{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:49:20Z","timestamp":1740149360098,"version":"3.37.3"},"reference-count":35,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,5]],"date-time":"2019-09-05T00:00:00Z","timestamp":1567641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61601164"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["PA2019GDQT0012"],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Physiological information such as respiratory rate and heart rate in the sleep state can be used to evaluate the health condition of the sleeper. Traditional sleep monitoring systems need body contact and are intrusive, which limits their applicability. Thus, a comfortable sleep biosignals detection system with both high accuracy and low cost is important for health care. In this paper, we design a sleep biosignals detection system based on low-cost piezoelectric ceramic sensors. 18 piezoelectric ceramic sensors are deployed under the mattress to capture the pressure data. The appropriate sensor that captures respiration and heartbeat sensitively is selected by the proposed channel-selection algorithm. Then, we propose a dynamic smoothing algorithm to extract respiratory rate and heart rate using the selected data. The dynamic smoothing can separate heartbeat signals from respiratory signals with low complexity by dynamically choosing the smooth window, and it is suitable for real-time implementation in low-cost embedded systems. For comparison, wavelet analysis and ensemble empirical mode decomposition (EEMD) are performed in a personal computer (PC). Experimental results show that data collected by piezoelectric ceramic sensors can be used for respiratory-rate and heart-rate detection with high accuracy. In addition, the dynamic smoothing can achieve high accuracy close to wavelet analysis and EEMD, while it has much lower complexity.<\/jats:p>","DOI":"10.3390\/s19183843","type":"journal-article","created":{"date-parts":[[2019,9,6]],"date-time":"2019-09-06T06:59:22Z","timestamp":1567753162000},"page":"3843","source":"Crossref","is-referenced-by-count":20,"title":["Detection of Sleep Biosignals Using an Intelligent Mattress Based on Piezoelectric Ceramic Sensors"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0901-3102","authenticated-orcid":false,"given":"Min","family":"Peng","sequence":"first","affiliation":[{"name":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China"},{"name":"Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei 230601, China"}]},{"given":"Zhizhong","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9099-0444","authenticated-orcid":false,"given":"Lusheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China"},{"name":"Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei 230601, China"}]},{"given":"Xusheng","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.compbiomed.2019.03.016","article-title":"Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals","volume":"108","author":"Viswabhargav","year":"2019","journal-title":"Comput. Biol. Med."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"35988","DOI":"10.1109\/ACCESS.2018.2849822","article-title":"A smart system for sleep monitoring by integrating IoT with big data analytics","volume":"6","author":"Yacchirema","year":"2018","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"45129","DOI":"10.1109\/ACCESS.2018.2865487","article-title":"Unobtrusive sleep monitoring using cardiac, breathing and movements activities: An exhaustive review","volume":"6","author":"Matar","year":"2018","journal-title":"IEEE Access"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"460","DOI":"10.3389\/fphys.2016.00460","article-title":"Modulations of heart rate, ECG, and cardio-respiratory coupling observed in polysomnography","volume":"7","author":"Penzel","year":"2016","journal-title":"Front. Physiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1547","DOI":"10.1109\/TBME.2016.2612938","article-title":"Development and evaluation of a wearable device for sleep quality assessment","volume":"64","author":"Kuo","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3887","DOI":"10.1109\/JSEN.2016.2536363","article-title":"Power line interference removal for high-quality continuous biosignal monitoring with low-power wearable devices","volume":"16","author":"Tomasini","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Majumder, S., Mondal, T., and Deen, M. (2017). Wearable sensors for remote health monitoring. Sensors, 17.","DOI":"10.3390\/s17010130"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1007\/s11277-016-3375-9","article-title":"A Qualitative Study on Implementation of the Intelligent Bed: Findings from a Rehabilitation Ward at a Large Chinese Tertiary Hospital","volume":"90","author":"Cai","year":"2016","journal-title":"Wirel. Pers. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Jia, Z., Alaziz, M., Chi, X., Howard, R.E., Zhang, Y., Zhang, P., Trappe, W., Sivasubramaniam, A., and An, N. (2016, January 11\u201314). HB-Phone: A Bed-Mounted Geophone-Based Heartbeat Monitoring System. Proceedings of the ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Vienna, Austria.","DOI":"10.1109\/IPSN.2016.7460676"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1109\/JBHI.2017.2757530","article-title":"Detection of Snores Using Source Separation on an Emfit Signal","volume":"22","author":"Tenhunen","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.eml.2016.05.015","article-title":"Recent progress in flexible and stretchable piezoelectric devices for mechanical energy harvesting, sensing and actuation","volume":"9","author":"Dagdeviren","year":"2016","journal-title":"Extrem. Mech. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bu, N., Ueno, N., and Fukuda, O. (2007, January 22\u201326). Monitoring of Respiration and Heartbeat during Sleep using a Flexible Piezoelectric Film Sensor and Empirical Mode Decomposition. Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France.","DOI":"10.1109\/IEMBS.2007.4352551"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Fujita, T., Shiono, S., Kanda, K., Maenaka, K., Hamada, H., and Higuchi, K. (2012, January 5\u20137). Flexible Sensor for Human Monitoring System by Using P(VDF\/TrFE) Thin Film. Proceedings of the International Conference on Emerging Trends in Engineering and Technology, Himeji, Japan.","DOI":"10.1109\/ICETET.2012.22"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2655","DOI":"10.1109\/TBME.2013.2262150","article-title":"Intensity-Modulated Microbend Fiber Optic Sensor for Respiratory Monitoring and Gating During MRI","volume":"60","author":"Lau","year":"2013","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Fajkus, M., Nedoma, J., Martinek, R., Vasinek, V., Nazeran, H., and Siska, P. (2017). A non-invasive multichannel hybrid fiber-optic sensor system for vital sign monitoring. Sensors, 17.","DOI":"10.3390\/s17010111"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4567","DOI":"10.1109\/JLT.2017.2749499","article-title":"Compact and Low-Cost Optical Fiber Respiratory Monitoring Sensor Based on Intensity Interrogation","volume":"35","author":"Kam","year":"2017","journal-title":"J. Light. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Otis, S., Mezghani, N., and Abdulrazak, B. (2018, January 27\u201330). Comparative Study of Heart Rate Extraction Methods for a Novel Intelligent Mattress. Proceedings of the International Symposium on Signal, Image, Video and Communications (ISIVC), Rabat, Morocco.","DOI":"10.1109\/ISIVC.2018.8709083"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3282","DOI":"10.1109\/JSEN.2019.2894834","article-title":"Optical Fiber Sensor Based on Plastic Optical Fiber and Smartphone for Measurement of the Breathing Rate","volume":"19","author":"Aitkulov","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1414","DOI":"10.1109\/JBHI.2014.2361732","article-title":"Ballistocardiography and Seismocardiography: A Review of Recent Advances","volume":"19","author":"Inan","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2562","DOI":"10.1109\/TBME.2016.2640309","article-title":"A Novel Framework for Motion-Tolerant Instantaneous Heart Rate Estimation by Phase-Domain Multiview Dynamic Time Warping","volume":"64","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Luengo, D., Meltzer, D., and Trigano, T. (2018). An Efficient Method to Learn Overcomplete Multi-Scale Dictionaries of ECG Signals. Appl. Sci., 8.","DOI":"10.20944\/preprints201811.0199.v1"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lee, J.S., Chung, G.S., Beak, H.J., Lim, Y.G., Lee, J.S., Jeong, D.U., and Park, K.S. (2009, January 4\u20137). A new approach of unconstrained sleep monitoring and pulse arrival time extraction using PPG pillow and CC-ECG electrode system. Proceedings of the International Conference on Information Technology and Applications in Biomedicine, Larnaca, Cyprus.","DOI":"10.1109\/ITAB.2009.5394467"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Taebi, A., and Mansy, H.A. (2017, January 2). Grouping similar seismocardiographic signals using respiratory information. Proceedings of the IEEE Signal Processing in Medicine and Biology Symposium (SPMB), Philadelphia, PA, USA.","DOI":"10.1109\/SPMB.2017.8257053"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","article-title":"The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis","volume":"454","author":"Huang","year":"1998","journal-title":"Math. Phys. Eng. Sci."},{"key":"ref_25","unstructured":"Zhu, Y., Fook, V.F.S., Jianzhong, E.H., Maniyeri, J., Guan, C., Zhang, H., Jiliang, E.P., and Biswas, J. (2014, January 26\u201330). Heart rate estimation from FBG sensors using cepstrum analysis and sensor fusion. Proceedings of the International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, IL, USA."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1007\/s10015-014-0179-4","article-title":"A noninvasive heartbeat, respiration, and body movement monitoring system for neonates","volume":"19","author":"Nukaya","year":"2014","journal-title":"Artif. Life Robot."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3909","DOI":"10.1109\/JSEN.2015.2402652","article-title":"Recognition of nutrition intake using time-frequency decomposition in a wearable necklace using a piezoelectric sensor","volume":"15","author":"Alshurafa","year":"2015","journal-title":"IEEE Sens. J."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Chen, W., Zhou, Q., Cheng, X., Peng, M., and Xu, L. (2018, January 28\u201330). A Novel User Sleep Information Monitoring System Based on Non-contact Mattress. Proceedings of the International Conference on Telecommunications and Communication Engineering, Beijing, China.","DOI":"10.1145\/3291842.3291896"},{"key":"ref_29","unstructured":"Pei, J., Huang, D., and Jiang, Q. (2011, January 15\u201317). Optimal design on twin-T notch filter in electromagnetic exploration equipments. Proceedings of the International Conference on Electric Information and Control Engineering, Wuhan, China."},{"key":"ref_30","first-page":"36","article-title":"An Approach for ECG Feature Extraction using Daubechies 4 (DB4) Wavelet","volume":"96","author":"Mohamed","year":"2014","journal-title":"Int. J. Comput. Appl."},{"key":"ref_31","unstructured":"Wei, D., Bovik, A.C., and Evans, B.L. (1997, January 2\u20135). Generalized coiflets: A new family of orthonormal wavelets. Proceedings of the Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Vijayakumari, B., Devi, J.G., and Mathi, M.I. (2016, January 7\u20139). Analysis of noise removal in ECG signal using symlet wavelet. Proceedings of the International Conference on Computing Technologies and Intelligent Data Engineering, Kovilpatti, India.","DOI":"10.1109\/ICCTIDE.2016.7725336"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1016\/j.ymssp.2015.05.024","article-title":"A multi-resolution filtered-x LMS algorithm based on discrete wavelet transform for active noise control","volume":"66","author":"Qiu","year":"2016","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2913","DOI":"10.1109\/TIP.2010.2050723","article-title":"Simplified 2-D Cubic Spline Interpolation Scheme Using Direct Computation Algorithm","volume":"19","author":"Lin","year":"2010","journal-title":"IEEE Trans. Image Process."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1142\/S1793536909000047","article-title":"Ensemble empirical mode decomposition: A noise-assisted data analysis method","volume":"1","author":"Wu","year":"2009","journal-title":"Adv. Adapt. Data Anal."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/18\/3843\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T08:49:14Z","timestamp":1718873354000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/18\/3843"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,5]]},"references-count":35,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["s19183843"],"URL":"https:\/\/doi.org\/10.3390\/s19183843","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,9,5]]}}}