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453 results on '"Katashev A"'

3. Method for Muscle Fatigue Detection Using Inertial Sensors

Author

Banga, Beāte, Katashev, Alexei, Greitāns, Modris, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Dekhtyar, Yuri, editor, and Saknite, Inga, editor

Published
2023
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4. Method to Detect Trigger Pulling Errors in Shooting Sports: Smart Textile Application

Author

Katashev, Alexei, Vevere, Adelina, Oks, Alexander, Terlecka, Galina, Saiva, Laima, Jansons, Mareks, Dyachenko, Natalya, Seglina, Patricija, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Dekhtyar, Yuri, editor, and Saknite, Inga, editor

Published
2023
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7. A Study Module in the Logical Structure of Cognitive Process in the Context of Variable-Based Blended Learning

Author

Smirnova, Galina I. and Katashev, Valery G.

Abstract

Blended learning is increasingly gaining importance in all levels of educational system, particularly in tertiary education. In engineering profiles the core blended learning activity is students' independent work, the efficiency of which is defined by the degree of students' active involvement into the educational process, their ability to absorb new knowledge independently, on their own. Our research is aimed at the analysis of blended learning and at revealing the approaches meant to activate students' independent work in blended learning based on LMS Moodle platform. The characteristic feature of the suggested approach is the orientation towards skills and work methods mastering carried out in the form of professional competencies training at practical classes and laboratory workshops. For the purpose of our research we used one of the most interactive Moodle tools--"workshop" in order to fulfill informational, educational and monitoring functions of learning. The use of the tool allowed revealing drawbacks of the method under study and managing these drawbacks in the most effective way. The paper contains the description of students' learning and independent work which would stimulate students' activity, self-management and develop their communicative skills. The outcomes of the current research proved that the approaches suggested significantly stir students' interest, thus, enhancing students their learning motivation, development of critical thinking and self-reflection, which altogether facilitate understanding theoretical material, encourage the development of practical skills and promote the pursue of academic goals.

Published
2017

11. Smart Shirt for Uncontrolled Movement Retraining

Author

Eizentals, Peteris, Katashev, Alexei, Oks, Alexander, Semjonova, Guna, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Henriques, Jorge, editor, Neves, Nuno, editor, and de Carvalho, Paulo, editor

Published
2020
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12. New Method to Analyze the Load Propagation on the Plantar Foot Surface During a Walk/Run Using the Smart Sock System

Author

Okss, Alexander, Katashev, Alexei, Eizentals, Peteris, Rozenstoka, Sandra, Suna, Dace, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Henriques, Jorge, editor, Neves, Nuno, editor, and de Carvalho, Paulo, editor

Published
2020
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18. On the Monitoring of Breathing Volume, Using Textile Strain Gauges

Author

Rozevika, Artyom, Katashev, Alexei, Okss, Alexander, Mantyla, Janne, Coffeng, Rene, Magjarevic, Ratko, Editor-in-Chief, Ładyżyński, Piotr, Series Editor, Ibrahim, Fatimah, Series Editor, Lacković, Igor, Series Editor, Rock, Emilio Sacristan, Series Editor, Lhotska, Lenka, editor, Sukupova, Lucie, editor, and Ibbott, Geoffrey S., editor

Published
2019
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20. Development of a New Method to Monitor Shoulder Girdle Motion for Ballerina with Shoulder Impingement Syndrome Based on DAid Smart Shirt Application

Author

Semjonova, Guna, Vetra, Janis, Oks, Alexander, Katashev, Alexei, Magjarevic, Ratko, Editor-in-Chief, Ładyżyński, Piotr, Series Editor, Ibrahim, Fatimah, Series Editor, Lacković, Igor, Series Editor, Rock, Emilio Sacristan, Series Editor, Lhotska, Lenka, editor, Sukupova, Lucie, editor, and Ibbott, Geoffrey S., editor

Published
2019
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21. Application of Smart Sock System for Testing of Shoe Cushioning Properties

Author

Oks, Alexander, Katashev, Alexei, Eizentals, Peteris, Pavare, Zane, Balcuna, Darta, Magjarevic, Ratko, Editor-in-Chief, Ładyżyński, Piotr, Series Editor, Ibrahim, Fatimah, Series Editor, Lacković, Igor, Series Editor, Rock, Emilio Sacristan, Series Editor, Lhotska, Lenka, editor, Sukupova, Lucie, editor, and Ibbott, Geoffrey S., editor

Published
2019
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22. A comparison between the commercially available gamma criteria evolution software and new modified algorithm for field-in-field technique

Author

Bernans, Alvis, Meziels, Ritvars, Katashev, Alexei, Magjarevic, Ratko, Editor-in-chief, Ładyżyński, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, Eskola, Hannu, editor, Väisänen, Outi, editor, Viik, Jari, editor, and Hyttinen, Jari, editor

Published
2018
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27. Development of Smart Sock System for Gate Analysis and Foot Pressure Control

Author

Oks, Alexander, Katashev, Alexei, Zadinans, M., Rancans, M., Litvak, J., Magjarevic, Ratko, Editor-in-chief, Ładyżyński, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, Kyriacou, Efthyvoulos, editor, Christofides, Stelios, editor, and Pattichis, Constantinos S., editor

Published
2016
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43. Improving the Recovery of Patients with Subacromial Pain Syndrome with the DAid Smart Textile Shirt

Author

Guna Semjonova, Janis Vetra, Vinita Cauce, Alexander Oks, Alexei Katashev, and Peteris Eizentals

Subjects
subacromial pain syndrome, physiotherapy, rehabilitation, smart textile, textile sensors, Chemical technology, TP1-1185
Abstract

Wearable technologies provide many possibilities for applications in medicine, and especially in physiotherapy, where tracking and evaluation of body motion are of utmost importance. Despite the existence of multiple smart garments produced for applications in physiotherapy, there is limited information available on the actual impact of these technologies on the clinical outcomes. The objective of this paper is to evaluate the impact of the Double Aid (DAid) smart shirt, a purely textile-based system, on the training process of patients with subacromial pain syndrome. A randomized controlled trial was performed where patients with subacromial pain syndrome had to perform the assigned training exercises while employing the DAid smart shirt system. The core point of each exercise was to perform a movement while holding the shoulders stationary. The smart shirt was designed to sense even slight shoulder motion thus providing the patient with feedback on the accuracy of the motion, and allowing the patient to adjust the movement. The appropriate muscles should be strengthened through an increased effort to control the shoulder motion. The recovery of patients using the feedback system at the end of the treatment was compared to that of a reference group through standardized tests—the Disabilities of the Arm, Shoulder, and Hand score (DASH score), Closed Kinetic Chain Upper Extremity Stability test (CKCUES test), and internal/external rotation ratio. The test group that used the DAid system demonstrated significantly better results of the performed tests for all applied outcome measures compared to the reference group (p < 0.001). An overall positive impact on the patient recovery was observed from the DAid smart shirt system when applied for rehabilitation training of patients with subacromial pain syndrome.

Published
2020
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44. Smart textile device for shooter’s fingers movement monitoring

Author

Mareks Jansons, Laima Saiva, Alexander Oks, Adelina Vevere, Galina Terlecka, Natalya Dyachenko, Patricija Seglina, and Alexei Katashev

Subjects
Computer science, Movement, Biomedical Engineering, Biophysics, Health Informatics, Bioengineering, Middle finger, Motion capture, Fingers, Biomaterials, Recoil, medicine, Humans, Movement (clockwork), Computer vision, Resistive touchscreen, Hand Strength, business.industry, Textiles, Index finger, Pressure sensor, medicine.anatomical_structure, Artificial intelligence, Grip force, business, Information Systems
Abstract

BACKGROUND: The manner in which shooters pull the trigger may significantly affect the shooter’s results. Shooting coaches are often not able to detect incorrect pull because of gun movement during the shot and recoil. OBJECTIVE: Development of the smart-textile based trigger pull monitoring system and demonstration of its ability to distinguish correct and wrong triggering techniques. METHODS: Two separated knitted resistive pressure sensors were integrated over III and II phalanges in the index finger fingerstall; single sensor was integrated over both III and II phalanges of the middle finger fingerstall. Resistance of the sensors was measured in a course of shots, performed by expert shooter, which simulated typical novice’s trigger pull errors. RESULTS: Sensors’ resistance recordings were made for following erroneous trigger pull motions: pulling of the trigger with index finger’s II phalanx instead of III; fast and jerky trigger pull (trigger tear-off); too fast release of the trigger after shot; and excessive grip force, applied by middle finger. For each type of erroneous movement, recordings waveforms included distinguishable features that characterised a particular type of error. CONCLUSIONS: The developed trigger pull monitoring system provides signals that could be used for recognition of the incorrect trigger pull motions during gun shots.

Published
2021
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46. Smart socks: new effective method of gait monitoring for systems with limited number of plantar sensors

Author

Oks, Alexander, Katashev, Alexei, Eizentals, Peteris, Rozenstoka, Sandra, and Suna, Dace

Abstract

Advanced version of DAid® Pressure Sock System (DPSS) for walking/running gait monitoring is proposed. The system enables to study in details time –related parameters of gait, such as foot strike time, stride/swing time, gradients of plantar loading/unloading, etc. both indoor and outdoor. A new method of data processing, analysis and representation is developed for such systems with limited quantity of sensors and implemented in DPSS software. The method considers the foot loading as a propagation of the plantar pressure wave, where separate sensors record amplitudes of pressure waves as reference points. Data processing includes scaling procedure that is based on application of sample entropy as the measure of sensors activity. Processed data are represented in the form of loading wave plots (WPs). WPs show load propagation across the sensors during the gait/stance. Developed system and method were tested for different types of walk/run and corresponding WPs were constructed and evaluated by sport medicine doctors. Good agreement between WPs – based analysis and diagnoses made by direct observation during walk/run tests confirms system efficacy and validity of results. Proposed method essentially simplifies gait studies and interpretation of the results.

Published
2024
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47. Smart shirt system for compensatory movement retraining assistance: feasibility study

Author

Eizentals, Peteris, Katashev, Alexei, Oks, Alexander, and Semjonova, Guna

Abstract

Movement retraining has proven to be a reliable way of treating compensatory movement faults, however, it is time-consuming and requires a lot of attention from a physiotherapist. Reliable movement retraining assistance system could enable patients to perform retraining exercises at home, thus increasing the possible exercise performance frequentness and consequently hasten the improvement. This paper describes a smart shirt system for movement retraining assistance. The smart shirt system is based on textile stretch sensors that are positioned over the typical movement fault sites for movement detection and monitoring. The information from the textile stretch sensors is used as visual feedback by the wearer for movement corrections. To verify the feasibility of the retraining assistance system, it was tested with a set of compensatory movement tests and retraining exercises. Each exercise was performed in a correct and incorrect manner, and the sensor measurement was analyzed to confirm the difference in measured signals between both cases. In total 11 exercises were performed to cover all of the typical compensatory movement sites, and for each retraining exercise, at least one sensor was identified, whose measurement could be used as feedback for the particular exercise.

Published
2024
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