{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T08:57:51Z","timestamp":1770541071471,"version":"3.49.0"},"reference-count":49,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,1,21]],"date-time":"2023-01-21T00:00:00Z","timestamp":1674259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Zayed Health Center at UAE University","award":["G00003476"],"award-info":[{"award-number":["G00003476"]}]},{"name":"Zayed Health Center at UAE University","award":["EP\/T021063\/1"],"award-info":[{"award-number":["EP\/T021063\/1"]}]},{"name":"Zayed Health Center at UAE University","award":["EP\/T021020\/1"],"award-info":[{"award-number":["EP\/T021020\/1"]}]},{"name":"EPSRC","award":["G00003476"],"award-info":[{"award-number":["G00003476"]}]},{"name":"EPSRC","award":["EP\/T021063\/1"],"award-info":[{"award-number":["EP\/T021063\/1"]}]},{"name":"EPSRC","award":["EP\/T021020\/1"],"award-info":[{"award-number":["EP\/T021020\/1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Breathing monitoring is an efficient way of human health sensing and predicting numerous diseases. Various contact and non-contact-based methods are discussed in the literature for breathing monitoring. Radio frequency (RF)-based breathing monitoring has recently gained enormous popularity among non-contact methods. This method eliminates privacy concerns and the need for users to carry a device. In addition, such methods can reduce stress on healthcare facilities by providing intelligent digital health technologies. These intelligent digital technologies utilize a machine learning (ML)-based system for classifying breathing abnormalities. Despite advances in ML-based systems, the increasing dimensionality of data poses a significant challenge, as unrelated features can significantly impact the developed system\u2019s performance. Optimal feature scoring may appear to be a viable solution to this problem, as it has the potential to improve system performance significantly. Initially, in this study, software-defined radio (SDR) and RF sensing techniques were used to develop a breathing monitoring system. Minute variations in wireless channel state information (CSI) due to breathing movement were used to detect breathing abnormalities in breathing patterns. Furthermore, ML algorithms intelligently classified breathing abnormalities in single and multiple-person scenarios. The results were validated by referencing a wearable sensor. Finally, optimal feature scoring was used to improve the developed system\u2019s performance in terms of accuracy, training time, and prediction speed. The results showed that optimal feature scoring can help achieve maximum accuracy of up to 93.8% and 91.7% for single-person and multi-person scenarios, respectively.<\/jats:p>","DOI":"10.3390\/s23031251","type":"journal-article","created":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T01:36:26Z","timestamp":1674437786000},"page":"1251","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Enhancing System Performance through Objective Feature Scoring of Multiple Persons\u2019 Breathing Using Non-Contact RF Approach"],"prefix":"10.3390","volume":"23","author":[{"given":"Mubashir","family":"Rehman","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, HITEC University, Taxila 47080, Pakistan"},{"name":"Department of Electrical and Computer Engineering, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan"}]},{"given":"Raza Ali","family":"Shah","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, HITEC University, Taxila 47080, Pakistan"}]},{"given":"Najah Abed Abu","family":"Ali","sequence":"additional","affiliation":[{"name":"College of Information Technology, United Arab Emirates University (UAEU), Abu Dhabi 15551, United Arab Emirates"}]},{"given":"Muhammad Bilal","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan"},{"name":"College of Information Technology, United Arab Emirates University (UAEU), Abu Dhabi 15551, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2052-1121","authenticated-orcid":false,"given":"Syed Aziz","family":"Shah","sequence":"additional","affiliation":[{"name":"Research Centre for Intelligent Healthcare, Coventry University, Coventry CV1 5FB, UK"}]},{"given":"Akram","family":"Alomainy","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6159-7512","authenticated-orcid":false,"given":"Mohammad","family":"Hayajneh","sequence":"additional","affiliation":[{"name":"College of Information Technology, United Arab Emirates University (UAEU), Abu Dhabi 15551, United Arab Emirates"}]},{"given":"Xiaodong","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4743-9136","authenticated-orcid":false,"given":"Muhammad Ali","family":"Imran","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7097-9969","authenticated-orcid":false,"given":"Qammer H.","family":"Abbasi","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Nandakumar, R., Gollakota, S., and Watson, N. (2015, January 18\u201322). Contactless Sleep Apnea Detection on Smartphones. Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services, Florence, Italy.","DOI":"10.1145\/2742647.2742674"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"17180","DOI":"10.1109\/JSEN.2021.3077530","article-title":"Contactless Small-Scale Movement Monitoring System Using Software Defined Radio for Early Diagnosis of COVID-19","volume":"21","author":"Rehman","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"657","DOI":"10.5694\/j.1326-5377.2008.tb01825.x","article-title":"Respiratory Rate: The Neglected Vital Sign","volume":"188","author":"Cretikos","year":"2008","journal-title":"Med. J. Aust."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"12","DOI":"10.7748\/en2011.05.19.2.12.c8504","article-title":"Rate of Respiration: The Forgotten Vital Sign","volume":"19","author":"Parkes","year":"2011","journal-title":"Emerg. Nurse"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1644","DOI":"10.1093\/eurheartj\/ehs420","article-title":"Respiratory Rate Predicts Outcome after Acute Myocardial Infarction: A Prospective Cohort Study","volume":"34","author":"Barthel","year":"2013","journal-title":"Eur. Heart J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1016\/j.jelectrocard.2014.07.020","article-title":"Development of Three Methods for Extracting Respiration from the Surface ECG: A Review","volume":"47","author":"Helfenbein","year":"2014","journal-title":"J. Electrocardiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1097\/ACO.0000000000000541","article-title":"Risk Factors for Opioid-Induced Respiratory Depression and Failure to Rescue: A Review","volume":"31","author":"Gupta","year":"2018","journal-title":"Curr. Opin. Anaesthesiol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/S0378-3782(98)00039-5","article-title":"Increased Amplitude Modulation of Continuous Respiration Precedes Sudden Infant Death Syndrome: Detection by Spectral Estimation of Respirogram","volume":"53","author":"Rantonen","year":"1998","journal-title":"Early Hum. Dev."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.annemergmed.2004.06.016","article-title":"The Vexatious Vital: Neither Clinical Measurements by Nurses nor an Electronic Monitor Provides Accurate Measurements of Respiratory Rate in Triage","volume":"45","author":"Lovett","year":"2005","journal-title":"Ann. Emerg. Med."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Wiesner, S., and Yaniv, Z. (2007, January 22\u201326). Monitoring Patient Respiration Using a Single Optical Camera. Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France.","DOI":"10.1109\/IEMBS.2007.4352895"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4567213","DOI":"10.1155\/2018\/4567213","article-title":"Contactless Monitoring of Breathing Patterns and Respiratory Rate at the Pit of the Neck: A Single Camera Approach","volume":"2018","author":"Massaroni","year":"2018","journal-title":"J. Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3161188","article-title":"C-FMCW Based Contactless Respiration Detection Using Acoustic Signal","volume":"1","author":"Wang","year":"2018","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3214289","article-title":"Extracting Multi-Person Respiration from Entangled RF Signals","volume":"2","author":"Yue","year":"2018","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2700211","DOI":"10.1109\/JTEHM.2019.2951670","article-title":"Small-Scale Perception in Medical Body Area Networks","volume":"7","author":"Fan","year":"2019","journal-title":"IEEE J. Transl. Eng. Health Med."},{"key":"ref_15","unstructured":"Qian, K., Wu, C., Yang, Z., Liu, Y., and Jamieson, K. (2017, January 10\u201314). Widar: Decimeter-Level Passive Tracking via Velocity Monitoring with Commodity Wi-Fi. Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing, Chennai, India."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Al-Wahedi, A., Al-Shams, M., Albettar, M.A., Alawsh, S., and Muqaibel, A. (2019, January 21\u201324). Wireless Monitoring of Respiration and Heart Rates Using Software-Defined-Radio. Proceedings of the 2019 16th International Multi-Conference on Systems, Signals & Devices (SSD), Istanbul, Turkey.","DOI":"10.1109\/SSD.2019.8893254"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Praktika, T.O., and Pramudita, A.A. (2020, January 26\u201328). Implementation of Multi-Frequency Continuous Wave Radar for Respiration Detection Using Software Defined Radio. Proceedings of the 2020 10th Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), Malang, Indonesia.","DOI":"10.1109\/EECCIS49483.2020.9263472"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Rehman, M., Shah, R.A., Khan, M.B., Shah, S.A., AbuAli, N.A., Yang, X., Alomainy, A., Imran, M.A., and Abbasi, Q.H. (2021). Improving Machine Learning Classification Accuracy for Breathing Abnormalities by Enhancing Dataset. Sensors, 21.","DOI":"10.3390\/s21206750"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2808","DOI":"10.1001\/jama.1990.03450210108045","article-title":"Clinical Methods: The History, Physical, and Laboratory Examinations","volume":"264","author":"Walker","year":"1990","journal-title":"JAMA"},{"key":"ref_20","first-page":"1","article-title":"Beyond Respiration: Contactless Sleep Sound-Activity Recognition Using RF Signals","volume":"3","author":"Liu","year":"2019","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Adib, F., Mao, H., Kabelac, Z., Katabi, D., and Miller, R.C. (2015, January 18\u201323). Smart Homes That Monitor Breathing and Heart Rate. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Soul, Republic of Korea.","DOI":"10.1145\/2702123.2702200"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Islam, S.M., Motoyama, N., Pacheco, S., and Lubecke, V.M. (2020, January 4\u20136). Non-Contact Vital Signs Monitoring for Multiple Subjects Using a Millimeter Wave FMCW Automotive Radar. Proceedings of the 2020 IEEE\/MTT-S International Microwave Symposium (IMS), Los Angeles, CA, USA.","DOI":"10.1109\/IMS30576.2020.9223838"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Cardillo, E., Li, C., and Caddemi, A. (2020, January 3\u20135). Empowering Blind People Mobility: A Millimeter-Wave Radar Cane. Proceedings of the 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT, Online.","DOI":"10.1109\/MetroInd4.0IoT48571.2020.9138239"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"14043","DOI":"10.1109\/JSEN.2020.3024961","article-title":"Radar Range-Breathing Separation for the Automatic Detection of Humans in Cluttered Environments","volume":"21","author":"Cardillo","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3397311","article-title":"BodyCompass: Monitoring Sleep Posture with Wireless Signals","volume":"4","author":"Yue","year":"2020","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_26","unstructured":"(2022, December 01). Ultra-Wideband Radar Technology. Available online: https:\/\/www.routledge.com\/Ultra-wideband-Radar-Technology\/Taylor\/p\/book\/9780849342677."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2046","DOI":"10.1109\/TMTT.2013.2256924","article-title":"A Review on Recent Advances in Doppler Radar Sensors for Noncontact Healthcare Monitoring","volume":"61","author":"Li","year":"2013","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1109\/TIM.2010.2064370","article-title":"Wireless Sensing of Human Respiratory Parameters by Low-Power Ultrawideband Impulse Radio Radar","volume":"60","author":"Lai","year":"2010","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Liu, X., Cao, J., Tang, S., and Wen, J. (2014, January 2\u20135). Wi-Sleep: Contactless Sleep Monitoring via Wifi Signals. Proceedings of the 2014 IEEE Real-Time Systems Symposium, Rome, Italy.","DOI":"10.1109\/RTSS.2014.30"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2466","DOI":"10.1109\/TMC.2015.2504935","article-title":"Contactless Respiration Monitoring via Off-the-Shelf WiFi Devices","volume":"15","author":"Liu","year":"2015","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, D., Ma, J., Wang, Y., Wang, Y., Wu, D., Gu, T., and Xie, B. (2016, January 12\u201316). Human Respiration Detection with Commodity Wifi Devices: Do User Location and Body Orientation Matter?. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany.","DOI":"10.1145\/2971648.2971744"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3264958","article-title":"FullBreathe: Full Human Respiration Detection Exploiting Complementarity of CSI Phase and Amplitude of WiFi Signals","volume":"2","author":"Zeng","year":"2018","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3351279","article-title":"FarSense: Pushing the Range Limit of WiFi-Based Respiration Sensing with CSI Ratio of Two Antennas","volume":"3","author":"Zeng","year":"2019","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Liu, J., Wang, Y., Chen, Y., Yang, J., Chen, X., and Cheng, J. (2015, January 22\u201325). Tracking Vital Signs during Sleep Leveraging Off-the-Shelf Wifi. Proceedings of the 16th ACM International Symposium on Mobile ad hoc Networking and Computing, Hangzhou, China.","DOI":"10.1145\/2746285.2746303"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Niu, K., Zhang, F., Chang, Z., and Zhang, D. (2018, January 8\u201312). A Fresnel Diffraction Model Based Human Respiration Detection System Using COTS Wi-Fi Devices. Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, Singapore.","DOI":"10.1145\/3267305.3267561"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wang, X., Yang, C., and Mao, S. (2017, January 5\u20138). PhaseBeat: Exploiting CSI Phase Data for Vital Sign Monitoring with Commodity WiFi Devices. Proceedings of the 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Atlanta, GA, USA.","DOI":"10.1109\/ICDCS.2017.206"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1939","DOI":"10.1109\/29.45540","article-title":"Performance Analysis of Root-MUSIC","volume":"37","author":"Rao","year":"1989","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"ref_38","first-page":"1","article-title":"TensorBeat: Tensor Decomposition for Monitoring Multiperson Breathing Beats with Commodity WiFi","volume":"9","author":"Wang","year":"2017","journal-title":"ACM Trans. Intell. Syst. Technol. (TIST)"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1109\/TBME.2017.2699422","article-title":"TR-BREATH: Time-Reversal Breathing Rate Estimation and Detection","volume":"65","author":"Chen","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Yang, Y., Cao, J., Liu, X., and Xing, K. (2018, January 9\u201312). Multi-Person Sleeping Respiration Monitoring with COTS WiFi Devices. Proceedings of the 2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Chengdu, China.","DOI":"10.1109\/MASS.2018.00017"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"18858","DOI":"10.1109\/JSEN.2022.3196564","article-title":"Development of an Intelligent Real-Time Multiperson Respiratory Illnesses Sensing System Using SDR Technology","volume":"22","author":"Rehman","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"5111","DOI":"10.1109\/JSEN.2020.3035960","article-title":"Non-Invasive RF Sensing for Detecting Breathing Abnormalities Using Software Defined Radios","volume":"21","author":"Ashleibta","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Khan, M.B., Rehman, M., Mustafa, A., Shah, R.A., and Yang, X. (2021). Intelligent Non-Contact Sensing for Connected Health Using Software Defined Radio Technology. Electronics, 10.","DOI":"10.3390\/electronics10131558"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Rehman, M., Shah, R.A., Khan, M.B., AbuAli, N.A., Shah, S.A., Yang, X., Alomainy, A., Imran, M.A., and Abbasi, Q.H. (2021). RF Sensing Based Breathing Patterns Detection Leveraging USRP Devices. Sensors, 21.","DOI":"10.3390\/s21113855"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"5387","DOI":"10.1007\/s00500-016-2123-0","article-title":"Stock Market Trend Prediction Using AHP and Weighted Kernel LS-SVM","volume":"21","year":"2017","journal-title":"Soft Comput."},{"key":"ref_46","first-page":"1157","article-title":"An Introduction to Variable and Feature Selection","volume":"3","author":"Guyon","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1142\/S0219720005001004","article-title":"Minimum Redundancy Feature Selection from Microarray Gene Expression Data","volume":"3","author":"Ding","year":"2005","journal-title":"J. Bioinform. Comput. Biol."},{"key":"ref_48","unstructured":"(2022, December 01). How to Choose a Feature Selection Method for Machine Learning\u2014MachineLearningMastery.Com. Available online: https:\/\/machinelearningmastery.com\/feature-selection-with-real-and-categorical-data\/."},{"key":"ref_49","first-page":"1","article-title":"MultiSense: Enabling Multi-Person Respiration Sensing with Commodity Wifi","volume":"4","author":"Zeng","year":"2020","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/3\/1251\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:12:52Z","timestamp":1760119972000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/3\/1251"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,21]]},"references-count":49,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["s23031251"],"URL":"https:\/\/doi.org\/10.3390\/s23031251","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,21]]}}}