Chinese Journal of Electrical Engineering ›› 2023, Vol. 9 ›› Issue (1): 71-92.doi: 10.23919/CJEE.2023.000016
• Special Issue Papers • Previous Articles Next Articles
Yifeng Wang, Zheng Zhao, Jiangtao Li*
Received:2022-09-30
Revised:2023-02-07
Accepted:2023-03-10
Online:2023-03-25
Published:2023-04-06
Contact:
*E-mail: li_jiangtao@xjtu.edu.cn
About author:Yifeng Wang (Student member, IEEE) was born in Anhui Province, China, in 1995. He received the B.S. degree in Electrical Engineering and Its Automation from Xi'an Jiaotong University, Xi'an, China, 2017. He is currently pursuing the Ph.D. degree in Electrical Engineering with the Xi'an Jiaotong University, Xi'an, China. His main research interests include the non-contact measuring methods and analysis algorithms of human physiology signals.Supported by:Yifeng Wang, Zheng Zhao, Jiangtao Li. Current Status and Development Tendency of Wearable Cardiac Health Monitoring*[J]. Chinese Journal of Electrical Engineering, 2023, 9(1): 71-92.
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| [1] L Y Ma, Z W Wang, J Fan, et al.An essential introduction to the annual report on cardiovascular health and diseases in China (2021).Chinese General Practice, 2022, 25(27): 3331-3346. [2] G X Wang.Future challenges and coping strategies of population ageing in China.Governance, 2022, 10(1): 50. [3] C Y Liu, M C Yang, J N Di, et al.Wearable ECG: History, key technologies and future challenges.Chinese Journal of Biomedical Engineering, 2019, 38(6): 641-652. [4] W J Ma, H P Ma, Y H Wang, et al.2021 Medical quality report of cardiovascular diseases in China: An executive summary.Chinese Circulation Journal, 2021, 36(11): 1041-1064. [5] X Y Kong, B L Ai, Y M Kong, et al.Artificial intelligence: A key to relieve China’s insufficient and unequally-distributed medical resources.American Journal of Translational Research, 2019, 11(5): 2632. [6] C Fikar, P Hirsch.Home health care routing and scheduling: A review.Computers & Operations Research, 2017, 77(1): 86-95. [7] S Landers, E Madigan, B Leff, et al.The future of home health care: A strategic framework for optimizing value.Home Health Care Management & Practice, 2016, 28(4): 262-278. [8] T Ali, J Hussain, M B Amin, et al.The intelligent medical platform: A novel dialogue-based platform for health-care services.Computer, 2020, 53(2): 35-45. [9] E J Topol.High-performance medicine: The convergence of human and artificial intelligence.Nature Medicine, 2019, 25(1): 44-56. [10] A Y Hannun, P Rajpurkar, M Haghpanahi, et al.Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.Nature Medicine, 2019, 25(1): 65-69. [11] Z I Attia, S Kapa, F L Jimenez, et al.Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram.Nature Medicine, 2019, 25(1): 70-74. [12] S B Jordan, D Travis, R H Reid, et al.Battery-free multichannel digital ECG biotelemetry using UHF RFID techniques.IEEE International Conference on RFID, 30 April-02 May, 2013, Orlando, USA. IEEE, 2013: 16-22. [13] N J Holter.New method for heart studies: Continuous electrocardiography of active subjects over long periods is now practical.Science, 1961, 134(3486): 1214-1220. [14] C Gopalsamy, S Park, R Rajamanickam, et al.The wearable motherboard: The first generation of adaptive and responsive textile structures (ARTS) for medical applications.Virtual Reality, 1999, 4(3): 152-168. [15] I Starr, A J Rawson, H A Schroeder, et al.Studies on the estimation of cardiac output in man, and of abnormalities in cardiac function, from the heart's recoil and the blood's impacts: The Ballistocardiogram.The American Journal of Physiology, 1939, 127(1): 1-28. [16] B Bozhenko.Seismocardiography: A new method in the study of functional conditions of the heart.Terapevticheskii Arkhiv, 1961, 33(1): 55-64. [17] D Salerno, J Zanetti.Seismocardiography: A new technique for recording cardiac vibrations. Concept, method and initial observations.Journal of Cardiovascular Technology, 1990, 9(2): 111-118. [18] R S Crow, P Hannan, D Jacobs, et al.Relationship between seismocardiogram and echocardiogram for events in the cardiac cycle.The American Journal of Noninvasive Cardiology, 1994, 8(1): 39-46. [19] T Aoyagi.Pulse oximetry: Its invention, theory and future.Journal of Anesthesia, 2003, 17(4): 259-266. [20] Z D Walton, P A Kyriacou, D G Silverman, et al.Measuring venous oxygenation using the photoplethy- smograph waveform.Journal of Clinical Monitoring and Computing, 2010, 24(4): 295-303. [21] S P McGrath, K L Ryan, S M Wendelken, et al. Pulse oximeter plethysmographic waveform changes in awake, spontaneously breathing, hypovolemic volunteers.Anesthesia and Analgesia, 2011, 112(2): 368-374. [22] R H Thiele, D A Colquhoun, J Patrie, et al.Relationship between plethysmographic waveform changes and hemodynamic variables in anesthetized, mechanically ventilated patients undergoing continuous cardiac output monitoring.Journal of Cardiothoracic and Vascular Anesthesia, 2011, 25(6): 1044-1050. [23] A A Alian, K H Shelley.Photoplethysmography.Best Practice & Research Clinical Anaesthesiology, 2014, 28(1): 395-406. [24] D Yang, J Zhu, P Zhu.SpO2 and heart rate measurement with wearable watch based on PPG.IET International Conference on Biomedical Image and Signal Processing, 2015, Beijing. UK: IET, 2015: 1-5. [25] A A Iskandar, R Kolla, K Schilling, et al.A wearable 1-lead necklace ECG for continuous heart rate monitoring.IEEE 18th International Conference on e-Health Networking, Applications and Services, 14-16 September, 2016, Munich, Germany. IEEE, 2016: 1-4. [26] O E Santala, J A Lipponen, H Jäntti, et al.Necklace embedded electrocardiogram for the detection and diagnosis of atrial fibrillation.Clinical Cardiology, 2020, 44(5): 620-626. [27] S Leng, R S Tan, K T C Chai, et al. The electronic stethoscope.Biomedical Engineering Online, 2015, 14(66): 1-37. [28] Z Y Zhao, C Y Liu, Y W Li, et al.Noise rejection for wearable ECGs using modified frequency slice wavelet transform and convolutional neural networks.IEEE Access, 2019, 7(1): 34060-34067. [29] M D Rienzo, P Meriggi, F Rizzo, et al.A wearable system for the seismocardiogram assessment in daily life conditions.Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 30 August- 03 September, 2011, Boston, USA. IEEE, 2011: 4263-4266. [30] D D He, E S Winokur, C Sodini.An ear-worn continuous ballistocardiogram (BCG) sensor for cardiovascular monitoring.Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012, San Diego, USA. IEEE, 2012: 5030-5033. [31] C Pinto, D Pereira, J Ferreira-Coimbra, et al.A comparative study of electronic stethoscopes for cardiac auscultation.Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2017, Jeju, South Korea. IEEE, 2017: 2610-2613. [32] C M Yang, C Veiga, J J R Andina, et al. Using PPG signals and wearable devices for atrial fibrillation screening.IEEE Transactions on Industrial Electronics, 2019, 66(11): 8832-8842. [33] D Weiler, S O Villajuan, L Edkins.BioWatch: A wrist watch based signal acquisition system for physiology signals including blood pressure.36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014, Chicago. IEEE, 2014: 2286-2289. [34] L Wang, B P Lo, G Z Yang.Multichannel reflective PPG earpiece sensor with passive motion cancellation.IEEE Transactions on Biomedical Circuits and System, 2007, 1(4): 235-241. [35] D Wang, H Z Xu.Research progress on assessment and management of malignant fungating wounds.Chinese Nursing Management, 2018, 18(11): 1554-1558. [36] M Yin, R Tang, K Han, et al.Study on the feasibility of replacing the Ag/AgCl ECG electrode with a new ECG electrode.China Medical Devices, 2021, 36(1): 69-74. [37] Y M Chi, T P Jung, G Cauwenberghs.Dry-contact and noncontact biopotential electrodes: Methodological review.IEEE Reviews in Biomedical Engineering, 2010, 3(1): 106-119. [38] J H Lee, J Y Hwang, J Zhu, et al.Flexible conductive composite integrated with personal earphone for wireless, real-time monitoring of electrophysiological signs.ACS Applied Materials and Interfaces, 2018, 10(25): 21184. [39] H L Peng, J Q Liu, Y Z Dong, et al.Parylene-based flexible dry electrode for bioptential recording.Sensors and Actuators B: Chemical, 2016, 231(1): 1-11. [40] M J Zhu, H M Wang, S Li, et al.Flexible electrodes for in vivo and in vitro electrophysiology signal recording.Advanced Healthcare Materials, 2021, 10(17): e2100646. [41] Y P Huang, Y T Song, L Gou, et al.A novel wearable flexible dry electrode based on cowhide for ECG measurement.Biosensors, 2021, 11(4): 101-117. [42] R Z Lin, H J Kim, S Achavananthadith, et al.Digitally-embroidered liquid metal electronic textiles for wearable wireless systems.Nature Communications, 2022, 13(1): 2190-2200. [43] X Liang, H Li, J Dou, et al.Stable and biocompatible carbon nanotube ink mediated by silk protein for printed electronics.Advanced Materials, 2020, 32(31): e2000165. [44] A J Golparvar, M K Yapici.Electrooculography by wearable graphene textiles.IEEE Sensors Journal, 2018, 18(21): 8971-8978. [45] A Miyamoto, S Lee, N F Cooray, et al.Inflammation-free, gas-permeable, lightweight, stretchable on-skin electronics with nanomeshes.Nature Nanotechnology, 2017, 12(1): 907-913. [46] B Sun, R N McCay, S Goswami, et al. Gas-permeable, multifunctional on-skin electronics based on laser-induced porous graphene and sugar-templated elastomer sponges.Advanced Materials, 2018, 30(50): 1804327. [47] Y Xu, G Zhao, L Zhu, et al.Pencil-paper on-skin electronics.Proceedings of the National Academy of Sciences, 2020, 117(31): 18292-18301. [48] R J Prance, A Debray, T D Clark, et al.An ultra-low-noise electrical-potential probe for human-body scanning.Measurement Science & Technology, 2000, 11(3): 291-297. [49] T Sullivan, S Deiss, G Cauwenberghs.A low-noise, non-contact EEG/ECG sensor.Biomedical Circuits and Systems Conference, 2007, Montreal. IEEE, 2007: 154-157. [50] Y M Chi, N G Patrick, E Kang, et al.Wireless non-contact cardiac and neural monitoring.Wireless Health, 2010, San Diego. ACM, 2010: 15-23. [51] M Fatoorechi, J Parkinson, R J Prance, et al.A comparative study of electrical potential sensors and Ag/AgCl electrodes for characterizing spontaneous and event related electroencephalogram signals.Journal of Neuroscience Methods, 2015, 251(1): 7-16. [52] B Yang, Y Dong.Capacitive coupled non-contact electrodes and ECG signal acquisition.Chinese Journal of Scientific Instrument, 2015, 1(5): 114-120. [53] T W Wang, S F Lin.Negative impedance capacitive electrode for ECG sensing through fabric layer.IEEE Transactions on Instrumentation and Measurement, 2020, 70(1): 4002308. [54] J T Li, Y F Wang, C J Li, et al.Non-contact electrocardiogram measuring method based on capacitance coupling electrodes with ultra-high input impedance.Review of Scientific Instruments, 2022, 93(3): 034101. [55] Y Khan, M Garg, Q Gui, et al.Flexible hybrid electronics: Direct interfacing of soft and hard electronics for wearable health monitoring.Advanced Functional Materials, 2016, 26(47): 8764-8775. [56] L Ren, S J Xu, J Gao, et al.Fabrication of flexible microneedle array electrodes for wearable bio-signal recording.Sensors, 2018, 18(4): 1191. [57] S Choi, S I Han, D Jung, et al.Highly conductive, stretchable and biocompatible Ag-Au core-sheath nanowire composite for wearable and implantable bioelectronics.Nature Nanotechnology. 2018, 13(1): 1048. [58] Y M Chi, G Cauwenberghs.Wireless non-contact EEG/ECG electrodes for body sensor networks.International Conference on Body Sensor Networks, 2010, Singapore. IEEE, 2010: 297-301. [59] T Amirtahà, E S Brian, J B Andrew, et al.Recent advances in seismocardiography.Vibration, 2019, 2(1): 64-86. [60] G Guidoboni, L Sala, M Enayati, et al.Cardiovascular function and ballistocardiogram: A relationship interpreted via mathematical modeling.IEEE Transactions on Biomedical Engineering, 2019, 66(10): 2906-2917. [61] O T Inan, P F Migeotte, K S Park, et al.Ballistocardiography and seismocardiography: A review of recent advances.IEEE Journal of Biomedical and Health Informatics, 2015, 19(4): 1414-1427. [62] U Morbiducci, L Scalise, M D Melis, et al.Optical vibrocardiography: A novel tool for the optical monitoring of cardiac activity.Annals of Biomedical Engineering, 2007, 35(1): 45-58. [63] Z Y Xia, M H Shandhi, O T Inan, et al.Non-contact sensing of seismocardiogram signals using microwave doppler radar.IEEE Sensors Journal, 2018, 18(14): 5956-5964. [64] D Rai, H K Thakkar, S S Rajput, et al.A comprehensive review on seismocardiogram: Current advancements on acquisition, annotation, and applications.Mathematics, 2021, 9(18): 2243. [65] M J Tadi, E Lehtonen, A Saraste, et al.Gyrocardiography: A new non-invasive monitoring method for the assessment of cardiac mechanics and the estimation of hemodynamic variables.Scientific Reports, 2017, 7(1): 6823. [66] M J Tadi, J Teuho, E Lehtonen, et al.A novel dual gating approach using joint inertial sensors: Implications for cardiac PET imaging.Physics in Medicine & Biology, 2017, 62(20): 8080-8101. [67] M Anumukonda, S R Chowdhury.Heart sound sensing through MEMS microphone.Sensors for Everyday Life, 2016, 22(1): 121-134. [68] S A Fattah, N M Rahman, A Maksud, et al.Stethophone: Low-cost digital stethoscope for remote personalized healthcare.IEEE Global Humanitarian Technology Conference, 2017, San Jose. IEEE, 2017: 1-7. [69] L X Liu, W D Zhang, G J Zhang, et al.Package optimization of the cilium-type MEMS bionic vector hydrophone.IEEE Sensors Journal, 2014, 14(4): 1185-1192. [70] R Martinek, R Kahankova, J Nedoma, et al.Adaptive signal processing of fetal PCG recorded by interferometric sensor.Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications, 2017, Málaga. Switzerland: Springer, 2017: 235-243. [71] M Golberg, S Polani, N Ozana, et al.Remote optical stethoscope and optomyography sensing device.Society of Photo-Optical Instrumentation Engineers Bio-medical Optics, 2017, San Francisco. SPIE, 2017: 10077. [72] Y H Liu, J J S Norton, R Qazi, et al. Epidermal mechano-acoustic sensing electronics for cardiovascular diagnostics and human-machine interfaces.Science Advances, 2016, 2(11): e1601185. [73] H X Li, Y F Ren, G J Zhang, et al.Design of a high SNR electronic heart sound sensor based on a MEMS bionic hydrophone.AIP Advances, 2019, 9(1): 015005. [74] L J Nowak, K M Nowak.Sound differences between electronic and acoustic stethoscopes.Biomedical Engineering Online, 2018, 17(1): 104. [75] S Biswas, A K Gogoi.Design issues of piezoresistive MEMS accelerometer for an application specific medical diagnostic system.IETE Technical Review, 2016, 33(1): 11-16. [76] F L Hedayioglu, S S Mattos, L Moser, et al.Development of a tele-stethoscope and its application in paediatric cardiology.Indian Journal of Experimental Biology, 2007, 45(1): 86-92. [77] S C Duan, W D Wang, S Zhang, et al.A bionic MEMS electronic stethoscope with double-sided diaphragm packaging.IEEE Access, 2021, 9(1): 27122-27129. [78] C Xue, S Chen, W Zhang, et al.Design, fabrication, and preliminary characterization of a novel MEMS bionic vector hydrophone.Microelectronics Journal, 2007, 38(10): 1021-1026. [79] D Biswas, N Simões-Capela, C V Hoof, et al.Heart rate estimation from wrist-worn photoplethysmography: A review.IEEE Sensors Journal, 2019, 19(16): 6560-6570. [80] J Fine, K L Branan, A J Rodriguez, et al.Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring.Biosensors, 2021, 11(4): 126. [81] Q X Zhang, X Zeng, W C Hu, et al.A machine learning-empowered system for long-term motion-tolerant wearable monitoring of blood pressure and heart rate with ear-ECG/PPG. IEEE Access, 2017, 5(1): 10547-10561. [82] Ł Dziuda.Fiber-optic sensors for monitoring patient physiological parameters: A review of applicable technologies and relevance to use during magnetic resonance imaging procedures.Journal of Biomedical Optics, 2016, 20(1): 010901. [83] B H Tracey, E L Miller.Nonlocal means denoising of ECG signals.IEEE Transactions on Biomedical Engineering, 2012, 59(9): 2383-2386. [84] M Hossain, J Lázaro, Y Noh, et al.Denoising wearable armband ECG data using the variable frequency complex demodulation technique.Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020, Montreal. IEEE, 2020: 592-595. [85] C A Deledalle, V Duval, J Salmon.Nonlocal methods with shape-adaptive patches (NLM-SAP).Journal of Mathematical Imaging and Vision, 2012, 43(2): 103-120. [86] D V D Ville, M Kocher. Nonlocal means with dimensionality reduction and SURE-based parameter selection.IEEE Transactions on Image Processing, 2011, 20(1): 1732-1735. [87] S Poungponsri, X H Yu.An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks.Neurocomputing, 2013, 117(1): 206-213. [88] A Galli, C Narduzzi, G Giorgi.Measuring heart rate during physical exercise by subspace decomposition and Kalman smoothing.IEEE Transactions on Instrumentation and Measurement, 2018, 67(5): 1102-1110. [89] M R Ram, K V Madhav, E H Krishna, et al.A novel approach for motion artifact reduction in PPG signals based on AS-LMS adaptive filter.IEEE Transactions on Instrumentation and Measurement, 2012, 61(5): 1445. [90] S Fallet, J M Vesin.Robust heart rate estimation using wrist-type photoplethysmographic signals during physical exercise: An approach based on adaptive filtering.Physiological Measurement, 2017, 38(2): 155-170. [91] K Xu, X Y Jiang, S J Lin, et al.Stochastic modeling based nonlinear Bayesian filtering for photoplethysmography denoising in wearable devices.IEEE Transactions on Industrial Informatics, 2020, 16(11): 7219-7230. [92] R Sameni, C Jutten.A nonlinear Bayesian filtering framework for ECG denoising.IEEE Transactions on Biomedical Engineering, 2007, 54(12): 2172-2185. [93] B Lee, J H Han, H J Baek, et al.Improved elimination of motion artifacts from a photoplethysmographic signal using a Kalman smoother with simultaneous accelero- metry.Physiological Measurement, 2010, 31(12): 1585. [94] R W Wijshoff, M Mischi, R M Aarts.Reduction of periodic motion artifacts in photoplethysmography.IEEE Transactions on Biomedical Engineering, 2017, 64(1): 196-207. [95] D D Giustina, M Riva, F Belloni, et al.Embedding a multichannel environmental noise cancellation algorithm into an electronic stethoscope.International Journal of Circuits,System,and Signal Processing, 2011, 2(5): 184. [96] S S Chowdhury, R Hyder, S B Hafiz, et al.Real-time robust heart rate estimation from wrist-type PPG signals using multiple reference adaptive noise cancellation.IEEE Journal of Biomedical and Health Informatics, 2018, 22(2): 450-459. [97] M B Mashhadi, E Asadi, M Eskandari, et al.Heart rate tracking using wrist-type photoplethysmographic (PPG) signals during physical exercise with simultaneous accelerometry.IEEE Signal Processing Letters, 2016, 23(2): 227-231. [98] Y L Ye, Y F Cheng, W W He, et al.Combining nonlinear adaptive filtering and signal decomposition for motion artifact removal in wearable photoplethysmography. IEEE Sensors Journal, 2016, 16(19): 7133-7141. [99] Y L Ye, W W He, Y F Cheng, et al.A robust random forest-based approach for heart rate monitoring using photoplethysmography signal contaminated by intense motion artifacts.Sensors, 2017, 17(2): 385. [100] W Jenkal, R Latif, A Toumanari, et al.An efficient algorithm of ECG signal denoising using the adaptive dual threshold filter and the discrete wavelet transform.Biocybernetics and Biomedical Engineering, 2016, 36(3): 499-508. [101] A Awal, S S Mostafa, M Ahmad, et al.An adaptive level dependent wavelet thresholding for ECG denoising.Biocybernetics and Biomedical Engineering, 2014, 34(4): 238-249. [102] D Gradolewski, G Redlarski.Wavelet-based denoising method for real phonocardiography signal recorded by mobile devices in noisy environment.Computers in Biology and Medicine, 2014, 52(1): 119-129. [103] F Wang, Z Ji.Application of the dual-tree complex wavelet transform in biomedical signal denoising.Bio-Medical Materials and Engineering, 2014, 24(1): 109-115. [104] Z Y Wang, J J Zhu, T H Yan, et al.A new modified wavelet-based ECG denoising.Computer Assisted Surgery, 2019, 24(S1): 174-183. [105] T T Cai, B W Silverman.Incorporating information on neighboring coefficients into wavelet estimation.Indian Journal of Statistics, 2001, 63(2): 127-148. [106] X Tan, X X Chen, X Y Hu, et al.EMD-based electrocardiogram delineation for a wearable low-power ECG monitoring device.Canadian Journal of Electrical and Computer Engineering, 2014, 37(4): 212. [107] S Pal, M Mitra.Empirical mode decomposition-based ECG enhancement and QRS detection.Computers in Biology and Medicine, 2012, 42(1): 83-92. [108] J Lee, D D McManus, S Merchant, et al. Automatic motion and noise artifact detection in Holter ECG data using empirical mode decomposition and statistical approaches.IEEE Transactions on Biomedical Engineering, 2012, 59(6): 1499-1506. [109] A Kabir, C Shahnaz.Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains.Biomedical Signal Processing and Control, 2012, 7(5): 481-489. [110] Z H Wu, N E Huang.Ensemble empirical mode decomposition: A noise-assisted data analysis method.Advances in Adaptive Data Analysis, 2009, 1(1): 1-41. [111] P Singh, S Shahnawazuddin, G Pradhan.Significance of modified empirical mode decomposition for ECG denoising.Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2017, Jeju. IEEE, 2017: 2956. [112] E Gokgoz, A Subasi.Effect of multiscale PCA de-noising on EMG signal classification for diagnosis of neuromuscular disorders.Journal of Medical Systems, 2014, 38(4): 31. [113] M P S Chawla. PCA and ICA processing methods for removal of artifacts and noise in electrocardiograms: A survey and comparison.Applied Soft Computing, 2011, 11(2): 2216-2226. [114] N Jain, D K Shakya.Denoising baseline wander noise from electrocardiogram signal using fast ICA with multiple adjustments.International Journal of Computer Applications, 2014, 99(2): 34-39. [115] X Chen, Q Chen, Y Zhang, et al.A novel EEMD-CCA approach to removing muscle artifacts for pervasive EEG.IEEE Sensors Journal, 2019, 19(19): 8420-8431. [116] S Calcagno, F L Foresta, M Versaci.Independent component analysis and discrete wavelet transform for artifact removal in biomedical signal processing.American Journal of Applied Sciences, 2014, 11(1): 57. [117] J Kevrica, A Subasi.Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system.Biomedical Signal Processing and Control, 2017, 31(1): 398-406. [118] M Wasimuddin, K Elleithy, A S Abuzneid, et al.Stages-based ECG signal analysis from traditional signal processing to machine learning approaches: A survey.IEEE Access, 2020, 8(1): 177782-177803. [119] Z Y Xu, Y F Wang, X C Tian, et al.Motion artifact removal based on stationary wavelet transform and adaptive filtering for wearable ECG monitoring.Lecture Notes in Electrical Engineering, 2022, 889(1): 683-693. [120] O Lahdenoja, T Hurnanen, Z Iftikhar, et al.Atrial fibrillation detection via accelerometer and gyroscope of a smartphone.IEEE Journal of Biomedical and Health Informatics, 2018, 22(1): 108-118. [121] M Elgendi, C Menon.Assessing anxiety disorders using wearable devices: Challenges and future directions.Brain Sciences, 2019, 9(3): 50. [122] S C Mukhopadhyay.Wearable sensors for human activity monitoring: A review.IEEE Sensors Journal, 2015, 15(3): 1321-1329. [123] Y N Zhang, R G Weaver, B Armstrong, et al.Validity of wrist-worn photoplethysmography devices to measure heart rate: A systematic review and meta-analysis.Journal of Sports Sciences, 2020, 38(17): 1-13. [124] V P Rachim, W Y Chung.Wearable-band type visible-near infrared optical biosensor for non-invasive blood glucose monitoring.Sensors and Actuators B: Chemical, 2019, 286(1): 173-180. [125] K Zhao, Y F Li, G X Wang, et al.A robust QRS detection and accurate R-peak identification algorithm for wearable ECG sensors.Science China Information Sciences, 2021, 64(1): 182401. [126] M Jacobsen, T A Dembek, A P Ziakos, et al.Reliable detection of atrial fibrillation with a medical wearable during inpatient conditions.Sensors, 2020, 20(19): 5517. [127] K Georgiou, A V Larentzakis, N N Khamis, et al.Can wearable devices accurately measure heart rate variability? A systematic review. Folia Medica, 2018, 60(1): 7-20. [128] M M Baig, H G Hosseini, A A Moqeem, et al.A systematic review of wearable patient monitoring systems: Current challenges and opportunities for clinical adoption.Journal of Medical Systems, 2017, 41(7): 115. |
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