| Title |
ECG signal analysis for the modelling of training process and fatigue evaluation / |
| Translation of Title |
EKG signalų analizė treniruočių proceso modeliavimui ir nuovargio vertinimo metodikos sudarymui. |
| Authors |
Butkevičiūtė, Eglė |
| Full Text |
|
| Pages |
48 |
| Keywords [eng] |
signal filtering algorithms ; electrocardiogram ; fatigue evaluation methodology ; ECG parameter estimation algorithms |
| Abstract [eng] |
Biological signals recorded in movement allow to evaluate interactions between different human organism systems and dynamic changes in daily activities. If a person performs physical or mental exercises, multiple systems work in parallel: cardiovascular, muscular, neural and others. ECG signals recorded in movement are contaminated with various noises. The obtained noise is non-stationary and depends on the intensity of a particular exercise. That is why ordinary filtering methods fail in signal processing without damage to basic signal characteristics. The proposed filtering algorithm is able to adapt to the level of appearing noise in different workloads and maintain the most important ECG parameter values that are essential for the health evaluation and monitoring. Also, in this research a new physiological fatigue evaluation and recognition methodology is proposed that uses linear and non-linear heart rate variability analysis and machine learning techniques. In the classification part the accurate ECG signal parameter estimation algorithms becomes very important. For these parameters search the modified and supplemented k-TEO algorithm was selected and implemented. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Summaries of doctoral thesis |
| Language |
English |
| Publication date |
2021 |
