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2018 | OriginalPaper | Chapter

Physiological Signals Fusion Oriented to Diagnosis - A Review

Authors : Y. F. Uribe, K. C. Alvarez-Uribe, D. H. Peluffo-Ordoñez, M. A. Becerra

Published in: Advances in Computing

Publisher: Springer International Publishing

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Abstract

The analysis of physiological signals is widely used for the development of diagnosis support tools in medicine, and it is currently an open research field. The use of multiple signals or physiological measures as a whole has been carried out using data fusion techniques commonly known as multimodal fusion, which has demonstrated its ability to improve the accuracy of diagnostic care systems. This paper presents a review of state of the art, putting in relief the main techniques, challenges, gaps, advantages, disadvantages, and practical considerations of data fusion applied to the analysis of physiological signals oriented to diagnosis decision support. Also, physiological signals data fusion architecture oriented to diagnosis is proposed.

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Literature
1.
go back to reference Clifford, G.D., Long, W.J., Moody, G.B., Szolovits, P.: Robust parameter extraction for decision support using multimodal intensive care data. Philos. Trans. A. Math. Phys. Eng. Sci. 367(1887), 411–429 (2009)CrossRef Clifford, G.D., Long, W.J., Moody, G.B., Szolovits, P.: Robust parameter extraction for decision support using multimodal intensive care data. Philos. Trans. A. Math. Phys. Eng. Sci. 367(1887), 411–429 (2009)CrossRef
2.
go back to reference Mollakazemi, M.J., Atyabi, S.A., Ghaffari, A.: Heart beat detection using a multimodal data coupling method. Physiol. Meas. 36(8), 1729–1742 (2015)CrossRef Mollakazemi, M.J., Atyabi, S.A., Ghaffari, A.: Heart beat detection using a multimodal data coupling method. Physiol. Meas. 36(8), 1729–1742 (2015)CrossRef
3.
go back to reference Soleymani, M., Lichtenauer, J., Pun, T., Pantic, M.: A multimodal database for affect recognition and implicit tagging. IEEE Trans. Affect. Comput. 3(1), 42–55 (2012)CrossRef Soleymani, M., Lichtenauer, J., Pun, T., Pantic, M.: A multimodal database for affect recognition and implicit tagging. IEEE Trans. Affect. Comput. 3(1), 42–55 (2012)CrossRef
4.
go back to reference Begum, S., Barua, S., Filla, R., Ahmed, M.U.: Classification of physiological signals for wheel loader operators using multi-scale entropy analysis and case-based reasoning. Expert Syst. Appl. 41(2), 295–305 (2014)CrossRef Begum, S., Barua, S., Filla, R., Ahmed, M.U.: Classification of physiological signals for wheel loader operators using multi-scale entropy analysis and case-based reasoning. Expert Syst. Appl. 41(2), 295–305 (2014)CrossRef
5.
go back to reference Pantelopoulos, A., Bourbakis, N.: SPN-model based simulation of a wearable health monitoring system. In: Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society Engineering the Future of Biomedicine, EMBC 2009, pp. 320–323 (2009) Pantelopoulos, A., Bourbakis, N.: SPN-model based simulation of a wearable health monitoring system. In: Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society Engineering the Future of Biomedicine, EMBC 2009, pp. 320–323 (2009)
6.
go back to reference Ryoo, H.C., Sun, H.H., Hrebien, L.: Two compartment fusion system designed for physiological state monitoring. In: Annual Reports Res. React. Inst., pp. 2224–2227 (2001) Ryoo, H.C., Sun, H.H., Hrebien, L.: Two compartment fusion system designed for physiological state monitoring. In: Annual Reports Res. React. Inst., pp. 2224–2227 (2001)
7.
go back to reference Li, Q., Mark, R.G., Clifford, G.D.: Artificial arterial blood pressure artifact models and an evaluation of a robust blood pressure and heart rate estimator. Biomed. Eng. Online 15, 1–15 (2009) Li, Q., Mark, R.G., Clifford, G.D.: Artificial arterial blood pressure artifact models and an evaluation of a robust blood pressure and heart rate estimator. Biomed. Eng. Online 15, 1–15 (2009)
8.
go back to reference Galeotti, L., Scully, C.G., Vicente, J., Johannesen, L., Strauss, D.G.: Robust algorithm to locate heart beats from multiple physiological waveforms by individual signal detector voting. Physiol. Meas. 36(8), 1705–1716 (2015)CrossRef Galeotti, L., Scully, C.G., Vicente, J., Johannesen, L., Strauss, D.G.: Robust algorithm to locate heart beats from multiple physiological waveforms by individual signal detector voting. Physiol. Meas. 36(8), 1705–1716 (2015)CrossRef
9.
go back to reference Tsiliki, G., Kossida, S.: Fusion methodologies for biomedical data. J. Proteomics 74(12), 2774–2785 (2011)CrossRef Tsiliki, G., Kossida, S.: Fusion methodologies for biomedical data. J. Proteomics 74(12), 2774–2785 (2011)CrossRef
10.
go back to reference Setz, C., Schumm, J., Lorenz, C., Arnrich, B., Tröster, G.: Using ensemble classifier systems for handling missing data in emotion recognition from physiology: one step towards a practical system. In: Affective Computing and Intelligent Interaction (ACII 2009), pp. 1–8 (2009) Setz, C., Schumm, J., Lorenz, C., Arnrich, B., Tröster, G.: Using ensemble classifier systems for handling missing data in emotion recognition from physiology: one step towards a practical system. In: Affective Computing and Intelligent Interaction (ACII 2009), pp. 1–8 (2009)
11.
go back to reference Castanedo, F.: A review of data fusion techniques. Sci. World J. 2013, 704504 (2013)CrossRef Castanedo, F.: A review of data fusion techniques. Sci. World J. 2013, 704504 (2013)CrossRef
12.
go back to reference Patil, R.: Digital signal preservation approaches of archived biomedical paper records - a review. In: 5th International Conference on Wireless Networks and Embedded Systems, WECON 2016, pp. 13–16 (2016) Patil, R.: Digital signal preservation approaches of archived biomedical paper records - a review. In: 5th International Conference on Wireless Networks and Embedded Systems, WECON 2016, pp. 13–16 (2016)
13.
go back to reference Liu, T., Si, Y., Wen, D., Zang, M., Lang, L.: Dictionary learning for VQ feature extraction in ECG beats classification. Expert Syst. Appl. 53, 129–137 (2016)CrossRef Liu, T., Si, Y., Wen, D., Zang, M., Lang, L.: Dictionary learning for VQ feature extraction in ECG beats classification. Expert Syst. Appl. 53, 129–137 (2016)CrossRef
14.
go back to reference Alvarez-Estevez, D., Moret-Bonillo, V.: Spectral heart rate variability analysis using the heart timing signal for the screening of the sleep apnea–hypopnea syndrome. Comput. Biol. Med. 71, 14–23 (2016)CrossRef Alvarez-Estevez, D., Moret-Bonillo, V.: Spectral heart rate variability analysis using the heart timing signal for the screening of the sleep apnea–hypopnea syndrome. Comput. Biol. Med. 71, 14–23 (2016)CrossRef
15.
go back to reference Liu, Q., Chen, Y.F., Fan, S.Z., Abbod, M.F., Shieh, J.S.: A comparison of five different algorithms for EEG signal analysis in artifacts rejection for monitoring depth of anesthesia. Biomed. Sig. Process. Control 25, 24–34 (2016)CrossRef Liu, Q., Chen, Y.F., Fan, S.Z., Abbod, M.F., Shieh, J.S.: A comparison of five different algorithms for EEG signal analysis in artifacts rejection for monitoring depth of anesthesia. Biomed. Sig. Process. Control 25, 24–34 (2016)CrossRef
16.
go back to reference Mack, D.J., Schönle, P.: An EOG-based, head-mounted eye tracker with 1 kHz sampling rate. In: IEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS, pp. 7–10 (2015) Mack, D.J., Schönle, P.: An EOG-based, head-mounted eye tracker with 1 kHz sampling rate. In: IEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS, pp. 7–10 (2015)
17.
go back to reference Khan, M., et al.: Analysing the effects of cold, normal, and warm digits on transmittance pulse oximetry. Biomed. Sig. Process. Control 26, 34–41 (2016)CrossRef Khan, M., et al.: Analysing the effects of cold, normal, and warm digits on transmittance pulse oximetry. Biomed. Sig. Process. Control 26, 34–41 (2016)CrossRef
18.
go back to reference Janik, P., Janik, M.A., Wróbel, Z.: Integrated micro power frequency breath detector. Sens. Actuators A Phys. 239, 79–89 (2016)CrossRef Janik, P., Janik, M.A., Wróbel, Z.: Integrated micro power frequency breath detector. Sens. Actuators A Phys. 239, 79–89 (2016)CrossRef
20.
go back to reference Francisco, J., et al.: Changes in the severity of aortic regurgitation at peak effort during exercise ☆. Int. J. Cardiol. 228, 145–148 (2017)CrossRef Francisco, J., et al.: Changes in the severity of aortic regurgitation at peak effort during exercise ☆. Int. J. Cardiol. 228, 145–148 (2017)CrossRef
21.
go back to reference Chuiko, G.P., Dvornik, O.V., Shyian, S.I., Baganov, Y.A.: A new age-related model for blood stroke volume. Comput. Biol. Med. 79(Oct), 144–148 (2016)CrossRef Chuiko, G.P., Dvornik, O.V., Shyian, S.I., Baganov, Y.A.: A new age-related model for blood stroke volume. Comput. Biol. Med. 79(Oct), 144–148 (2016)CrossRef
22.
go back to reference Lorenzi, P., Rao, R., Romano, G., Kita, A., Irrera, F.: Mobile devices for the real-time detection of specific human motion disorders. IEEE Sens. J. 16(23), 8220–8227 (2016) Lorenzi, P., Rao, R., Romano, G., Kita, A., Irrera, F.: Mobile devices for the real-time detection of specific human motion disorders. IEEE Sens. J. 16(23), 8220–8227 (2016)
23.
go back to reference Takaura, K., Tsuchiya, N., Fujii, N.: Frequency-dependent spatiotemporal profiles of visual responses recorded with subdural ECoG electrodes in awake monkeys: differences between high- and low-frequency activity. NeuroImage 124, 557–572 (2016)CrossRef Takaura, K., Tsuchiya, N., Fujii, N.: Frequency-dependent spatiotemporal profiles of visual responses recorded with subdural ECoG electrodes in awake monkeys: differences between high- and low-frequency activity. NeuroImage 124, 557–572 (2016)CrossRef
24.
go back to reference Antelis, J.M., Gudi, B., Eduardo, L., Sanchez-ante, G., Sossa, H.: Dendrite morphological neural networks for motor task recognition from electroencephalographic signals. Biomed. Sig. Process. Control 44, 12–24 (2018)CrossRef Antelis, J.M., Gudi, B., Eduardo, L., Sanchez-ante, G., Sossa, H.: Dendrite morphological neural networks for motor task recognition from electroencephalographic signals. Biomed. Sig. Process. Control 44, 12–24 (2018)CrossRef
26.
go back to reference Kaur, H., Rajni, R.: On the detection of cardiac arrhythmia with principal. Wirel. Pers. Commun. 97(4), 5495–5509 (2017)CrossRef Kaur, H., Rajni, R.: On the detection of cardiac arrhythmia with principal. Wirel. Pers. Commun. 97(4), 5495–5509 (2017)CrossRef
27.
go back to reference Rajesh, K.N.V.P.S., Dhuli, R.: Biomedical signal processing and control classification of imbalanced ECG beats using re-sampling techniques and AdaBoost ensemble classifier. Biomed. Sig. Process. Control 41, 242–254 (2018)CrossRef Rajesh, K.N.V.P.S., Dhuli, R.: Biomedical signal processing and control classification of imbalanced ECG beats using re-sampling techniques and AdaBoost ensemble classifier. Biomed. Sig. Process. Control 41, 242–254 (2018)CrossRef
28.
go back to reference Mulam, H.: Optimized feature mapping for eye movement recognition using electrooculogram signals. In: 8th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2017 (2017) Mulam, H.: Optimized feature mapping for eye movement recognition using electrooculogram signals. In: 8th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2017 (2017)
29.
go back to reference Lv, Z., Zhang, C., Zhou, B., Gao, X., Wu, X.: Design and implementation of an eye gesture perception system based on electrooculography. Expert Syst. Appl. 91, 310–321 (2018)CrossRef Lv, Z., Zhang, C., Zhou, B., Gao, X., Wu, X.: Design and implementation of an eye gesture perception system based on electrooculography. Expert Syst. Appl. 91, 310–321 (2018)CrossRef
30.
go back to reference Young, A.J., Kuiken, T.A., Hargrove, L.J.: Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses. J. Neural Eng. 11(5), 56021 (2014)CrossRef Young, A.J., Kuiken, T.A., Hargrove, L.J.: Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses. J. Neural Eng. 11(5), 56021 (2014)CrossRef
31.
go back to reference Kaur, A., Agarwal, R., Kumar, A.: Adaptive threshold method for peak detection of surface electromyography signal from around shoulder muscles. J. Appl. Stat. 4763, 714–726 (2018)MathSciNetCrossRef Kaur, A., Agarwal, R., Kumar, A.: Adaptive threshold method for peak detection of surface electromyography signal from around shoulder muscles. J. Appl. Stat. 4763, 714–726 (2018)MathSciNetCrossRef
32.
go back to reference Khurana, V., Kumar, P., Saini, R., Roy, P.P.: ScienceDirect EEG based word familiarity using features and frequency bands combination Action editor: Ning Zhong. Cogn. Syst. Res. 49, 33–48 (2018)CrossRef Khurana, V., Kumar, P., Saini, R., Roy, P.P.: ScienceDirect EEG based word familiarity using features and frequency bands combination Action editor: Ning Zhong. Cogn. Syst. Res. 49, 33–48 (2018)CrossRef
33.
go back to reference Koelstra, S.: Deap: a database for emotion analysis; using physiological signals. IEEE Trans. Affect. Comput. 3(1), 18–31 (2012)CrossRef Koelstra, S.: Deap: a database for emotion analysis; using physiological signals. IEEE Trans. Affect. Comput. 3(1), 18–31 (2012)CrossRef
34.
go back to reference Degenhart, A.D., Hiremath, S.V., Yang, Y.: Remapping cortical modulation for electrocorticographic brain–computer interfaces: a somatotopy-based approach in individuals with upper-limb paralysis. J. Neural Eng. 15(2), 026021 (2018)CrossRef Degenhart, A.D., Hiremath, S.V., Yang, Y.: Remapping cortical modulation for electrocorticographic brain–computer interfaces: a somatotopy-based approach in individuals with upper-limb paralysis. J. Neural Eng. 15(2), 026021 (2018)CrossRef
35.
go back to reference Ravan, M.: Beamspace fast fully adaptive brain source localization for limited data sequences. Inverse Probl. 33(5), 055021 (2017)MathSciNetCrossRef Ravan, M.: Beamspace fast fully adaptive brain source localization for limited data sequences. Inverse Probl. 33(5), 055021 (2017)MathSciNetCrossRef
36.
go back to reference Alonso-ar, M.A., Ibarra-hern, R.F., Cruz-guti, A., Licona-ch, A.L., Villarreal-reyes, S.: Design and evaluation of a parametric model for cardiac sounds. Comput. Biol. Med. 89(Aug), 170–180 (2017) Alonso-ar, M.A., Ibarra-hern, R.F., Cruz-guti, A., Licona-ch, A.L., Villarreal-reyes, S.: Design and evaluation of a parametric model for cardiac sounds. Comput. Biol. Med. 89(Aug), 170–180 (2017)
37.
go back to reference Babu, K.A., Ramkumar, B., Manikandan, M.S.: Real-time detection of S2 sound using simultaneous recording of PCG and PPG. In: IEEE Region 10 Annual International Conference, pp. 1475–1480 (2017) Babu, K.A., Ramkumar, B., Manikandan, M.S.: Real-time detection of S2 sound using simultaneous recording of PCG and PPG. In: IEEE Region 10 Annual International Conference, pp. 1475–1480 (2017)
38.
go back to reference Prabha, A., Trivedi, A., Kumar, A.A., Kumar, C.S.: Automated system for obstructive sleep apnea detection using heart rate variability and respiratory rate variability. In: International Conference on Advances in Computing, pp. 1303–1307 (2017) Prabha, A., Trivedi, A., Kumar, A.A., Kumar, C.S.: Automated system for obstructive sleep apnea detection using heart rate variability and respiratory rate variability. In: International Conference on Advances in Computing, pp. 1303–1307 (2017)
39.
go back to reference Lee, H., Chung, H., Ko, H., Lee, J.: Wearable multichannel photoplethysmography framework for heart rate monitoring during intensive exercise. IEEE Sens. J. 18(7), 2983–2993 (2018)CrossRef Lee, H., Chung, H., Ko, H., Lee, J.: Wearable multichannel photoplethysmography framework for heart rate monitoring during intensive exercise. IEEE Sens. J. 18(7), 2983–2993 (2018)CrossRef
40.
go back to reference Oliveira, C.C., Machado Da Silva, J.: A fuzzy logic approach for highly dependable medical wearable systems. In: Proceedings of the 2015 IEEE 20th International Mixed-Signal Testing Workshop, IMSTW 2015 (2015) Oliveira, C.C., Machado Da Silva, J.: A fuzzy logic approach for highly dependable medical wearable systems. In: Proceedings of the 2015 IEEE 20th International Mixed-Signal Testing Workshop, IMSTW 2015 (2015)
41.
go back to reference Li, J., et al.: Design of a continuous blood pressure measurement system based on pulse wave and ECG signals. IEEE J. Transl. Eng. Heal. Med. 6(Jan), 1–14 (2018) Li, J., et al.: Design of a continuous blood pressure measurement system based on pulse wave and ECG signals. IEEE J. Transl. Eng. Heal. Med. 6(Jan), 1–14 (2018)
42.
go back to reference Conte, R., Longo, M., Marano, S., Matta, V., Elettrica, I., Dea, A.: Fusing evidences from intracranial pressure data using dempster-shafer theory. In: 15th International Conference on Digital Signal Processing, pp. 159–162 (2007) Conte, R., Longo, M., Marano, S., Matta, V., Elettrica, I., Dea, A.: Fusing evidences from intracranial pressure data using dempster-shafer theory. In: 15th International Conference on Digital Signal Processing, pp. 159–162 (2007)
43.
go back to reference Al-Saud, K., Mahmuddin, M., Mohamed, A.: Wireless body area sensor networks signal processing and communication framework: survey on sensing, communication technologies, delivery and feedback. J. Comput. Sci. 8(1), 121–132 (2012)CrossRef Al-Saud, K., Mahmuddin, M., Mohamed, A.: Wireless body area sensor networks signal processing and communication framework: survey on sensing, communication technologies, delivery and feedback. J. Comput. Sci. 8(1), 121–132 (2012)CrossRef
44.
go back to reference Torniainen, J., Cowley, B., Henelius, A., Lukander, K., Pakarinen, S.: Feasibility of an electrodermal activity ring prototype as a research tool. In: IEEE Engineering in Medicine and Biology Society, EMBS, pp. 6433–6436 (2015) Torniainen, J., Cowley, B., Henelius, A., Lukander, K., Pakarinen, S.: Feasibility of an electrodermal activity ring prototype as a research tool. In: IEEE Engineering in Medicine and Biology Society, EMBS, pp. 6433–6436 (2015)
45.
go back to reference Muller, J., et al.: Repeatability of measurements of galvanic skin response – a pilot study. Open Complement. Med. J. 5(1), 11–17 (2013)MathSciNetCrossRef Muller, J., et al.: Repeatability of measurements of galvanic skin response – a pilot study. Open Complement. Med. J. 5(1), 11–17 (2013)MathSciNetCrossRef
46.
go back to reference Wang, Y.-Z., et al.: Nonenzymatic electrochemiluminescence glucose sensor based on quenching effect on luminol using attapulgite–TiO2. Sens. Actuators B Chem. 230, 449–455 (2016)CrossRef Wang, Y.-Z., et al.: Nonenzymatic electrochemiluminescence glucose sensor based on quenching effect on luminol using attapulgite–TiO2. Sens. Actuators B Chem. 230, 449–455 (2016)CrossRef
47.
go back to reference Belgacem, N., Fournier, R., Nait-Ali, A., Bereksi-Reguig, F.: A novel biometric authentication approach using ECG and EMG signals. J. Med. Eng. Technol. 39(4), 226–238 (2015)CrossRef Belgacem, N., Fournier, R., Nait-Ali, A., Bereksi-Reguig, F.: A novel biometric authentication approach using ECG and EMG signals. J. Med. Eng. Technol. 39(4), 226–238 (2015)CrossRef
48.
go back to reference Kume, D., Akahoshi, S., Yamagata, T., Wakimoto, T., Nagao, N.: Does voluntary hypoventilation during exercise impact EMG activity? SpringerPlus 5(1), 149 (2016)CrossRef Kume, D., Akahoshi, S., Yamagata, T., Wakimoto, T., Nagao, N.: Does voluntary hypoventilation during exercise impact EMG activity? SpringerPlus 5(1), 149 (2016)CrossRef
49.
go back to reference Stuart, S., Galna, B., Lord, S., Rochester, L.: A protocol to examine vision and gait in Parkinson’s disease: impact of cognition and response to visual cues [version 2; referees: 2 approved] Referee Status, pp. 1–18 (2016) Stuart, S., Galna, B., Lord, S., Rochester, L.: A protocol to examine vision and gait in Parkinson’s disease: impact of cognition and response to visual cues [version 2; referees: 2 approved] Referee Status, pp. 1–18 (2016)
50.
go back to reference Abdat, F., Maaoui, C., Pruski, A.: Bimodal system for emotion recognition from facial expressions and physiological signals using feature-level fusion. In: Symposium on Computer Modeling and Simulation, pp. 24–29 (2011) Abdat, F., Maaoui, C., Pruski, A.: Bimodal system for emotion recognition from facial expressions and physiological signals using feature-level fusion. In: Symposium on Computer Modeling and Simulation, pp. 24–29 (2011)
52.
go back to reference Verma, G.K., Tiwary, U.S.: Multimodal fusion framework: a multiresolution approach for emotion classification and recognition from physiological signals. NeuroImage 102(P1), 162–172 (2014)CrossRef Verma, G.K., Tiwary, U.S.: Multimodal fusion framework: a multiresolution approach for emotion classification and recognition from physiological signals. NeuroImage 102(P1), 162–172 (2014)CrossRef
53.
go back to reference Soria-Frisch, A., Riera, A., Dunne, S.: Fusion operators for multi-modal biometric authentication based on physiological signals. In: IEEE International Conference on Fuzzy Syst, FUZZ 2010, pp. 18–23 (2010) Soria-Frisch, A., Riera, A., Dunne, S.: Fusion operators for multi-modal biometric authentication based on physiological signals. In: IEEE International Conference on Fuzzy Syst, FUZZ 2010, pp. 18–23 (2010)
54.
go back to reference Khaleghi, B., Khamis, A., Karray, F.O., Razavi, S.N.: Multisensor data fusion: a review of the state of the art. Inf. Fusion 14(1), 28–44 (2013)CrossRef Khaleghi, B., Khamis, A., Karray, F.O., Razavi, S.N.: Multisensor data fusion: a review of the state of the art. Inf. Fusion 14(1), 28–44 (2013)CrossRef
55.
go back to reference Jeon, T., Yu, J., Pedrycz, W., Jeon, M., Lee, B., Lee, B.: Robust detection of heartbeats using association models from blood pressure and EEG signals. Biomed. Eng. Online 15, 1–14 (2016)CrossRef Jeon, T., Yu, J., Pedrycz, W., Jeon, M., Lee, B., Lee, B.: Robust detection of heartbeats using association models from blood pressure and EEG signals. Biomed. Eng. Online 15, 1–14 (2016)CrossRef
56.
go back to reference Lahat, D., Adali, T., Jutten, C.: Multimodal data fusion: an overview of methods, challenges, and prospects. Proc. IEEE 103(9), 1449–1477 (2015)CrossRef Lahat, D., Adali, T., Jutten, C.: Multimodal data fusion: an overview of methods, challenges, and prospects. Proc. IEEE 103(9), 1449–1477 (2015)CrossRef
57.
go back to reference Van Gerven, M.A.J., Taal, B.G., Lucas, P.J.F.: Dynamic Bayesian networks as prognostic models for clinical patient management. J. Biomed. Inform. 41, 515–529 (2008)CrossRef Van Gerven, M.A.J., Taal, B.G., Lucas, P.J.F.: Dynamic Bayesian networks as prognostic models for clinical patient management. J. Biomed. Inform. 41, 515–529 (2008)CrossRef
58.
go back to reference Gravina, R., Alinia, P., Ghasemzadeh, H., Fortino, G.: Multi-sensor fusion in body sensor networks: state-of-the-art and research challenges. Inf. Fusion 35, 68–80 (2017)CrossRef Gravina, R., Alinia, P., Ghasemzadeh, H., Fortino, G.: Multi-sensor fusion in body sensor networks: state-of-the-art and research challenges. Inf. Fusion 35, 68–80 (2017)CrossRef
59.
go back to reference Ringeval, F., et al.: Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data. Pattern Recognit. Lett. 66, 22–30 (2015)CrossRef Ringeval, F., et al.: Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data. Pattern Recognit. Lett. 66, 22–30 (2015)CrossRef
60.
go back to reference Alemzadeh, H., Saleheen, M.U., Jin, Z., Kalbarczyk, Z., Iyer, R.K.: RMED: a reconfigurable architecture for embedded medical monitoring. In: 2011 IEEE/NIH Life Science Systems and Applications Workshop, pp. 112–115 (2011) Alemzadeh, H., Saleheen, M.U., Jin, Z., Kalbarczyk, Z., Iyer, R.K.: RMED: a reconfigurable architecture for embedded medical monitoring. In: 2011 IEEE/NIH Life Science Systems and Applications Workshop, pp. 112–115 (2011)
61.
go back to reference Magalhães, J., Rüger, S.: Information theoretic semantic multimedia indexing. In: Proceedings of the 6th ACM International Conference on Image and Video Retrieval, pp. 619–626 (2007) Magalhães, J., Rüger, S.: Information theoretic semantic multimedia indexing. In: Proceedings of the 6th ACM International Conference on Image and Video Retrieval, pp. 619–626 (2007)
62.
go back to reference Sivanathan, A., Lim, T., Louchart, S., Ritchie, J.: Temporal multimodal data synchronisation for the analysis of a game driving task using EEG. Entertain. Comput. 5(4), 323–334 (2014)CrossRef Sivanathan, A., Lim, T., Louchart, S., Ritchie, J.: Temporal multimodal data synchronisation for the analysis of a game driving task using EEG. Entertain. Comput. 5(4), 323–334 (2014)CrossRef
63.
go back to reference Ruiz, M.D., Gómez-Romero, J., Molina-Solana, M., Ros, M., Martin-Bautista, M.J.: Information fusion from multiple databases using meta-association rules. Int. J. Approx. Reason. 80, 185–198 (2017)MathSciNetCrossRef Ruiz, M.D., Gómez-Romero, J., Molina-Solana, M., Ros, M., Martin-Bautista, M.J.: Information fusion from multiple databases using meta-association rules. Int. J. Approx. Reason. 80, 185–198 (2017)MathSciNetCrossRef
64.
go back to reference Nemati, S., Malhotra, A., Clifford, G.D.: Data fusion for improved respiration rate estimation. EURASIP J. Adv. Sig. Process. 2010, 926305 (2010)CrossRef Nemati, S., Malhotra, A., Clifford, G.D.: Data fusion for improved respiration rate estimation. EURASIP J. Adv. Sig. Process. 2010, 926305 (2010)CrossRef
65.
go back to reference Zong, C.Z.C., Chetouani, M.: Hilbert-Huang transform based physiological signals analysis for emotion recognition. In: 2009 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp. 334–339 (2009) Zong, C.Z.C., Chetouani, M.: Hilbert-Huang transform based physiological signals analysis for emotion recognition. In: 2009 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp. 334–339 (2009)
66.
go back to reference Martínez, H., Yannakakis, G.: Mining multimodal sequential patterns: a case study on affect detection. In: International Conference on Multimodal, pp. 3–10 (2011) Martínez, H., Yannakakis, G.: Mining multimodal sequential patterns: a case study on affect detection. In: International Conference on Multimodal, pp. 3–10 (2011)
67.
go back to reference Chen, J., Luo, N., Liu, Y., Liu, L., Zhang, K., Kolodziej, J.: A hybrid intelligence-aided approach to affect-sensitive e-learning. Computing 98(1–2), 215–233 (2016)MathSciNetCrossRef Chen, J., Luo, N., Liu, Y., Liu, L., Zhang, K., Kolodziej, J.: A hybrid intelligence-aided approach to affect-sensitive e-learning. Computing 98(1–2), 215–233 (2016)MathSciNetCrossRef
68.
go back to reference Chen, L., Zhao, Y., Zhang, J., Zou, J.: Automatic detection of alertness/drowsiness from physiological signals using wavelet-based nonlinear features and machine learning. Expert Syst. Appl. 42(21), 7344–7355 (2015)CrossRef Chen, L., Zhao, Y., Zhang, J., Zou, J.: Automatic detection of alertness/drowsiness from physiological signals using wavelet-based nonlinear features and machine learning. Expert Syst. Appl. 42(21), 7344–7355 (2015)CrossRef
69.
go back to reference Su, H., Zheng, G.: A non-intrusive drowsiness related accident prediction model based on D-S evidence theory. In: 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE, pp. 570–573 (2007) Su, H., Zheng, G.: A non-intrusive drowsiness related accident prediction model based on D-S evidence theory. In: 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE, pp. 570–573 (2007)
70.
go back to reference Cosoli, G., Casacanditella, L., Tomasini, E., Scalise, L.: Evaluation of heart rate variability by means of laser doppler vibrometry measurements. J. Phys. Conf. Ser. 658, 12002 (2015)CrossRef Cosoli, G., Casacanditella, L., Tomasini, E., Scalise, L.: Evaluation of heart rate variability by means of laser doppler vibrometry measurements. J. Phys. Conf. Ser. 658, 12002 (2015)CrossRef
71.
go back to reference Fatemian, S.Z., Agrafioti, F., Hatzinakos, D.: HeartID: cardiac biometric recognition. In: IEEE 4th International Conference Biometrics Theory, Applications and Systems, BTAS 2010, pp. 1–5 (2010) Fatemian, S.Z., Agrafioti, F., Hatzinakos, D.: HeartID: cardiac biometric recognition. In: IEEE 4th International Conference Biometrics Theory, Applications and Systems, BTAS 2010, pp. 1–5 (2010)
72.
go back to reference Pantelopoulos, A., Saldivar, E., Roham, M.: A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 6919–6922 (2011) Pantelopoulos, A., Saldivar, E., Roham, M.: A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 6919–6922 (2011)
73.
go back to reference Zreik, M., Ben-Tsvi, Y., Taub, A., Almog, R.O., Messer, H.: Detection of auditory stimulus onset in the pontine nucleus using a multichannel multi-unit activity electrode. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, vol. 2, no. 17, pp. 2708–2711 (2011) Zreik, M., Ben-Tsvi, Y., Taub, A., Almog, R.O., Messer, H.: Detection of auditory stimulus onset in the pontine nucleus using a multichannel multi-unit activity electrode. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, vol. 2, no. 17, pp. 2708–2711 (2011)
74.
go back to reference Ueda, H., Miyawaki, M., Hiraoka, H.: High-normal blood pressure is associated with new-onset electrocardiographic left ventricular hypertrophy. J. Hum. Hypertens. 29(1), 9–13 (2015)CrossRef Ueda, H., Miyawaki, M., Hiraoka, H.: High-normal blood pressure is associated with new-onset electrocardiographic left ventricular hypertrophy. J. Hum. Hypertens. 29(1), 9–13 (2015)CrossRef
75.
go back to reference Benoit, A., et al.: Multimodal focus attention and stress detection and feedback in an augmented driver simulator. Pers. Ubiquitous Comput. 13(1), 33–41 (2009)CrossRef Benoit, A., et al.: Multimodal focus attention and stress detection and feedback in an augmented driver simulator. Pers. Ubiquitous Comput. 13(1), 33–41 (2009)CrossRef
76.
go back to reference Ai, L., Wang, J., Wang, X.: Multi-features fusion diagnosis of tremor based on artificial neural network and D–S evidence theory. Sig. Process. 88, 2927–2935 (2008)CrossRef Ai, L., Wang, J., Wang, X.: Multi-features fusion diagnosis of tremor based on artificial neural network and D–S evidence theory. Sig. Process. 88, 2927–2935 (2008)CrossRef
77.
go back to reference Sukuvaara, T., Heikela, A.: Computerized patient monitoring. Acta Anaesthesiol. Scand. 37, 185–189 (1993)CrossRef Sukuvaara, T., Heikela, A.: Computerized patient monitoring. Acta Anaesthesiol. Scand. 37, 185–189 (1993)CrossRef
78.
go back to reference Liou, L.M., et al.: Functional connectivity between parietal cortex and the cardiac autonomic system in uremics. Kaohsiung J. Med. Sci. 30(3), 125–132 (2014)CrossRef Liou, L.M., et al.: Functional connectivity between parietal cortex and the cardiac autonomic system in uremics. Kaohsiung J. Med. Sci. 30(3), 125–132 (2014)CrossRef
79.
go back to reference Almasri, M.M., Elleithy, K.M.: Data fusion models in WSNs: comparison and analysis. In: Proceedings of 2014 Zone 1 Conference of the American Society for Engineering Education -Engineering Education: Industry Involvement and Interdisciplinary Trends, ASEE Zone 1, no. 203 (2014) Almasri, M.M., Elleithy, K.M.: Data fusion models in WSNs: comparison and analysis. In: Proceedings of 2014 Zone 1 Conference of the American Society for Engineering Education -Engineering Education: Industry Involvement and Interdisciplinary Trends, ASEE Zone 1, no. 203 (2014)
80.
go back to reference Synnergren, J., Gamalielsson, J., Olsson, B.: Mapping of the JDL data fusion model to bioinformatics. In: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, pp. 1506–1511 (2007) Synnergren, J., Gamalielsson, J., Olsson, B.: Mapping of the JDL data fusion model to bioinformatics. In: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, pp. 1506–1511 (2007)
81.
go back to reference Uluda, K., Roebroeck, A.: General overview on the merits of multimodal neuroimaging data fusion. NeuroImage 102(P1), 3–10 (2014)CrossRef Uluda, K., Roebroeck, A.: General overview on the merits of multimodal neuroimaging data fusion. NeuroImage 102(P1), 3–10 (2014)CrossRef
82.
go back to reference Mohamed, S., Haggag, S., Nahavandi, S., Haggag, O.: Towards automated quality assessment measure for EEG signals. Neurocomputing 237, 281–290 (2017)CrossRef Mohamed, S., Haggag, S., Nahavandi, S., Haggag, O.: Towards automated quality assessment measure for EEG signals. Neurocomputing 237, 281–290 (2017)CrossRef
Metadata
Title
Physiological Signals Fusion Oriented to Diagnosis - A Review
Authors
Y. F. Uribe
K. C. Alvarez-Uribe
D. H. Peluffo-Ordoñez
M. A. Becerra
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-98998-3_1

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