The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper we present a method for optimization of spatial selectivity of multi-pad electrode during transcutaneous Functional Electrical Stimulation (FES). The presented method is based on measurement of individual muscle twitches using Micro-Electro-Mechanical Systems (MEMS) accelerometers positioned on hand, while stimulating with low frequency electrical stimulation via pads within multi-pad...
We present a system for polymyographic analysis which addresses detection of muscle fatigue and strategies assumed by the central nervous system to deal with it. The system consists of EMG amplifiers, force transducers, A/D converter, portable computer and software running in the LabView environment that allows real-time and detailed offline processing of EMG signals in time and frequency domains...
Independent Component Analysis (ICA) is becoming an accepted technique for artifact removal. Nevertheless, there is no consensus about appropriate methods for different applications. This study presents a comparison of common ICA methods: RobustICA, SOBI, JADE, and BSS-CCA, for extraction of ECG artifacts from EEG signal. Algorithms were applied to the data created by superimposing artifact free real-life...
This paper presents machine learning (ML) techniques for development of a control scheme to be used in functional electrical stimulation (FES) of hemiplegic walking. The goal is to make an electrical stimulation pattern by mapping the sensors signals acquired during walking (input) to activities of muscles (output) acting around knee and ankle joints. Two machine learning techniques with ability of...
In this paper, an efficient heart beat classification algorithm suitable for implementation on mobile devices is presented. A simplified ECG model is used for feature extraction in the time domain. The QRS complex is modeled using straight lines, while P and T waves are modeled using parabolas. The model parameters are estimated by minimizing the root mean square (RMS) of the model error. Heart beats...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.