2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)最新文献

{"title":"A case study about the load effect on the mechanical performances in a commercial WBV platform for clinical applications","authors":"F. Orsini, A. Scorza, C. Foti, A. Rossi, M. Sollini, S. Conforto, Simone Ranaldi, F. Vurchio, S. Sciuto, Fabio Fuiano, F. Botta","doi":"10.1109/MeMeA49120.2020.9137146","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137146","url":null,"abstract":"The use of whole body vibration (WBV) platforms in neuromuscular studies has grown in the last years, especially for the interest of the technique in fields such as rehabilitation and sport training. Different studies have dealt with the correlation between biological effect and frequency or acceleration magnitude, but little has been told regarding the influence of the applied weight on the performances of WBV plates. In this work a commercial WBV platform, has been tested with different loads measuring the accelerations of the footboard. The results show that the system has a reduction of the mean acceleration at high loads, although the variability of the system response at fixed load is noticeable. The high variability is then an actual and very challenging issue and an in-depth characterization of the WBV plates must be done before making reproducible studies on the biological effect of vibrations in clinical applications.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127812325","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":"Bedding waveguide for smartphone-based ballistocardiography","authors":"Guillaume Cathelain, J. Bergounioux, F. Jouen","doi":"10.1109/MeMeA49120.2020.9137272","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137272","url":null,"abstract":"Ballistocardiography (BCG), a contactless heart rate monitoring method, has the potential to measure vital signs and reduce neonates’ monitoring pain and discomfort. It uses an accelerometer on the mattress side. However, the bedding and bed frame nature may alter the propagation of the ejection force to the sensor, especially in case of viscous foam or damping medical beds. As neonates have a weaker ejection force than adults, heartbeats are sometimes undetectable with usual BCG systems.The contribution of the bedding nature to the BCG amplitude is investigated and a waveguide bedding is designed to amplify the BCG signal: a healthy adult volunteer is asked to rest in supine position on a bed. A contactless accelerometer records the BCG for one minute on the bed surface, twenty centimeters away from the thorax. Amplitude of heartbeats are compared for different waveguide beddings, with or without a mattress cover. Another experimentation applies this principle with a smartphone that includes an accelerometer without any hardware amplification, in comparison with a usual BCG system. The selected waveguides beddings significantly amplify up to 50 % the smallest heartbeats in the BCG signal. The smartphone BCG was also amplified with the waveguide bedding and heartbeats could be detected.The choice of bedding and bed frame must be considered for BCG measurement systems. Waveguides beddings amplify the ejection force generated during systole and offer opportunities to develop a smartphone-based contactless monitoring method for the mechanical cardiac activity of neonates.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124729977","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":"Heart rate monitoring under stress condition during behavioral analysis in children with neurodevelopmental disorders","authors":"L. D’Alvia, E. Pittella, F. Fioriello, Andrea Maugeri, E. Rizzuto, E. Piuzzi, C. Sogos, Z. Prete","doi":"10.1109/MeMeA49120.2020.9137306","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137306","url":null,"abstract":"Monitoring physiological parameters under stress conditions – i.e., heart rate, breath frequency or heart rate variability - through non-invasive and comfortable wearable devices was a research topic of great interest in many medical fields. In the last decade, several wearable devices and methods have been developed for stress monitoring, showing suitable performance in estimating the stress indicator. In spite of the interest in the field, the development of wearable solutions suitable for child neuropsychiatry applications was still an open challenge. In this study, we evaluate the cardiac activity in children - with and without neurodevelopmental disorders - through a novel wearable solution in order to compare the stress response in different structured activities and games. Each subject was equipped with a 3-lead electrocardiograph device and a piezoelectric respiratory sensor embedded into a thoracic belt. Subjects were asked to carry out five different activities previously chosen from a subset of specific behavioral tests (three different free-games and two structured activities). All experimental sessions were video-recorded. Results highlighted how wearable devices could help in estimating stress indicators for long-tests (over twenty-five minutes). The clinical application was conducted on a cohort of 32 children so divided: 13 with Specific Language Disorder, 15 with Autism Spectrum Disorder, and 4 control children without neurodevelopmental disorders. Statistical differences were observed between populations in the heart rate. Moreover, all subjects experienced stress effects evidenced by variation of heart rate and standard deviation, which are supported by the video analysis.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116106593","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":"Deep Melanoma classification with K-Fold Cross-Validation for Process optimization","authors":"Yali Nie, L. D. Santis, M. Carratù, M. O’nils, P. Sommella, J. Lundgren","doi":"10.1109/MeMeA49120.2020.9137222","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137222","url":null,"abstract":"Deep convolution neural networks (DCNNs) enable effective methods to predict the melanoma classes otherwise found with ultrasonic extraction. However, gathering large datasets in local hospitals in Sweden can take years. Small datasets will result in models with poor accuracy and insufficient generalization ability, which has a great impact on the result. This paper proposes to use a K-Fold cross validation approach based on a DCNN algorithm working on a small sample dataset. The performance of the model is verified via a Vgg16 extracting the features. The experimental results reveal that the model built by the approach proposed in this paper can effectively achieve a better prediction and enhance the accuracy of the model, which proves that K-Fold can achieve better performance on a small skin cancer dataset.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127491143","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":"A Deep Learning Approach for Mood Recognition from Wearable Data","authors":"Giuseppe Romano Tizzano, M. Spezialetti, Silvia Rossi","doi":"10.1109/MeMeA49120.2020.9137218","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137218","url":null,"abstract":"Emotion and mood recognition plays a key role in human-robot interaction, especially in the context of socially assistive robotics. Mood-aware robots could be useful as companions and social assistants for elders and people affected by depression and other mood disorders. An interesting option for continuously tracking a user's mood is the use of wearable and mobile devices. However, the classification of the mood from physiological and kinematics data is still a challenge, due to intersubjects differences: on one hand, \"one-fits-all\" classification approaches usually achieve lower accuracy than person-specific methods; on the other hand, personalized models require in general a large amount of data from a single subject to be trained and, therefore, becomes effective after long periods of acquisition. In this paper, we propose a deep learning approach for mood recognition from a publicly available dataset that includes a gyroscope, accelerometer, and heart-rate data. We propose the use of long-short term memory networks (LSTM), testing them both as classifiers and as features extractors in hybrid models. We compared their performances both against and in conjunction with traditional machine learning approaches, namely support vector machines (SVM) and Gaussian mixture models (GMM). We also consider transfer learning strategies to reduce the amount of personal data needed to train the model. Our results show that the use of LSTMs significantly improves the classification accuracy with respect to machine learning approaches, especially if employed as feature extractors and combined with SVM. However, we observed that transfer learning does not achieve significant results in boosting the training of a personalized model.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128516536","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":"Experimental Development and Validation of an E-Textile Sock Prototype","authors":"F. Amitrano, L. Donisi, A. Coccia, A. Biancardi, G. Pagano, G. D'Addio","doi":"10.1109/MeMeA49120.2020.9137302","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137302","url":null,"abstract":"SWEET Sock is a wearable prototype device designed as a sensorized sock in E-Textile, which allows the acquisition of plantar pressure and acceleration signals deriving from the motion of the lower limbs. Aim of this study is to validate the device, comparing its collected data to the ones obtained by standard instrument used in clinical environment. Accelerometric signals recorded by Sweet Sock have been compared with those obtained by the inertial system Opal by APDM, while Zebris baropodometric platform by FDM has been used as the reference system to validate pressure signals. Bland-Altman analysis has been used to assess benchmarking. Both for accelerometric and pressure signals, no systematic or proportional difference between the devices has been carried out, resulting that reliable measures can be obtained with the prototype device.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128531463","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":"Organic substrates for novel printed sensors in neural interfacing: a measurement method for cytocompatibility analysis","authors":"Sarah Tonello, G. Giorgi, S. Pisu, A. Cester","doi":"10.1109/MeMeA49120.2020.9137118","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137118","url":null,"abstract":"Advances in bioelectronics as interdisciplinary field combining electronics with novel materials for targeting biological monitoring have brought a strong acceleration in the development of sensors for neural interfaces. However, the success of any implantable device comes along with properties such as long-term stability and optimal cytocompatibility. Thus, the need to improve the reliability and reproducibility of quantitative methods for analyzing and comparing cells-substrate interaction of novel heterogeneous materials has become more and more compelling. To this aim, a systematization of the approach to analyze cytocompatibility assays appears as important as the standardization of the acquisition conditions themselves.. In this picture, the paper proposes a user-friendly toolbox able to improve the reliability of the analysis of fluorescence images from cultured organic materials. The first section, allowing a proper customization of several parameters, performs an optimal automatized segmentation of the image with an adaptive threshold strategy, evaluating cell parameters distribution on the substrate. The second one estimates the uncertainty in the evaluation of cell number and provides cell density maps at different scales. The comparison among different organic semiconductors demonstrated the possibility to use the software to compare the effect of different materials on cell parameters. Future works will address the correlation of those results from cell imaging with correspondent maps of the most peculiar properties of each cultured substrate.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131781028","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":"A Study on the Subject and Location Specificity in Reflectance based SpO2 Estimation using R-value based Calibration Curve","authors":"Arsath P. S. Mohamed Tanveejul, Alex Annamol, S. Preejith, D. J. Christopher, T. Balamugesh, S. Chandy, J. Joseph, M. Sivaprakasam","doi":"10.1109/MeMeA49120.2020.9137227","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137227","url":null,"abstract":"Design and development of an accurate and reliable pulse oximeter depend on various critical components ranging from sensors, cabling and electronics, signal processing, value estimation and informing the results to the caretaker in a timely manner. Starting from the optical interface between the sensor and tissues, optical, mechanical and electrical design of the sensor and sensor calibration serves as the building block of pulse oximetry technology. In this paper, we present the analysis of reflectance Photoplethysmogram (PPG) signals acquired using a custom-built data acquisition platform in a clinical setting on 28 subjects suffering from various pulmonary disorders. The paper mainly focuses on the feasibility of using R-value for blood oxygen saturation level (SpO2) measurement using reflectance PPG signals, which is a widely accepted method. All analysis in this study is done using a NellcorTM transmittance probe as the reference. R-value obtained from reflectance PPG signals shows a correlation coefficient of 0.9 and above against the R-value computed from transmittance PPG signals for individual subjects on a specific location. The reflectance PPG based R-value is analyzed over the 28 subjects to determine the trend in variations over the entire subject population and measurement sites. R-value is subject-specific and is also heavily dependent on the measurement site. The analysis carried out shows that the usage of a generic R-value based calibration model for computing SpO2 using reflectance PPG signals from various measurement sites is an erroneous approach.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125634929","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":"MeMeA 2020 Cover Page","authors":"","doi":"10.1109/memea49120.2020.9137279","DOIUrl":"https://doi.org/10.1109/memea49120.2020.9137279","url":null,"abstract":"","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133918261","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":"iQPrep Kit: A milli-fluidic test kit for immunodiagnostics","authors":"Ramdayalan Kumarasami, J. Joseph, Jayaraman Kiruthi Vasan, S. Pandidurai, Prabhakar Sithambaram, M. Sivaprakasam","doi":"10.1109/MeMeA49120.2020.9137129","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137129","url":null,"abstract":"Conventional laboratory-based diagnostics require highly sophisticated equipment to multiplex and analyze samples at scale. Recent advances in Point-of-care diagnostic devices have enabled rapid and accurate diagnosis on site leading to timely confirmation and effective management of individual and community health. A key enabler of such advancements is the simple to use lateral flow immunoassays that provide quick and accurate qualitative and semi-quantitative results. Typical lateral flow tests have sample preparation steps before deposition on the test membrane. Sample preparation by manual means is time-consuming and error-prone. The iQPrep Kit handles sample preparation using milli-fluidic channels and utilizes lateral flow test kits to quantitatively evaluate key immunological markers like HbA1c, Vitamin D, and TSH. The test kit design enables quick prototyping using 3D printing and can easily be mass-produced using injection molding. The functional performance of the kit was verified using a pneumatic system. The average fluid loss during fluid transport is around 7 µl using the pneumatic system. Repeatability tests were done to check if comparable amounts of fluid were transported for the same operating conditions. The coefficient of variation for the above test ranged between 2.1 % and 5.6 %. A quadratic relation was obtained between the fluid flow rate and the syringe air pressure for the multi-material valves within the kit. The quadratic fit had R2 values of 0.996 and 0.977 for the multichannel and dispensing valves, respectively. The multichannel and dispensing valves can withstand syringe air pressure of up to 2.1 kPa and 1.9 kPa, respectively, during fluid flow, before leaking. When the valves are closed, they can withstand a pressure of 1.3 kPa for 2 sec. An HbA1c test was done by manual sample preparation and using the kit. The results were similar in both cases establishing the accurate sample preparation capability of the kit. The iQPrep Kit is hence, a versatile test platform for immunodiagnostics.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134085900","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}