Journal of Electrical Bioimpedance最新文献

{"title":"Machine learning-enhanced gesture recognition through impedance signal analysis.","authors":"Hoang Nhut Huynh, Quoc Tuan Nguyen Diep, Minh Quan Cao Dinh, Anh Tu Tran, Nguyen Chau Dang, Thien Luan Phan, Trung Nghia Tran, Congo Tak Shing Ching","doi":"10.2478/joeb-2024-0007","DOIUrl":"10.2478/joeb-2024-0007","url":null,"abstract":"<p><p>Gesture recognition is a crucial aspect in the advancement of virtual reality, healthcare, and human-computer interaction, and requires innovative methodologies to meet the increasing demands for precision. This paper presents a novel approach that combines Impedance Signal Spectrum Analysis (ISSA) with machine learning to improve gesture recognition precision. A diverse dataset that included participants from various demographic backgrounds (five individuals) who were each executing a range of predefined gestures. The predefined gestures were designed to encompass a broad spectrum of hand movements, including intricate and subtle variations, to challenge the robustness of the proposed methodology. The machine learning model using the K-Nearest Neighbors (KNN), Gradient Boosting Machine (GBM), Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) algorithms demonstrated notable precision in performance evaluations. The individual accuracy values for each algorithm are as follows: KNN, 86%; GBM, 86%; NB, 84%; LR, 89%; RF, 87%; and SVM, 87%. These results emphasize the importance of impedance features in the refinement of gesture recognition. The adaptability of the model was confirmed under different conditions, highlighting its broad applicability.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"63-74"},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11165689/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141306950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback.","authors":"Steffen Maude Fagerland, Henrik Røsholm Berntsen, Mats Fredriksen, Tor Endestad, Stavros Skouras, Mona Elisabeth Rootwelt-Revheim, Ragnhild Marie Undseth","doi":"10.2478/joeb-2024-0006","DOIUrl":"10.2478/joeb-2024-0006","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The goal of this study was to explore the development and implementation of a protocol for real-time fMRI neurofeedback (rtfMRI-nf) and to assess the potential for enhancing the selective brain activation using stimuli from Virtual Reality (VR). In this study we focused on two specific brain regions, supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Publications by other study groups have suggested impaired function in these specific brain regions in patients with the diagnoses Attention Deficit Hyperactivity Disorder (ADHD) and Tourette's Syndrome (TS). This study explored the development of a protocol to investigate if attention and contextual memory may be used to systematically strengthen the procedure of rtfMRI-nf.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We used open-science software and platforms for rtfMRI-nf and for developing a simulated repetition of the rtfMRI-nf brain training in VR. We conducted seven exploratory tests in which we updated the protocol at each step. During rtfMRI-nf, MRI images are analyzed live while a person is undergoing an MRI scan, and the results are simultaneously shown to the person in the MRI-scanner. By focusing the analysis on specific regions of the brain, this procedure can be used to help the person strengthen conscious control of these regions. The VR simulation of the same experience involved a walk through the hospital toward the MRI scanner where the training sessions were conducted, as well as a subsequent simulated repetition of the MRI training. The VR simulation was a 2D projection of the experience.The seven exploratory tests involved 19 volunteers. Through this exploration, methods for aiming within the brain (e.g. masks/algorithms for coordinate-system control) and calculations for the analyses (e.g. calculations based on connectivity versus activity) were updated by the project team throughout the project. The final procedure involved three initial rounds of rtfMRI-nf for learning brain strategies. Then, the volunteers were provided with VR headsets and given instructions for one week of use. Afterward, a new session with three rounds of rtfMRI-nf was conducted.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Through our exploration of the indirect effect parameters - brain region activity (directed oxygenated blood flow), connectivity (degree of correlated activity in different regions), and neurofeedback score - the volunteers tended to increase activity in the reinforced brain regions through our seven tests. Updates of procedures and analyses were always conducted between pilots, and never within. The VR simulated repetition was tested in pilot 7, but the role of the VR contribution in this setting is unclear due to underpowered testing.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This proof-of-concept protocol implies how rtfMRI-nf may be used to selectively train two brain regions (SMA and rIFG). The method may likely be adapted to train any given region in the brain","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"41-62"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141200537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity study of a locally developed six electrode focused impedance method.","authors":"Trilochan Khanal, K Siddique-E Rabbani","doi":"10.2478/joeb-2024-0005","DOIUrl":"10.2478/joeb-2024-0005","url":null,"abstract":"<p><p>The Focused Impedance Method (FIM) is a new technique of electrical bioimpedance measurements in the human body. The idea originated in Bangladesh and provides an opportunity for localized measurement of bioimpedance down to reasonable depths from the body surface using skin surface electrodes. This has potential applications for physiological studies of targeted organs in the body and in detecting or diagnosing diseases and disorders. FIM is based on the age-old Tetra-Polar Impedance Measurement (TPIM) but provides a few significant improvements. Technology must be developed indigenously to obtain long-term benefits, particularly in Low and Medium Income countries (LMIC). This paper presents an experimental sensitivity study of the six-electrode version of the Focused Impedance method (FIM-6) with the circuit and phantom indigenously designed in Nepal. The work involved sensitivity studies of both FIM-6 and TPIM with the necessary circuit blocks developed through experimental validation. The sensitivity studies were performed on a simple 2D phantom with different electrode arrangements for FIM-6 and linear TPIM. A cylindrical object was placed at different positions for this study. The FIM-6 gave a high sensitivity in the central part, which remained almost constant within a small region that may be termed as the focused region. On the other hand, TPIM results fell off sharply away from the central point, making it unsuitable for practical measurements on target organs. Besides, there were areas with large negative sensitivities in TPIM, which were much smaller in FIM. The results obtained through this work clearly show the improvement offered by FIM over TPIM.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"33-40"},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11042114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140867567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Concordance between dual indirect methods for assessing fat percentage.","authors":"Hurtado B, Colina E, Gonzalez-Correa C H","doi":"10.2478/joeb-2024-0004","DOIUrl":"10.2478/joeb-2024-0004","url":null,"abstract":"<p><p>In the last decades there is a growing interest in the evaluation of human body composition for being an important part of the integral assessment of individuals. Its use has been extended to different disciplines associated with health care (medicine, nutrition, physiotherapy), and to sports and population fields. Specifically, fat percentage can be related to innumerable diseases. However, there are discrepancies in the results of fat percentage measurement measured by different methods.</p><p><strong>Objective: </strong>To evaluate the concordance between two low-cost and easily accessible double indirect methods, which have been used indistinctly in different studies where access to more accurate methods is not available, and to determine fat percentage and its relationship with age, sex, body mass index (BMI), waist circumference, level of physical activity and sedentary hours.</p><p><strong>Materials and method: </strong>Twenty-four persons between 18 and 38 years and 28 between 39 and 59 years from a university community were evaluated. Calculations were made: BMI, fat % was estimated by anthropometry with a digital adipometer (Skyndex System I USA) and by Electrical Bioimpedance Analysis - BIA (Biody Expert ZM II FRA), physical activity level and sedentary hours were determined with the short IPAQ questionnaire. Pearson's correlation coefficient, Bland & Altman's graphical method and Lin's concordance correlation index were calculated. The significance level p<0.05 was estimated.</p><p><strong>Results: </strong>The fat percentage by anthropometry was: 30.5% ±8.5 (18-38 years) 35.0% ±6.7 (39-59 years); by BIA 27.0% ±7.3 (18-38 years) and 29.2% ±7.0 (39-59 years). Both techniques showed good correlation, but low degree of concordance (Lin index less than 0.9) except for the group of young persons with moderate level of physical activity (0.95).</p><p><strong>Conclusions: </strong>The doubly indirect methods used in the study showed strong correlation, but low concordance, so their use is not recommended indistinctly for the follow-up of a particular case. According to the study data for this specific population in young people with moderate physical activity, follow-up could be performed with either of the two methods.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"26-32"},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10996899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140869242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rheoencephalography: A non-invasive method for neuromonitoring.","authors":"Sandor Szabo, Zsolt Totka, Jozsef Nagy-Bozsoky, Istvan Pinter, Mihaly Bagany, Michael Bodo","doi":"10.2478/joeb-2024-0003","DOIUrl":"10.2478/joeb-2024-0003","url":null,"abstract":"<p><p>In neurocritical care, the gold standard method is intracranial pressure (ICP) monitoring for the patient's lifesaving. Since it is an invasive method, it is desirable to use an alternative, noninvasive technique. The computerized real-time invasive cerebral blood flow (CBF) autoregulation (AR) monitoring calculates the status of CBF AR, called the pressure reactivity index (PRx). Studies documented that the electrical impedance of the head (Rheoencephalography - REG) can detect the status of CBF AR (REGx) and ICP noninvasively. We aimed to test REG to reflect ICP and CBF AR. For nineteen healthy subjects we recorded bipolar bifrontal and bitemporal REG derivations and arm bioimpedance pulses with a 200 Hz sampling rate. The challenges were a 30-second breath-holding and head-down-tilt (HDT - Trendelenburg) position. Data were stored and processed offline. REG pulse wave morphology and REGx were calculated. The most relevant finding was the significant morphological change of the REG pulse waveform (2^nd peak increase) during the HDT position. Breath-holding caused REG amplitude increase, but it was not significant. REGx in male and female group averages have similar trends during HDT by indicating the active status of CBF AR. The morphological change of REG pulse wave during HDT position was identical to ICP waveform change during increased ICP, reflecting decreased intracranial compliance. A correlation study between ICP and REG was initiated in neurocritical care patients. The noninvasive REG monitoring would also be useful in space research as well as in military medicine during the transport of wounded service members as well as for fighter pilots to indicate the loss of CBF and consciousness.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"10-25"},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936697/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140120948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the effect of several moisturizing creams using the low frequency electrical susceptance approach.","authors":"Dindar S Bari, Zana K Ali, Soleen A Hameed, Haval Y Yacoob Aldosky","doi":"10.2478/joeb-2024-0002","DOIUrl":"10.2478/joeb-2024-0002","url":null,"abstract":"<p><p>Moisturizers are cosmetic compounds designed to increase the moisture content of the skin. There are many types of these products in the market making it difficult for consumers to select the most effective moisturizer according to their age and gender. Hence, the aim of this study was to evaluate the effects of different moisturizers on skin hydration as well as to figure out any dependencies of the effects of these products on age or gender-related differences. We investigated the short-term moisturizing effects of five different skin moisturizers on 60 participants by using a low frequency electrical instrument. Skin surface susceptance was recorded and compared before and after the application of moisturizers. Statistically significant differences were observed in the moisturizing effect among different types of products. However, with respect to gender and age differences, there were insignificant differences in the effects of the moisturizers. Results of this study suggest that some types of moisturizers that exist in the markets are not as effective as required, which calls for a further evaluation of the moisturizers before entering markets and offering them for sale. In addition, findings suggest that gender or age differences are perhaps not important to consider in the application of moisturizers.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"4-9"},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10896182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139973892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrical bioimpedance in the era of artificial intelligence.","authors":"Jie Hou, Naimahmed Nesaragi, Christian Tronstad","doi":"10.2478/joeb-2024-0001","DOIUrl":"10.2478/joeb-2024-0001","url":null,"abstract":"","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"15 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10830329/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139674056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of physiological concentrations of GABA using dielectric spectroscopy - A pilot study.","authors":"Jie Hou, Runar Strand-Amundsen, Ørjan G Martinsen","doi":"10.2478/joeb-2023-0006","DOIUrl":"10.2478/joeb-2023-0006","url":null,"abstract":"<p><p>Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter that is present at a relatively low level throughout the normal adult human brain. Abnormal GABA levels are found in people with neurodegenerative disorders such as Parkinson's disease, epilepsy, schizophrenia, depression, and others. Being able to measure the GABA concentration would be beneficial for patient groups with fluctuating GABA levels for better diagnosis and treatment. In this study, we explore the feasibility of using dielectric relaxation spectroscopy for the detection of GABA concentrations within a physiological range, with the perspective of miniaturization and use during implantation. Utilizing machine learning techniques, we were able to differentiate GABA concentrations down to 5 μm. This work investigates a novel use of dielectric relaxation spectroscopy, to assess if physiological GABA concentrations can be detected through permittivity measurements.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"14 1","pages":"47-52"},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10750319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139075332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing biomedical engineering: Leveraging Hjorth features for electroencephalography signal analysis.","authors":"Wissam H Alawee, Ali Basem, Luttfi A Al-Haddad","doi":"10.2478/joeb-2023-0009","DOIUrl":"10.2478/joeb-2023-0009","url":null,"abstract":"<p><p>Biomedical engineering stands at the forefront of medical innovation, with electroencephalography (EEG) signal analysis providing critical insights into neural functions. This paper delves into the utilization of EEG signals within the MILimbEEG dataset to explore their potential for machine learning-based task recognition and diagnosis. Capturing the brain's electrical activity through electrodes 1 to 16, the signals are recorded in the time-domain in microvolts. An advanced feature extraction methodology harnessing Hjorth Parameters-namely Activity, Mobility, and Complexity-is employed to analyze the acquired signals. Through correlation analysis and examination of clustering behaviors, the study presents a comprehensive discussion on the emergent patterns within the data. The findings underscore the potential of integrating these features into machine learning algorithms for enhanced diagnostic precision and task recognition in biomedical applications. This exploration paves the way for future research where such signal processing techniques could revolutionize the efficiency and accuracy of biomedical engineering diagnostics.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"14 1","pages":"66-72"},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10750318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139075331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smart needle electrical bioimpedance to provide information on needle tip relationship to target nerve prior to local anesthetic deposition in peripheral nerve block (USgPNB) procedures.","authors":"Edel Whelton, Lisa Helen, Brian O'Donnell, Martin O'Sullivan, Justina Ugwah, Walter Messina, Yineng Wang, Niamh O'Mahoney, Eric Moore","doi":"10.2478/joeb-2023-0007","DOIUrl":"10.2478/joeb-2023-0007","url":null,"abstract":"<p><p>Ultrasound guided peripheral nerve block (USgPNB) refers to anaesthetic techniques to deposit local anesthetic next to nerves, permitting painful surgery without necessitating general anesthesia. Needle tip position prior to local anesthetic deposition is a key determinant of block success and safety. Nerve puncture and intra-neural injection of local anesthetic can cause permanent nerve injury. Currently ultrasound guidance is not sufficiently sensitive to reliably detect needle to nerve proximity. Feedback with bioimpedance data from the smart needle tip might provide the anesthetist with information as to the relationship between the needle tip and the target nerve prior to local anesthetic deposition. Bioimpedance using a smart needle integrated with a two-electrode impedance sensor has been developed to determine needle to nerve proximity during USgPNB. Having obtained all necessary ethical and regulatory approvals, <i>in vivo</i> data on brachial plexus, vagus, femoral and sciatic nerves were obtained from seven pig models using the smart needle bioimpedance system. The excision and histological analysis of above peripheral nerves and observation of the architecture and structure of nerves by means of histology allow the calculation of the ratios of connective tissue to neural tissue to determine the influence of this variable on absolute impedance. The ratio results give extra clinical data and explain the hetrogeneity of impedance data in the pig models and the hypothesis that connective tissue with intra-neural fat has higher impedance than neural tissue.</p>","PeriodicalId":38125,"journal":{"name":"Journal of Electrical Bioimpedance","volume":"14 1","pages":"53-59"},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10750317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139075333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}