The Academic Perspective Procedia publishes Academic Platform symposiums papers as three volumes in a year. DOI number is given to all of our papers.
Publisher : Academic Perspective
Journal DOI : 10.33793/acperpro
Journal eISSN : 2667-5862
Year :2019, Volume 2, Issue 3, Pages: 831-840
22.11.2019
Analysis of ECG Signals Recorded Using Different Stimuli from Patients in Intensive Care Unit: A Case Study
Intensive Care Units (ICUs) are more difficult and complex areas of hospital as treatment and care. In these units, the patients are monitored continuously with a bedside monitor for respiration, O2 saturation and pulse information. However, this information, which is periodically noted on the patient observation papers, may not represent a definite diagnose/follow up about the patients health condition in all times. Therefore, in order to assist the physician in these units where the diagnosis/follow up is important, attributes are extracted from ECG signals easy-to-obtain by using signal processing methods. ECG signals were obtained from 3 patients at different days. Attributes were analyzed statistically to see if the patient reacted to oral/touch stimuli and to monitor his / her health condition. As a result, it was possible to evaluate the coma patients response to stimuli and to follow-up for improving physiological well-being using ECG signals.
[1] Cooksley V, T Holland, The unconscious patient, Medicine. 2013;41(3): 146-150.
[2] Campbell S, McCormick W. Approach to the comatose patient. Can JCME 2002; 77-84.
[3] Sepit D. Bilinç durumunun değerlendirilmesi ve Glasgow Koma skalası. Hemşirelikte Eğitimve Araştırma Dergisi 2005; 2(1): 12-6.
[4] Flower L. Literature Survey on Biomedical Signal Processing Methods. International Journalof Innovative Research in Computer and Communication Engineering 2016; 4(2): 50-4.
[5] Wieser M, Koenig B.A, Riener R. Quantitative Description of the State of Awareness ofPatients in Vegetative and Minimally Conscious State. 32nd Annual International Conferenceof the IEEE EMBS Buenos Aires, Argentina,5533-5536, August 31 - September 4, 2010.
[6] Rigas G, Goletsis Y, Fotiadis DI. Real-Time Driver’s Stress Event Detection. IEEETransactions on Intelligent Transportation Systems 2012; 13:221-234.
[7] Begum S., Ahmed MU, Funk P, Xiong N, Schéele B.V. Case-Based Decision SupportSystem for Individual Stress Diagnosis Using Fuzzy Similarity Matching. The Journal ofComputational Intelligence (CI), 2009; 25(3):180-195.
[8] Arslan S, Ozer N. Touching, Music Therapy and Aromatherapy’s Effect on the PhysiologicalSituation of the Patients in Intensive Care Unit. International Journal of Caring Sciences2016; 9 (3):867.
[9] Chan MF. et al. Effects of music on patients undergoing a Cclamp procedure afterpercutaneous coronary interventions. Journal of Advanced Nursing 2006; 53(6): 669-679.
[10] Cooke B, Ernst E. Aromatherapy: a systematic review. British Journal of General Practice2000; 50: 493-6.
[11] Bashar SK, Ding E, Walkey AJ, McManus DD, Chon KH. Noise Detection inElectrocardiogram Signals for Intensive Care Unit Patients. IEEE Access, 2019;7:88357-88368.
[12] Lin C, Chen S, Wang Y, Lu S. Develop a multiple physiological system of ICU patientswith symptom analysis and decision making. 2014 IEEE International Conference onConsumer Electronics - Taiwan, Taipei, 2014; 163-164.
[13] Serackis A, Abromavicius V, Gudiškis A. Identification of ECG signal pattern changes toreduce the incidence of Ventricular Tachycardia false alarms. 2015 Computing in CardiologyConference (CinC), Nice, 2015;1193-1196.
[14] Manna T, Swetapadma A. An Improved Method for Detecting False Alarm in ArrhythmiaICU Patients. 2018 Fourth International Conference on Research in ComputationalIntelligence and Communication Networks (ICRCICN), Kolkata, India, 2018; 66-69.
[15] Oh B.S, Yeo Y. K, Wan F. Y, Wen Y, Yang Y, Lin Z. Effects of noisy sounds on humanstress using ECG signals: An empirical study. In 2015 10th International Conference onInformation, Communications and Signal Processing (ICICS) 2015; 1-4.
[16] Kocaçalışkan İ, Akanıl Bingöl N. Biyoistatistik, 2nd ed. pp. 184, 2008.
Cite
@article{acperproISITES2019ID92, author={Altıntop, Çiğdem Gülüzar and Latifoğlu, Fatma and Yazar, Mehmet Akif and Akın, Aynur Karayol and İleri, Ramis}, title={Analysis of ECG Signals Recorded Using Different Stimuli from Patients in Intensive Care Unit: A Case Study}, journal={Academic Perspective Procedia}, eissn={2667-5862}, volume={2}, year=2019, pages={831-840}}
Altıntop, Ç. , Latifoğlu, F. , Yazar, M. , Akın, A. , İleri, R.. (2019). Analysis of ECG Signals Recorded Using Different Stimuli from Patients in Intensive Care Unit: A Case Study. Academic Perspective Procedia, 2 (3), 831-840. DOI: 10.33793/acperpro.02.03.92
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