Neinvazivní sledování zdravotního stavu pracovníků pomocí nositelného zařízení

Abstract

The aim of this thesis is to design a virtual device for processing medical data from monitoring of a worker. And validation of this device by experimental measurements using wearable sensors and subsequent analysis of the acquired electrocardiogram (ECG) data using a continuous wavelet transform (CWT)-based R-peak detection algorithm and subsequent evaluation of the quality of detection and heart rate (HR) estimation using this methodology. Frequency analysis of the EMG recording to visualize the spectrum composition of each scenario, and quantify the worker load. Finally, detection of worker activity using a novel accelerometer-gyroscope-magnetometer (AGM) method and from measured EMG, and their validation against a reference camera recording. The study was carried out on real data measured in experimental measurements in laboratory conditions within the new CPIT TL3 building on a line demonstrating Industry 4.0. The output of the work is a virtual instrument for displaying and analyzing the basic vital signs of the subject being monitored using commercially available Shimmer devices.