additional","affiliation":[{"name":"Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gioacchino D.","family":"De Sario Velasquez","sequence":"additional","affiliation":[{"name":"Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher J.","family":"McLeod","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charles J.","family":"Bruce","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0818-273X","authenticated-orcid":false,"given":"Rickey E.","family":"Carter","sequence":"additional","affiliation":[{"name":"Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2004-7538","authenticated-orcid":false,"given":"Antonio J.","family":"Forte","sequence":"additional","affiliation":[{"name":"Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5717","DOI":"10.1007\/s11042-021-11761-8","article-title":"Pain fingerprinting using multimodal sensing: Pilot study","volume":"81","author":"Keskinarkaus","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tsai, F.-S., Weng, Y.-M., Ng, C.-J., and Lee, C.-C. (2019, January 18\u201321). Pain versus Affect? An Investigation in the Relationship between Observed Emotional States and Self-Reported Pain. Proceedings of the 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Lanzhou, China.","DOI":"10.1109\/APSIPAASC47483.2019.9023134"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1016\/j.jpain.2022.02.013","article-title":"A Review of Potential National Chronic Pain Surveillance Systems in the United States","volume":"23","author":"Duca","year":"2022","journal-title":"J. Pain"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Shu, L., Xie, J., Yang, M., Li, Z., Li, Z., Liao, D., Xu, X., and Yang, X. (2018). A Review of Emotion Recognition Using Physiological Signals. Sensors, 18.","DOI":"10.3390\/s18072074"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"197","DOI":"10.15171\/jcs.2018.030","article-title":"Behavioral Pain Indicators in Patients with Traumatic Brain Injury Admitted to an Intensive Care Unit","volume":"7","author":"Nazari","year":"2018","journal-title":"J. Caring Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"896276","DOI":"10.3389\/fpain.2022.896276","article-title":"Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches","volume":"3","author":"Berger","year":"2022","journal-title":"Front. Pain Res."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Li, J.-L., Weng, Y.-M., Ng, C.-J., and Lee, C.-C. (2018, January 2\u20136). Learning Conditional Acoustic Latent Representation with Gender and Age Attributes for Automatic Pain Level Recognition. Proceedings of the Interspeech 2018, Hyderabad, India.","DOI":"10.21437\/Interspeech.2018-1298"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.jneumeth.2004.07.005","article-title":"Computerized analysis of audible and ultrasonic vocalizations of rats as a standardized measure of pain-related behavior","volume":"141","author":"Han","year":"2005","journal-title":"J. Neurosci. Methods"},{"key":"ref_9","unstructured":"Ren, Z., Cummins, N., Han, J., Schnieder, S., Krajewski, J., and Schuller, B. (2018, January 10\u201312). Evaluation of the pain level from speech: Introducing a novel pain database and benchmarks. Proceedings of the 13th ITG-Symposium, Oldenburg, Germany. Speech Communication."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1109\/TAFFC.2019.2946774","article-title":"Automatic Recognition Methods Supporting Pain Assessment: A Survey","volume":"13","author":"Werner","year":"2019","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1017\/S0012162200001146","article-title":"Preliminary validation of an observational checklist for persons with cognitive impairments and inability to communicate verbally","volume":"42","author":"Breau","year":"2000","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_12","first-page":"e59057","article-title":"Multi-modal signals for analyzing pain responses to thermal and electrical stimuli","volume":"146","author":"Gruss","year":"2019","journal-title":"JoVE (J. Vis. Exp.)"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.pmn.2012.09.004","article-title":"Differences in Pain Measures by Mini-Mental State Examination Scores of Residents in Aged Care Facilities: Examining the Usability of the Abbey Pain Scale\u2013Japanese Version","volume":"15","author":"Takai","year":"2014","journal-title":"Pain Manag. Nurs."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Tsai, F.-S., Weng, Y.-M., Ng, C.-J., and Lee, C.-C. (2017, January 23\u201326). Embedding stacked bottleneck vocal features in a LSTM architecture for automatic pain level classification during emergency triage. Proceedings of the 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, TX, USA.","DOI":"10.1109\/ACII.2017.8273618"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1703","DOI":"10.1002\/ejp.1623","article-title":"Crying out in pain\u2014A systematic review into the validity of vocalization as an indicator for pain","volume":"24","author":"Helmer","year":"2020","journal-title":"Eur. J. Pain"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.pmn.2014.06.003","article-title":"Generating and Selecting Pain Indicators for Brain-Injured Critical Care Patients","volume":"16","author":"Roulin","year":"2015","journal-title":"Pain Manag. Nurs."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/S0885-3924(02)00530-4","article-title":"Pain Assessment in Elderly Patients with Severe Dementia","volume":"25","author":"Manfredi","year":"2003","journal-title":"J. Pain Symptom Manag."},{"key":"ref_18","first-page":"6","article-title":"Investigating the Variability of Voice Quality and Pain Levels as a Function of Multiple Clinical Parameters","volume":"762","author":"Hong","year":"2019","journal-title":"Age"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Lotan, M., and Icht, M. (2023). Diagnosing Pain in Individuals with Intellectual and Developmental Disabilities: Current State and Novel Technological Solutions. Diagnostics, 13.","DOI":"10.3390\/diagnostics13030401"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"107365","DOI":"10.1016\/j.cmpb.2023.107365","article-title":"Automatic assessment of pain based on deep learning methods: A systematic review","volume":"231","author":"Gkikas","year":"2023","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_21","first-page":"1","article-title":"Feature extraction methods LPC, PLP and MFCC in speech recognition","volume":"1","author":"Dave","year":"2013","journal-title":"Int. J. Adv. Res. Eng. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Htet, Y., Zin, T.T., Tin, P., Tamura, H., Kondo, K., and Chosa, E. (2022). HMM-Based Action Recognition System for Elderly Healthcare by Colorizing Depth Map. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph191912055"},{"key":"ref_23","first-page":"455","article-title":"Support-Vector Machine-Based Classifier of Cross-Correlated Phoneme Segments for Speech Sound Disorder Screening","volume":"294","author":"Mahmut","year":"2022","journal-title":"Stud. Health Technol. Inform."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Liang, Y.-C., Wijaya, I., Yang, M.-T., Juarez, J.R.C., and Chang, H.-T. (2022). Deep Learning for Infant Cry Recognition. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19106311"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1044\/2022_AJSLP-22-00142","article-title":"Tutorial: Using Visual\u2013Acoustic Biofeedback for Speech Sound Training","volume":"32","author":"Hitchcock","year":"2023","journal-title":"Am. J. Speech-Lang. Pathol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"655202","DOI":"10.3389\/fpsyg.2021.655202","article-title":"Can the Vocal Expression of Intellectually Disabled Individuals Be Used as a Pain Indicator? Initial Findings Supporting a Possible Novice Assessment Method","volume":"12","author":"Icht","year":"2021","journal-title":"Front. Psychol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e597","DOI":"10.1097\/PR9.0000000000000597","article-title":"Phonetic characteristics of vocalizations during pain","volume":"2","author":"Lautenbacher","year":"2017","journal-title":"Pain Rep."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1080\/09524622.2018.1463295","article-title":"Vocal communication of simulated pain","volume":"28","author":"Raine","year":"2018","journal-title":"Bioacoustics"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1046\/j.1365-2648.2002.02206.x","article-title":"Dealing with uncertainty: Parental assessment of pain in their children with profound special needs","volume":"38","author":"Carter","year":"2002","journal-title":"J. Adv. Nurs."},{"key":"ref_30","unstructured":"Salinas-Ranneberg, M., Niebuhr, O., Kunz, M., Lautenbacher, S., and Barbosa, P. (2017, January 6\u20139). Effects of pain on vowel production\u2013Towards a new way of pain-level estimation based on acoustic speech-signal analyses. Proceedings of the 43 Deutsche Jahrestagung f\u00fcr Akustik, Kiel, Germany."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Corbett, A., Achterberg, W.P., Husebo, B.S., Lobbezoo, F., de Vet, H., Kunz, M., Strand, L.I., Constantinou, M., Tudose, C., and Kappesser, J. (2014). An international road map to improve pain assessment in people with impaired cognition: The development of the Pain Assessment in Impaired Cognition (PAIC) meta-tool. BMC Neurol., 14.","DOI":"10.1186\/s12883-014-0229-5"},{"key":"ref_32","first-page":"e211","article-title":"The Analysis of Pain Research through the Lens of Artificial Intelligence and Machine Learning","volume":"25","author":"Nagireddi","year":"2022","journal-title":"Pain Physician"},{"key":"ref_33","unstructured":"Mundial, F.E., and Schwab, K. (2016, January 11\u201312). The Fourth Industrial Revolution: What it means, how to respond. Proceedings of the 2016 World Economic Forum, Dubai, United Arab Emirates."},{"key":"ref_34","unstructured":"House of Lords Select Committee A (2018). AI in the UK: Ready, Willing and Able, House of Lords."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"101649","DOI":"10.1016\/j.techsoc.2021.101649","article-title":"Collective action on artificial intelligence: A primer and review","volume":"66","author":"Baum","year":"2021","journal-title":"Technol. Soc."},{"key":"ref_36","first-page":"49","article-title":"Chapter 4. Robot companions and ethics: A pragmatic approach of ethical design","volume":"24","author":"Cornet","year":"2013","journal-title":"J. Int. Bio\u00e9th."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"S36","DOI":"10.1016\/j.metabol.2017.01.011","article-title":"Artificial intelligence in medicine","volume":"69","author":"Hamet","year":"2017","journal-title":"Metabolism"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1111\/odi.14056","article-title":"Deep learning for osteoarthritis classification in temporomandibular joint","volume":"29","author":"Jung","year":"2023","journal-title":"Oral Dis."},{"key":"ref_39","first-page":"981","article-title":"Survey on natural language processing in medical image analysis","volume":"47","author":"Liu","year":"2022","journal-title":"Zhong Nan Da Xue Xue Bao Yi Xue Ban"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.artmed.2014.12.012","article-title":"Predicting protein complexes from weighted protein\u2013protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering","volume":"63","author":"Theofilatos","year":"2015","journal-title":"Artif. Intell. Med."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1994","DOI":"10.3758\/s13414-021-02369-z","article-title":"The influence of time structure on prediction motion in visual and auditory modalities","volume":"84","author":"Qin","year":"2022","journal-title":"Atten. Percept. Psychophys."},{"key":"ref_42","doi-asserted-by":"crossref","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":"ref_43","doi-asserted-by":"crossref","unstructured":"Walter, S., Gruss, S., Ehleiter, H., Tan, J., Traue, H.C., Crawcour, S., Werner, P., Al-Hamadi, A., and Andrade, A.O. (2013, January 13\u201315). The biovid heat pain database data for the advancement and systematic validation of an automated pain recognition system. Proceedings of the 2013 IEEE International Conference on Cybernetics (CYBCO), Lausanne, Switzerland.","DOI":"10.1109\/CYBConf.2013.6617456"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Lucey, P., Cohn, J.F., Prkachin, K.M., Solomon, P.E., and Matthews, I. (2011, January 21\u201323). Painful data: The UNBC-McMaster shoulder pain expression archive database. Proceedings of the 2011 IEEE International Conference on Automatic Face & Gesture Recognition (FG), Santa Barbara, CA, USA.","DOI":"10.1109\/FG.2011.5771462"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3314","DOI":"10.1109\/TCYB.2017.2662199","article-title":"Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification","volume":"52","author":"Rodriguez","year":"2022","journal-title":"IEEE Trans. Cybern."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Gouverneur, P., Li, F., Shirahama, K., Luebke, L., Adamczyk, W.M., Szikszay, T.M., Luedtke, K., and Grzegorzek, M. (2023). Explainable Artificial Intelligence (XAI) in Pain Research: Understanding the Role of Electrodermal Activity for Automated Pain Recognition. Sensors, 23.","DOI":"10.3390\/s23041959"},{"key":"ref_47","unstructured":"Krenker, A., Be\u0161ter, J., and Kos, A. (2011). Artificial Neural Networks: Methodological Advances and Biomedical Applications, InTech."},{"key":"ref_48","unstructured":"O\u2019Shea, K., and Nash, R. (2015). An introduction to convolutional neural networks. arXiv."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"7231","DOI":"10.1038\/s41467-022-34780-x","article-title":"Path sampling of recurrent neural networks by incorporating known physics","volume":"13","author":"Tsai","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_50","first-page":"106","article-title":"Real Time Audio-Based Distress Signal Detection as Vital Signs of Myocardial Infarction Using Convolutional Neural Networks","volume":"13","author":"Mohan","year":"2022","journal-title":"J. Adv. Inf. Technol."},{"key":"ref_51","unstructured":"Zehetner, A., Hagm\u00fcller, M., and Pernkopf, F. (2014, January 1\u20135). Wake-up-word spotting for mobile systems. Proceedings of the 2014 22nd European Signal Processing Conference (EUSIPCO), Lisbon, Portugal."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.neunet.2022.03.003","article-title":"Two-stage streaming keyword detection and localization with multi-scale depthwise temporal convolution","volume":"150","author":"Hou","year":"2022","journal-title":"Neural Netw."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Qin, H., Ma, X., Ding, Y., Li, X., Zhang, Y., Ma, Z., Wang, J., Luo, J., and Liu, X. (2023). BiFSMNv2: Pushing Binary Neural Networks for Keyword Spotting to Real-Network Performance. IEEE Trans. Neural Netw. Learn. Syst., 1\u201313.","DOI":"10.1109\/TNNLS.2023.3243259"},{"key":"ref_54","unstructured":"Oshrat, Y., Bloch, A., Lerner, A., Cohen, A., Avigal, M., and Zeilig, G. (June, January 31). Speech prosody as a biosignal for physical pain detection. Proceedings of the 8th Conference on Speech Prosody, Boston, MA, USA."},{"key":"ref_55","first-page":"Cd015016","article-title":"Systemic opioid regimens for postoperative pain in neonates","volume":"4","author":"Kinoshita","year":"2023","journal-title":"Cochrane Database Syst. Rev."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1016\/j.hoc.2022.06.009","article-title":"Chronic Pain: Prevalence and Management","volume":"36","author":"Carroll","year":"2022","journal-title":"Hematol. Oncol. Clin. N. Am."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Tsai, F.-S., Hsu, Y.-L., Chen, W.-C., Weng, Y.-M., Ng, C.-J., and Lee, C.-C. (2016, January 8\u201312). Toward Development and Evaluation of Pain Level-Rating Scale for Emergency Triage based on Vocal Characteristics and Facial Expressions. Proceedings of the Interspeech 2016, San Francisco, CA, USA.","DOI":"10.21437\/Interspeech.2016-408"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1097\/EJA.0000000000001691","article-title":"Pain Management after Total Knee Arthroplasty: Procedure Specific Postoperative Pain Management Recommendations","volume":"39","author":"Kehlet","year":"2022","journal-title":"Eur. J. Anaesthesiol."},{"key":"ref_59","first-page":"535","article-title":"Cancer Pain and Opioid Use Disorder","volume":"36","author":"Ganguly","year":"2022","journal-title":"Oncology"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Grezl, F., Karafiat, M., and Vesely, K. (2014, January 4\u20139). Adaptation of multilingual stacked bottle-neck neural network structure for new language. Proceedings of the 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, Italy.","DOI":"10.1109\/ICASSP.2014.6855089"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Wu, Z., Valentini-Botinhao, C., Watts, O., and King, S. (2015, January 19\u201324). Deep neural networks employing multi-task learning and stacked bottleneck features for speech synthesis. Proceedings of the 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), South Brisbane, Australia.","DOI":"10.1109\/ICASSP.2015.7178814"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Chuangsuwanich, E., and Glass, J.R. (2014, January 14\u201318). Language ID-based training of multilingual stacked bottleneck features. Proceedings of the Interspeech 2014, Singapore.","DOI":"10.21437\/Interspeech.2014-1"},{"key":"ref_63","first-page":"255","article-title":"Knowledge of heart attack symptoms in a community survey of Victoria","volume":"14","author":"Smith","year":"2002","journal-title":"Emerg. Med. Australas."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1155\/2002\/426193","article-title":"Effects of Emotion on Pain Reports, Tolerance and Physiology","volume":"7","author":"Carter","year":"2002","journal-title":"Pain Res. Manag."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1002\/jclp.1030","article-title":"Pain and emotion: New research directions","volume":"57","author":"Keefe","year":"2001","journal-title":"J. Clin. Psychol."},{"key":"ref_66","unstructured":"Melzack, R. (1982). Wall PD the Challenge of Pain, Basic Books."},{"key":"ref_67","unstructured":"Robinson, M.E., and Riley, J.L. (1999). Psychosocial Factors in Pain: Critical Perspectives, The Guilford Press."},{"key":"ref_68","doi-asserted-by":"crossref","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":"ref_69","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/0304-3959(90)90052-F","article-title":"Heart rate changes as an autonomic component of the pain response","volume":"43","author":"Strian","year":"1990","journal-title":"Pain"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1161\/01.CIR.35.6.1073","article-title":"Relation of Heart Rate and Systolic Blood Pressure to the Onset of Pain in Angina Pectoris","volume":"35","author":"Robinson","year":"1967","journal-title":"Circulation"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1097\/ACO.0b013e3283183fe4","article-title":"Changes in skin conductance as a tool to monitor nociceptive stimulation and pain","volume":"21","author":"Storm","year":"2008","journal-title":"Curr. Opin. Anaesthesiol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1111\/j.1365-2044.2007.05191.x","article-title":"The assessment of postoperative pain by monitoring skin conductance: Results of a prospective study","volume":"62","author":"Ledowski","year":"2007","journal-title":"Anaesthesia"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1007\/s11906-022-01205-5","article-title":"The Effects of Pain and Analgesic Medications on Blood Pressure","volume":"24","author":"Rivasi","year":"2022","journal-title":"Curr. Hypertens. Rep."},{"key":"ref_74","first-page":"47","article-title":"Classification of high blood pressure persons vs. normal blood pressure persons using voice analysis","volume":"1","author":"Saloni","year":"2014","journal-title":"IJ Image Graph. Signal Process."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.jpain.2011.10.014","article-title":"The Perception of Pain in Others: How Gender, Race, and Age Influence Pain Expectations","volume":"13","author":"Wandner","year":"2012","journal-title":"J. Pain"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/0304-3959(95)00214-6","article-title":"Gender variations in clinical pain experience","volume":"65","author":"Unruh","year":"1996","journal-title":"Pain"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1016\/j.cnur.2004.02.013","article-title":"Pain assessment and management in persons with dementia","volume":"39","author":"Horgas","year":"2004","journal-title":"Nurs. Clin. N. Am."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.pain.2005.03.025","article-title":"Age effects on pain thresholds, temporal summation and spatial summation of heat and pressure pain","volume":"115","author":"Lautenbacher","year":"2005","journal-title":"Pain"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.ijcard.2009.11.046","article-title":"Influence of age on pain perception in acute myocardial ischemia: A possible cause for delayed treatment in elderly patients","volume":"149","author":"Rittger","year":"2011","journal-title":"Int. J. Cardiol."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.jpain.2005.02.007","article-title":"Sex Differences in the Associations among Psychological Factors and Pain Report: A Novel Psychophysical Study of Patients with Chronic Low Back Pain","volume":"6","author":"Robinson","year":"2005","journal-title":"J. Pain"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Werner, P., Al-Hamadi, A., Niese, R., Walter, S., Gruss, S., and Traue, H.C. (2014, January 24\u201328). Automatic pain recognition from video and biomedical signals. Proceedings of the 2014 22nd International Conference on Pattern Recognition, Stockholm, Sweden.","DOI":"10.1109\/ICPR.2014.784"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"54","DOI":"10.12968\/ijpn.2006.12.2.20531","article-title":"Introduction of a pain scale for palliative care patients with cognitive impairment","volume":"12","author":"Timmerman","year":"2006","journal-title":"Int. J. Palliat. Nurs."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.jpainsymman.2007.08.015","article-title":"Pain Behavior in Rheumatoid Arthritis Patients: Identification of Pain Behavior Subgroups","volume":"36","author":"Waters","year":"2008","journal-title":"J. Pain Symptom Manag."}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/10\/4\/500\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:20:43Z","timestamp":1760124043000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/10\/4\/500"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,21]]},"references-count":83,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["bioengineering10040500"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering10040500","relation":{},"ISSN":["2306-5354"],"issn-type":[{"value":"2306-5354","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,21]]}}}