Karolina Jančiulevičiûtė, Birutė Paliakaitė, V. Marozas
{"title":"Influence of Signal Acquisition Location on Blood Pressure Parameters in Photoplethysmogram","authors":"Karolina Jančiulevičiûtė, Birutė Paliakaitė, V. Marozas","doi":"10.1109/BIOMDLORE49470.2021.9594490","DOIUrl":"https://doi.org/10.1109/BIOMDLORE49470.2021.9594490","url":null,"abstract":"BACKGROUND: Abnormal changes in blood pressure (BP) may be an indicator of developing cardiovascular diseases. Thus, continuous BP monitoring can facilitate early diagnosis and treatment of cardiovascular diseases. Since there is a lack of convenient methods for continuous BP monitoring, morphological analysis of an optical photoplethysmogram (PPG) signal is considered as an alternative.OBJECTIVE: Although PPG can be acquired from different body locations, it is unclear which is the most suitable for obtaining BP-related parameters. Hence, the aim of this study is to investigate the influence of the signal acquisition location on morphological PPG parameters.METHODS: PPG parameters from different body locations, i.e., finger, ear and neck, were assessed for 48 healthy participants performing 2 cold water tests. Changes in parameters between cold water and rest phases were checked for significance.RESULTS: Five out of seven parameters for the finger PPG changed significantly between all adjacent phases, whereas only sporadic changes were observed in the parameters for the ear and neck PPGs. However, all parameters except one showed significant changes at least once between cold water and rest phases.CONCLUTIONS: PPG signals acquired from the finger are the most suitable for assessing parameters potentially associated with changes in BP.","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115397939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martynas Ramanauskas, R. Bikuliciene, Evelina Jotkeviciute
{"title":"The effect of physiotherapy on body balance and pain intensity of elite female handball player after anterior cruciate ligament reconstruction and medial meniscus fixation: A case study","authors":"Martynas Ramanauskas, R. Bikuliciene, Evelina Jotkeviciute","doi":"10.1109/BIOMDLORE49470.2021.9594306","DOIUrl":"https://doi.org/10.1109/BIOMDLORE49470.2021.9594306","url":null,"abstract":"Knee injuries are relatively common in court- and field-based sports. Anterior cruciate ligament (ACL) and meniscus injuries often require surgical treatment to return to high-level sports. ACL tears after reconstruction surgery carry a high recurrence rate. Balance training plays an important role in injury prevention programmes and is important to improve lower extremity function and decrease the risk of recurring knee injury. The research aim is to evaluate the effect of physiotherapy for an elite female handball player’s body balance and pain intensity after anterior cruciate ligament reconstruction and medial meniscus fixation. Body balance was evaluated with the Posturomed platform with two-dimensional measurement by MicroSwing software. Pain intensity was measured using the Visual Analogue Scale (VAS). A physiotherapy programme with an unstable oscillatory platform was developed and used to train the athlete’s body balance. Posturomed platform oscillations decreased from 34.1 cm to 16 cm in the frontal plane on the left leg and from 46 cm to 24.4 cm on the right leg; in the sagittal plane the platform distance changed from 273 cm to 256 cm on the left leg and 207 cm to 211 cm on the right leg. The average platform disturbance in the frontal plane was 22.73 ± 6.75 cm on the left leg and 31.21 ± 9.37 cm on the right; the average disturbance path in the sagittal plane was 254.5 ± 61.48 cm on the left leg and 223 ± 37.56 cm on the right leg. Balance stability increased from 55% (right leg) and 65% (left leg) to 89% (right leg) and 88% (left leg). During 6 weeks of intervention the pain intensity score changed from 7 to 3 (VAS). The six-week physiotherapy programme with an unstable oscillatory platform (Posturomed) improved body balance and decreased the pain intensity.","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123315981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Wodarski, M. Chmura, M. Gzik, Grzegorz Gruszka, J. Jurkojć
{"title":"Technical Analysis of the Displacements of the Centre of Pressure in the Standing Posture Based on Data Obtained Using Selected Stock Market Indicators","authors":"P. Wodarski, M. Chmura, M. Gzik, Grzegorz Gruszka, J. Jurkojć","doi":"10.1109/BIOMDLORE49470.2021.9594338","DOIUrl":"https://doi.org/10.1109/BIOMDLORE49470.2021.9594338","url":null,"abstract":"BACKGROUND: Commonly used analyses of the ability to maintain balance do not take into account momentary changes appearing during the entire analysis. Looking at the nature of the COP and COM curves, a conclusion can be drawn that such trends could be investigated applying methods used for the technical analysis of stock exchange rates.OBJECTIVE: The objective of the study was to determine whether the Moving Average Convergence/Divergence indicator (MACD) could be used in the analyses concerning the assessment of the ability to maintain balance.METHODS: The study group was consisted of 85 healthy individuals in the real environment tests and 12 healthy individuals in the virtual environment tests (with a oscillating scenery). Performed calculations enabled the identification of time intervals between successive trend changes in relation to the COP displacements.RESULTS: Test results revealed that, when standing, the most frequently appearing time intervals between successive trend changes were restricted within the range of 0.1 s. to 0.5 s.CONCLUSIONS: The above-presented trend was observed both in relation to the measurements conducted in the real environment and those performed in the oscillating virtual environment. The foregoing could indicate that the changes are characteristic and indispensable for the proper maintaining of balance by humans.","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122474841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Oscar Jossa Bastidas, B. Garcia-Zapirain, A. L. Totoricagüena, Sofia Zahia, Jon Uriarte Carpio
{"title":"Feature analysis and prediction of complications in ostomy patients based on laboratory analytical data using a machine learning approach","authors":"Oscar Jossa Bastidas, B. Garcia-Zapirain, A. L. Totoricagüena, Sofia Zahia, Jon Uriarte Carpio","doi":"10.1109/BIOMDLORE49470.2021.9594427","DOIUrl":"https://doi.org/10.1109/BIOMDLORE49470.2021.9594427","url":null,"abstract":"BACKGROUND: Stoma complications are commonly related to inadequate surgical preparation and changes in abdominal perimeter configuration. Preventive identification of such complications would improve patient care quality of life.OBJECTIVE: To carry out an approximate study on the prediction of complications in ostomy patients, based on laboratory analytical data using a machine learning approach.METHODS: A total of 20 patients participate in the study. Following the data preprocessing stage, 16 patients with 14 features were selected. The cross-validation method with k = 4 was used to obtain the results of 3 classifiers trained using all the features. Moreover, the classification process was also applied to the most important features, selected according to a committee composed of feature importance algorithms.RESULTS: The results showed that the best outcomes were obtained using the logistic regression classifier, with the features selected by the attribute importance committee.CONCLUSIONS: It is not possible to use the system developed as a diagnostic tool at this point, due to the small amount of data. However, the results were good in terms of classification. Furthermore, the approach of using a committee to select the most important clinical features improved the results. The results obtained in this project can serve as an initial starting point for future research on diagnostic systems for ostomy patients.","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"20 S4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113957231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of Wheelchair Orientation in Human-Robot Interactions","authors":"Jessica Y. Bo, H. V. D. Van der Loos","doi":"10.1109/BIOMDLORE49470.2021.9594328","DOIUrl":"https://doi.org/10.1109/BIOMDLORE49470.2021.9594328","url":null,"abstract":"Autonomous mobile robots are being introduced in human-populated environments with increasing frequency, notably in hospitals and long-term care facilities. Ensuring safe and intuitive human robot interaction (HRI) is becoming a growing need, especially for pedestrians with mobility aids such as wheelchairs. The dynamics of wheelchair users differ from those of foot pedestrians, so accurate characterization of a wheelchair’s location and orientation for state estimation is crucial. The 2D laser scanner is a well-suited sensor for accurate distance measurements with fast computation speeds, but the sparsity of its data is often a hindrance to effective object detection. Despite so, 2D range data from laser scanners is found to be effective in the detection and orientation estimation of wheelchairs, even in cluttered environments. The range data from the scanner is pre-processed by segmenting out objects using density-based clustering. A two-step classification algorithm first identifies wheelchair candidates from segmented objects with the random forest classifier, then estimates the wheelchair’s orientation as one of six classes with a neural network. The models achieve 98% true positive rate for detection and 86% for orientation classification. The outcomes of this research can inform future works in building a real time wheelchair detection and state estimation for mobile robots.","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114762780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Maintenance of hemodialysis catheters in the intensive care unit","authors":"Z. Kuzborska, Liubov Albu","doi":"10.1109/BIOMDLORE49470.2021.9594292","DOIUrl":"https://doi.org/10.1109/BIOMDLORE49470.2021.9594292","url":null,"abstract":"Renal failure is a common complication of the acute conditions. One in five patients of the ICU (Intensive Care Unit) develop acute renal failure and 17% of them need the renal replacement therapy. Studies have shown that the use of hemofiltration in the development of acute renal failure improves patient survival. The early start of hemofiltration and the careful maintenance of hemodialysis catheters are associated with better results. Nurses face the complications in caring the hemodialysis catheters, that prologs treatment and patient care, length of stay and critically ill patients often die from the developed infections.The aim of the study was to investigate the maintenance of hemodialysis catheters in the intensive care unit: to identify the most common complications and analyze the actions of nurses aimed to reduce the risk of complications.Investigation method: Quantitative research, questionnaire. Statistical analysis of data was performed using IBM SPSS Statistics 20.0 and Excel 2010 programs. Descriptive statistical methods were used, the sample characteristics were calculated: average, percentage.Conclusions: When working with the hemofiltration patients who has the hemodialysis catheters, nurses focus on prevention of infections, completing documentation related to hemofiltration and monitoring the status of the catheter and the patient’s condition.","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132410740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Povilas Piartli, Andrius Rapalis, E. Kaniušas, L. Jankauskaite, V. Marozas
{"title":"Pain Recognition from Finger Plethysmography using Neural Networks","authors":"Povilas Piartli, Andrius Rapalis, E. Kaniušas, L. Jankauskaite, V. Marozas","doi":"10.1109/BIOMDLORE49470.2021.9594510","DOIUrl":"https://doi.org/10.1109/BIOMDLORE49470.2021.9594510","url":null,"abstract":"Pain is often mismanaged due to incorrect assessment of pain level. Currently, pain is evaluated with subjective methods only, such as pain questionnaires. It may lead to erroneous evaluation of pain level. For this reason, there is a need for objective pain evaluation. The aim of this study is to test different neural network architectures and different types of inputs derived from finger plethysmography to evaluate which type of network and input type is most suitable for objective pain detection. Photoplethysmogram signals were filtered, segmented into heartbeat pulses, and normalized in amplitude and duration. The fifty-three signal intensity and fifteen time-domain features were extracted from the pre-processed photoplethysmogram signal. Three different neural network architectures were employed with ten different types of input. Results showed that feature-based models performed better than signal-based models. All three neural networks architectures achieved a mean accuracy of 0.85 for feature-based models and 0.76 for signal-based models. Multi-layer perception neural network with 12-heartbeats averaged showed the best performance with an accuracy of 0.92. Feature-based approach and multi-layer perception neural network showed the highest accuracy, specificity, and sensitivity for pain recognition. Additional post-processing could increase model accuracy and may be used in future research.","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124266268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[BIOMDLORE 2021 Front cover]","authors":"","doi":"10.1109/biomdlore49470.2021.9594322","DOIUrl":"https://doi.org/10.1109/biomdlore49470.2021.9594322","url":null,"abstract":"","PeriodicalId":111164,"journal":{"name":"2021 International Conference BIOMDLORE","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123428162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}