Electrocardiograph-based identification of persons with sleep apnoea

The electrocardiogram (ECG) is a universal, easily measurable biosignal that is unique to each individual, ubiquitous, and difficult to reproduce due to its independence from external body characteristics. The potential of ECG as a suitable recording for person recognition has increased with the development of methods that can measure ECG signals "off the person." This measurement technique involves electrodes embedded in objects that the person comes into contact with during other activities. Various applications can be integrated with continuous ECG monitoring to derive quantitative measurements of the user’s current stress, fatigue, and illness. With the advanced technology for recording ECG signals, real-time authentication is becoming more popular. Although classification of subjects using ECG has primarily been performed on healthy patients, this paper focuses on the ECG processing of sleep apnea patients. We have demonstrated the feasibility of using the ECG-based identification method, not only for healthy individuals but also for patients suffering from this disease. Our work has shown the practical use of this method for a larger part of the population in the medical environment.