Can patients in deep coma hear us? Examination of coma depth using physiological signals. (August 2022)

• Record Type: Journal Article
• Authors: Altıntop, Çiğdem Gülüzar; Latifoğlu, Fatma; Akın, Aynur Karayol
• Is Part Of: Biomedical signal processing and control. Volume 77(2022)
• Publication Date: 2022-08
• Subjects: Glasgow coma score -- Depth of coma -- Electrocardiography -- Electrooculography -- Eye movement -- Level of consciousness; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2022.103756
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: Glasgow Coma Scale (GCS) is used to determine the level of consciousness of comatose patients. This study aimed to evaluate GCS with an objective approach using Electrocardiography (ECG) and Electrooculography (EOG) signals. This is the first study to use ECG and EOG signals to classify patients in deep coma (GCS 3–8). Although patients were unconscious, they were aware of emotional stimuli applied by the family/nurse. Abstract: The Glasgow coma score (GCS) is the most commonly used scale to measure the depth of a coma. Determining the GCS score depends on the clinician's experience and cannot be done fully on sedated and intubated patients. In addition, the success of the scale is being questioned due to differences in reliability and performance among clinicians. Therefore, this study aimed to evaluate GCS with an objective approach using Electrocardiography (ECG) and Electrooculography (EOG) signals based on numerical results. In this study, ECG and EOG signals were obtained simultaneously with the recording scenario in which the family and the nurse play an active role as the emotional stimulus, with a new approach. Using the features extracted from physiological signals, the effects of the family and the nurse on unconscious patients and their level of consciousness were evaluated with statistical analysis methods. In addition, classification studies were performed and the success of physiological signals in classifying the GCS was compared. In the classification of consciousness levels, 88.64% accuracy with ECG signals and 73.70% accuracy with EOG signals were obtained. In addition, our results showed that although the patients were unconscious, they were aware of the emotional stimuli applied by the family/nurse. Thus, in this study, a novel approach was proposed that, the GCS of coma patients could be determined with the analysis of EOG and ECG signals obtained with tactile and auditory stimuli.