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Motion Analysis in Biomedical Engineering
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Motion Analysis in Biomedical Engineering

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: closed (15 August 2023) | Viewed by 6125

Special Issue Editors

Dr. Agnieszka Szczęsna

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Guest Editor
Department of Computer Graphics, Vision and Digital Systems, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
Interests: motion analysis; 3D computer graphics; motion capture; quaternions; inertial sensors; digital geometry processing
Dr. Adam Świtoński

E-Mail Website
Guest Editor
Department of Computer Graphics, Vision and Digital Systems, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
Interests: processing and classification of motion capture data; time series analysis; machine learning; computer vision
Special Issues, Collections and Topics in MDPI journals
Dr. Damian Pęszor

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Guest Editor
Department of Computer Graphics, Vision and Digital Systems, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
Interests: motion capture; gait analysis
Dr. Michał Staniszewski

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Guest Editor
Department of Computer Graphics, Vision and Digital Systems, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
Interests: signal processing; computer vision; image processing; object recognition

Special Issue Information

Dear Colleagues,

Biomedical signal processing involves acquiring and preprocessing physiological signals and extracting meaningful information to identify patterns and trends within the signals. Sources of biomedical signals include neural activity, cardiac rhythm, muscle and skeleton movement, and other physiological activities. The Special Issue concerns the new methods of analysis of human motion treated as a biomedical signal. Depending on the acquisition method, time series may encode motion in the form of orientations, positions, accelerations, or angular velocities in 3D. Combined with other biomedical signals, which are more and more easily accessible through wearable devices, it can be an essential source of information on the psycho-physical condition during daily life activities. This is an interdisciplinary and fast-developing field with wide and promising biomedical applications, human–computer interfacing, and surveillance systems for monitoring human behaviors as well as analysis of biomedical signals for diagnosis and rehabilitation applications.

  • Biomedical signal processing
  • Biomedical signal sensing
  • Biomedical signals
  • Wearable devices
  • Human motion analysis
  • Artificial intelligence (AI)
  • Physiological activities

Dr. Agnieszka Szczęsna
Dr. Adam Świtoński
Dr. Damian Pęszor
Dr. Michał Staniszewski
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

28 pages, 1382 KiB  
Article
Analysis of Relation between Brainwave Activity and Reaction Time of Short-Haul Pilots Based on EEG Data
by Bartosz Binias, Dariusz Myszor, Sandra Binias and Krzysztof A. Cyran
Sensors 2023, 23(14), 6470; https://doi.org/10.3390/s23146470 - 17 Jul 2023
Cited by 2 | Viewed by 1656
Abstract
The purpose of this research is to examine and assess the relation between a pilot’s concentration and reaction time with specific brain activity during short-haul flights. Participants took part in one-hour long flight sessions performed on the FNPT II class flight simulator. Subjects [...] Read more.
The purpose of this research is to examine and assess the relation between a pilot’s concentration and reaction time with specific brain activity during short-haul flights. Participants took part in one-hour long flight sessions performed on the FNPT II class flight simulator. Subjects were instructed to respond to unexpected events that occurred during the flight. The brainwaves of each participant were recorded with the Emotiv EPOC+ Scientific Contextual EEG device. The majority of participants showed a statistically significant, positive correlation between Theta Power in the frontal lobe and response time. Additionally, most subjects exhibited statistically significant, positive correlations between band-power and reaction times in the Theta range for the temporal and parietal lobes. Statistically significant event-related changes (ERC) were observed for the majority of subjects in the frontal lobe for Theta frequencies, Beta waves in the frontal lobe and in all lobes for the Gamma band. Notably, significant ERC was also observed for Theta and Beta frequencies in the temporal and occipital Lobes, Alpha waves in the frontal, parietal and occipital lobes for most participants. A difference in brain activity patterns was observed, depending on the performance in time-restricted tasks. Full article
(This article belongs to the Special Issue Motion Analysis in Biomedical Engineering)
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18 pages, 1615 KiB  
Article
The Problem of Monitoring the Psycho-Physical Condition of Seniors during Proposed Activities in Urban Space
by Ewa Lach, Anna Szewczenko, Iwona Chuchnowska, Natalia Bursiewicz, Iwona Benek, Sylwia Widzisz-Pronobis, Daria Bal, Klaudia Elsner, Marta Sanigórska, Mateusz Sutor and Jakub Włodarz
Sensors 2023, 23(3), 1602; https://doi.org/10.3390/s23031602 - 1 Feb 2023
Cited by 2 | Viewed by 1422
Abstract
The world’s population is rapidly ageing, which places a heavy burden on traditional healthcare systems with increased economic and social costs. Technology can assist in the implementation of strategies that enable active and independent ageing by promoting and motivating health-related behaviours, monitoring, and [...] Read more.
The world’s population is rapidly ageing, which places a heavy burden on traditional healthcare systems with increased economic and social costs. Technology can assist in the implementation of strategies that enable active and independent ageing by promoting and motivating health-related behaviours, monitoring, and collecting data on daily life for assessment and for aiding in independent living. ICT (Information and Communication Technology) tools can help prevent cognitive and physical decline and social isolation, and enable elderly people to live independently. In this paper, we introduced a comprehensive tool for guiding seniors along the designed urban health paths employing urban architecture as an impulse to perform physical and cognitive exercises. The behaviour of seniors is monitored during their activities using wearable sensors and mobile application. We distinguished three types of data recipients (seniors, path/exercise designers, and the public), for whom we proposed methods of analysing the obtained data and examples of their use. In this work, a wide range of diverse information was examined from which short- and long-term patterns can be drawn. We have also shown that by fusing sensory data and data from mobile applications, we can give context to sensory data, thanks to which we can formulate more insightful assessments of seniors’ behaviour. Full article
(This article belongs to the Special Issue Motion Analysis in Biomedical Engineering)
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14 pages, 2087 KiB  
Article
Modeling of Respiratory Motion to Support the Minimally Invasive Destruction of Liver Tumors
by Dominik Spinczyk, Sylwester Fabian and Krzysztof Król
Sensors 2022, 22(20), 7740; https://doi.org/10.3390/s22207740 - 12 Oct 2022
Cited by 2 | Viewed by 1365
Abstract
Objective: Respiratory movements are a significant factor that may hinder the use of image navigation systems during minimally invasive procedures used to destroy focal lesions in the liver. This article aims to present a method of estimating the displacement of the target point [...] Read more.
Objective: Respiratory movements are a significant factor that may hinder the use of image navigation systems during minimally invasive procedures used to destroy focal lesions in the liver. This article aims to present a method of estimating the displacement of the target point due to respiratory movements during the procedure, working in real time. Method: The real-time method using skin markers and non-rigid registration algorithms has been implemented and tested for various classes of transformation. The method was validated using clinical data from 21 patients diagnosed with liver tumors. For each patient, each marker was treated as a target and the remaining markers as target position predictors, resulting in 162 configurations and 1095 respiratory cycles analyzed. In addition, the possibility of estimating the respiratory phase signal directly from intraoperative US images and the possibility of synchronization with the 4D CT respiratory sequence are also presented, based on ten patients. Results: The median value of the target registration error (TRE) was 3.47 for the non-rigid registration method using the combination of rigid transformation and elastic body spline curves, and an adaptation of the assessing quality using image registration circuits (AQUIRC) method. The average maximum distance was 3.4 (minimum: 1.6, maximum 6.8) mm. Conclusions: The proposed method obtained promising real-time TRE values. It also allowed for the estimation of the TRE at a given geometric margin level to determine the estimated target position. Directions for further quantitative research and the practical possibility of combining both methods are also presented. Full article
(This article belongs to the Special Issue Motion Analysis in Biomedical Engineering)
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12 pages, 2377 KiB  
Article
Measuring Respiratory Motion for Supporting the Minimally Invasive Destruction of Liver Tumors
by Dominik Spinczyk
Sensors 2022, 22(17), 6446; https://doi.org/10.3390/s22176446 - 26 Aug 2022
Cited by 2 | Viewed by 1057
Abstract
Objective: Destroying liver tumors is a challenge for contemporary interventional radiology. The aim of this work is to compare different techniques used for the measurement of respiratory motion, as this is the main hurdle to the effective implementation of this therapy. Methods: Laparoscopic [...] Read more.
Objective: Destroying liver tumors is a challenge for contemporary interventional radiology. The aim of this work is to compare different techniques used for the measurement of respiratory motion, as this is the main hurdle to the effective implementation of this therapy. Methods: Laparoscopic stereoscopic reconstruction of point displacements on the surface of the liver, observation of breathing using external markers placed on the surface of the abdominal cavity, and methods for registration of the surface of the abdominal cavity during breathing were implemented and evaluated. Results: The following accuracies were obtained: above 4 mm and 0.5 mm, and below 8 mm for laparoscopic, skin markers, and skin surface registration methods, respectively. Conclusions: The clinical techniques and accompanying imaging modalities employed to destroy liver tumors, as well as the advantages and limitations of the proposed methods, are presented. Further directions for their development are also indicated. Full article
(This article belongs to the Special Issue Motion Analysis in Biomedical Engineering)
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