Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856562
H. Durmuş, Emel Çetin Ari, B. Karaböce, M. Seyidov
In this study, we experimentally investigated the effects of temperature and optical power of an LED therapy device within a tissue phantom and on its surface. We attempted to ascertain the effects of LED lights of different colors, such as red, yellow, green, blue, orange, and purple, situated at the LED therapy device on the surface and within the agar phantom. We formed a temperature effect on the agar phantom via the LED therapy device at 20, 40, and 60 minutes intervals. The temperature measurements were performed using a thermocouple placed at the surface and within the agar phantom. Furthermore, the relationships between the obtained internal temperatures of each LED light of different colors and the determined surface temperatures of each LED light of different colors were statistically analyzed, discussed, and evaluated. In addition, as well as to characterize the agar phantom optically and acoustically, optical power measurements were also made under different LED lights at the phantom surface level. This study aimed to investigate the temperature and optical power effects of an LED therapy device on a well-characterized tissue-mimicking phantom prior to clinical application. The results of this study indicate that the LED therapy device examined is safe and harmless for daily use, particularly in terms of temperature and related optical power effects.
{"title":"Experimental Evaluation of Temperature and Optical Power Generated by a LED Therapy Device on an Agar Phantom","authors":"H. Durmuş, Emel Çetin Ari, B. Karaböce, M. Seyidov","doi":"10.1109/MeMeA54994.2022.9856562","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856562","url":null,"abstract":"In this study, we experimentally investigated the effects of temperature and optical power of an LED therapy device within a tissue phantom and on its surface. We attempted to ascertain the effects of LED lights of different colors, such as red, yellow, green, blue, orange, and purple, situated at the LED therapy device on the surface and within the agar phantom. We formed a temperature effect on the agar phantom via the LED therapy device at 20, 40, and 60 minutes intervals. The temperature measurements were performed using a thermocouple placed at the surface and within the agar phantom. Furthermore, the relationships between the obtained internal temperatures of each LED light of different colors and the determined surface temperatures of each LED light of different colors were statistically analyzed, discussed, and evaluated. In addition, as well as to characterize the agar phantom optically and acoustically, optical power measurements were also made under different LED lights at the phantom surface level. This study aimed to investigate the temperature and optical power effects of an LED therapy device on a well-characterized tissue-mimicking phantom prior to clinical application. The results of this study indicate that the LED therapy device examined is safe and harmless for daily use, particularly in terms of temperature and related optical power effects.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115074367","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}
With the increasing risks of cardiovascular diseases (CVDs) all over the world, electrocardiogram (ECG) monitoring has become an important means for the timely diagnosis of CVDs. However, ECG signal can be easily disturbed by noises such as motion artifact (MA) when recorded by wearable devices in our daily life. To eliminate these noises in ECG signal, a denoising algorithm based on multi-threshold stationary wavelet transform (SWT), called MT-SWT, is proposed. We first propose a QRS complex detection algorithm based on joint threshold judgement to accurately separate the QRS complex from the other waves of ECG signals. Then, taking historical ECG signals when the human body is static as the reference signals, we set multiple thresholds for different SWT coefficients and different parts of ECG signals respectively. Finally, for a section of the input ECG signal, each SWT coefficient is processed by a given soft thresholding function for denoising. We compare MT-SWT with other algorithms based on MIT-BIH datasets, and also implement it in real-world ECG monitoring wearable devices. The experimental results show that compared with the state-of-the-arts, MT-SWT achieves higher accuracy on QRS complex detection under the condition of low signal-to-noise ratio (SNR). Moreover, MT-SWT achieves high SNR improvement ($SNR_{imp}$) and low percent root mean square difference ($PRD$) under different SNR conditions.
{"title":"Electrocardiogram Signal Denoising Based on Multi-Threshold Stationary Wavelet Transform","authors":"Huyang Peng, Yongrui Chen, Donglin Shi, Fengling Xie","doi":"10.1109/MeMeA54994.2022.9856544","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856544","url":null,"abstract":"With the increasing risks of cardiovascular diseases (CVDs) all over the world, electrocardiogram (ECG) monitoring has become an important means for the timely diagnosis of CVDs. However, ECG signal can be easily disturbed by noises such as motion artifact (MA) when recorded by wearable devices in our daily life. To eliminate these noises in ECG signal, a denoising algorithm based on multi-threshold stationary wavelet transform (SWT), called MT-SWT, is proposed. We first propose a QRS complex detection algorithm based on joint threshold judgement to accurately separate the QRS complex from the other waves of ECG signals. Then, taking historical ECG signals when the human body is static as the reference signals, we set multiple thresholds for different SWT coefficients and different parts of ECG signals respectively. Finally, for a section of the input ECG signal, each SWT coefficient is processed by a given soft thresholding function for denoising. We compare MT-SWT with other algorithms based on MIT-BIH datasets, and also implement it in real-world ECG monitoring wearable devices. The experimental results show that compared with the state-of-the-arts, MT-SWT achieves higher accuracy on QRS complex detection under the condition of low signal-to-noise ratio (SNR). Moreover, MT-SWT achieves high SNR improvement ($SNR_{imp}$) and low percent root mean square difference ($PRD$) under different SNR conditions.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115365419","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}
Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856572
A. Patange, Zhihang Zhang, Ruairi Monaghan, M. Fallon, H. Humphreys, B. Tiwari, S. Daniels
Exposure to bioaerosols are associated with wide a range of public health issues. Pathogenic bioaerosols can contribute to the onset of various diseases, therefore their rapid and efficient detection is crucial to public health. Loop Mediated Isothermal Amplification (LAMP) is a highly specific and accurate nucleic acid amplification method to detect microbes. In this study, we developed a simplified LAMP assay capable of detecting microbes in aerosols with minimal chemical and processing requirements. An air sampling system was designed to efficiently collect and recover microbes in aerosols and integrate into a LAMP assay process. We demonstrated successful collection of Escherichia coli (E. coli) aerosols and detection by a colorimetric LAMP assay. It was found that the colorimetric LAMP assay detected E. coli in concentrations as low as 102 CFU/ml. This combined technology enables accurate and rapid genomic detection of bioaerosols outside of conventional laboratory settings. This work describes a fully automated colorimetric LAMP assay device, the Luremain stable for up to 4 weeks at room temperature, however this study is ongoing, and we expect a significantly longer life of the reagent.smAir LM365, for facilitating the integrated technology with easy operation. All the processes including air sampling, DNA extraction, DNA amplification and detection were integrated on this device. The cartridge design allows the device to complete several detection processes before an intervention is required by an operator. We demonstrated that E. coli contaminated water samples can be automatically detected and analysed on our LAMP assay device in approximately 60 min. Along with the automation of the device, stable and long-term storage of LAMP reagents is an important requirement. Here we also comment on a preservation method for the LAMP reagents, and we evaluate the stability of preserved reagents at ambient temperature. Our data indicate that preserved LAMP reagents can remain stable for up to 4 weeks at room temperature, however this study is ongoing, and we expect a significantly longer life of the reagent.
{"title":"Development of an Integrated Air Sampling and Loop-Mediated Isothermal Amplification (LAMP) technology for detection of bioaerosols in indoor environments","authors":"A. Patange, Zhihang Zhang, Ruairi Monaghan, M. Fallon, H. Humphreys, B. Tiwari, S. Daniels","doi":"10.1109/MeMeA54994.2022.9856572","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856572","url":null,"abstract":"Exposure to bioaerosols are associated with wide a range of public health issues. Pathogenic bioaerosols can contribute to the onset of various diseases, therefore their rapid and efficient detection is crucial to public health. Loop Mediated Isothermal Amplification (LAMP) is a highly specific and accurate nucleic acid amplification method to detect microbes. In this study, we developed a simplified LAMP assay capable of detecting microbes in aerosols with minimal chemical and processing requirements. An air sampling system was designed to efficiently collect and recover microbes in aerosols and integrate into a LAMP assay process. We demonstrated successful collection of Escherichia coli (E. coli) aerosols and detection by a colorimetric LAMP assay. It was found that the colorimetric LAMP assay detected E. coli in concentrations as low as 102 CFU/ml. This combined technology enables accurate and rapid genomic detection of bioaerosols outside of conventional laboratory settings. This work describes a fully automated colorimetric LAMP assay device, the Luremain stable for up to 4 weeks at room temperature, however this study is ongoing, and we expect a significantly longer life of the reagent.smAir LM365, for facilitating the integrated technology with easy operation. All the processes including air sampling, DNA extraction, DNA amplification and detection were integrated on this device. The cartridge design allows the device to complete several detection processes before an intervention is required by an operator. We demonstrated that E. coli contaminated water samples can be automatically detected and analysed on our LAMP assay device in approximately 60 min. Along with the automation of the device, stable and long-term storage of LAMP reagents is an important requirement. Here we also comment on a preservation method for the LAMP reagents, and we evaluate the stability of preserved reagents at ambient temperature. Our data indicate that preserved LAMP reagents can remain stable for up to 4 weeks at room temperature, however this study is ongoing, and we expect a significantly longer life of the reagent.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116872613","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}
Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856529
J. Panić, V. Giannini, Arianna Defeudis, D. Regge, G. Balestra, S. Rosati
The use of Deep Learning (DL) algorithms in the medical imaging field is increasing in recent years. However, they require the selection of a set of parameters to properly perform. In this study we evaluated the impact of three factors (the construction of the training set, the number of network layers and the loss function) on the performance of a U-Net system in the segmentation of Locally Advanced Rectal Cancer (LARC) on Magnetic Resonance Imaging (MRI). Images from 3 different institutions and 4 different scanners were used to this scope, for a total of 100 patients. All images underwent a pre-processing step to normalize and to highlight the tumoral area. The sequences of two scanners were used to construct the networks while the remaining sequences were employed for validating the best performing systems. From our results, it emerged that Dice Similarity Coefficient is not affected by any of the evaluated factors. Conversely, the choice of loss function could bias the results towards either precision or recall and, thus, it should be properly performed according to the scope of the network. Moreover, a slightly improvement of the performances was observed using a training set based on clustering, maybe due to a better representation of the heterogeneity characterizing medical images.
{"title":"Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images","authors":"J. Panić, V. Giannini, Arianna Defeudis, D. Regge, G. Balestra, S. Rosati","doi":"10.1109/MeMeA54994.2022.9856529","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856529","url":null,"abstract":"The use of Deep Learning (DL) algorithms in the medical imaging field is increasing in recent years. However, they require the selection of a set of parameters to properly perform. In this study we evaluated the impact of three factors (the construction of the training set, the number of network layers and the loss function) on the performance of a U-Net system in the segmentation of Locally Advanced Rectal Cancer (LARC) on Magnetic Resonance Imaging (MRI). Images from 3 different institutions and 4 different scanners were used to this scope, for a total of 100 patients. All images underwent a pre-processing step to normalize and to highlight the tumoral area. The sequences of two scanners were used to construct the networks while the remaining sequences were employed for validating the best performing systems. From our results, it emerged that Dice Similarity Coefficient is not affected by any of the evaluated factors. Conversely, the choice of loss function could bias the results towards either precision or recall and, thus, it should be properly performed according to the scope of the network. Moreover, a slightly improvement of the performances was observed using a training set based on clustering, maybe due to a better representation of the heterogeneity characterizing medical images.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124412855","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}
Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856519
Madison Cohen-McFarlane, Bruce Wallace, P. Xi, R. Goubran, F. Knoefel
The field of remote health monitoring is a growing field, which is being driven by the rapid advances in sensors and sensor measurement systems. The respiratory system can be affected by a variety of underlying conditions and respiratory event monitoring can provide medical professionals with information that would otherwise be unavailable. A key area of concern is respiration over the course of a night, changes in which can be indicative of breathing and sleep related disorders. Previous work has proposed the use of pressure sensitive mats (PSM) or audio measurement to independently detect these changes. However, neither the PSM measurement nor the audio measurement is able to capture all respiratory events and there are privacy concerns associated with continuous monitoring (especially when recording audio). This paper presents the feasibility of a system that would utilize both PSM and audio measurements. Here, a single participant was asked to lay down on a PSM and to perform a series of respiratory events (normal breathing, fast breathing, slow breathing, gasping, mimicking central sleep apnea, wheezing, snoring, and coughing) while a microphone was recording. Signal processing was applied to both measurements in order to investigate both breathing rate and uncommon respiratory events. The resulting signals were then compared. The advantages and disadvantages of both measurements are discussed and a sample scenario of the fusion of audio and PSM measurements is presented in order to capture obstructive sleep apnea events.
{"title":"Feasibility analysis of the fusion of pressure sensors and audio measurements for respiratory evaluations","authors":"Madison Cohen-McFarlane, Bruce Wallace, P. Xi, R. Goubran, F. Knoefel","doi":"10.1109/MeMeA54994.2022.9856519","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856519","url":null,"abstract":"The field of remote health monitoring is a growing field, which is being driven by the rapid advances in sensors and sensor measurement systems. The respiratory system can be affected by a variety of underlying conditions and respiratory event monitoring can provide medical professionals with information that would otherwise be unavailable. A key area of concern is respiration over the course of a night, changes in which can be indicative of breathing and sleep related disorders. Previous work has proposed the use of pressure sensitive mats (PSM) or audio measurement to independently detect these changes. However, neither the PSM measurement nor the audio measurement is able to capture all respiratory events and there are privacy concerns associated with continuous monitoring (especially when recording audio). This paper presents the feasibility of a system that would utilize both PSM and audio measurements. Here, a single participant was asked to lay down on a PSM and to perform a series of respiratory events (normal breathing, fast breathing, slow breathing, gasping, mimicking central sleep apnea, wheezing, snoring, and coughing) while a microphone was recording. Signal processing was applied to both measurements in order to investigate both breathing rate and uncommon respiratory events. The resulting signals were then compared. The advantages and disadvantages of both measurements are discussed and a sample scenario of the fusion of audio and PSM measurements is presented in order to capture obstructive sleep apnea events.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121383923","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}
Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856574
F. Amato, Maria Fasani, Glauco Raffaelli, Valerio Cesarini, Gabriella Olmo, N. Lorenzo, G. Costantini, G. Saggio
Automatic assessment of speech disorders is a cutting-edge topic in vocal analysis. Recent studies indicated possible connections between eating disorders and voice alterations. In this work, we assessed the influence of obesity and Gastro- Esophageal Reflux Disease (GERD) on voice, being the former a risk factor for the latter. Moreover, we investigated the mutual influence of the diseases working with a consistent set of features. To these aims, we used vocal tests from 92 subjects, with vocal tests consisting of vowel phonation and sentence repetition, and subjects including healthy controls, obese patients, patients with GERD, and obese patients with GERD. Machine Learning models, consisting of Naive Bayes and Support Vector Machine, were successfully employed on extracted features in binary classifications, resulting in 0.86 and 0.82 of accuracies on validation set in scoring the presence of GERD and obesity, respectively. The absence of performance deterioration when moving to the test set denoted a lack of overfitting. As for the tasks and the features employed, the sentence repetition proved to be more effective than the vowel phonation, while Mel Frequency Cepstral Coefficients, Perceptual Linear Prediction Coefficients, Bark Band Energy Coefficients, and noise measures appear to be among the most significant features for the application at hand.
{"title":"Obesity and Gastro-Esophageal Reflux voice disorders: a Machine Learning approach","authors":"F. Amato, Maria Fasani, Glauco Raffaelli, Valerio Cesarini, Gabriella Olmo, N. Lorenzo, G. Costantini, G. Saggio","doi":"10.1109/MeMeA54994.2022.9856574","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856574","url":null,"abstract":"Automatic assessment of speech disorders is a cutting-edge topic in vocal analysis. Recent studies indicated possible connections between eating disorders and voice alterations. In this work, we assessed the influence of obesity and Gastro- Esophageal Reflux Disease (GERD) on voice, being the former a risk factor for the latter. Moreover, we investigated the mutual influence of the diseases working with a consistent set of features. To these aims, we used vocal tests from 92 subjects, with vocal tests consisting of vowel phonation and sentence repetition, and subjects including healthy controls, obese patients, patients with GERD, and obese patients with GERD. Machine Learning models, consisting of Naive Bayes and Support Vector Machine, were successfully employed on extracted features in binary classifications, resulting in 0.86 and 0.82 of accuracies on validation set in scoring the presence of GERD and obesity, respectively. The absence of performance deterioration when moving to the test set denoted a lack of overfitting. As for the tasks and the features employed, the sentence repetition proved to be more effective than the vowel phonation, while Mel Frequency Cepstral Coefficients, Perceptual Linear Prediction Coefficients, Bark Band Energy Coefficients, and noise measures appear to be among the most significant features for the application at hand.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114555305","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}
Pub Date : 2022-06-22DOI: 10.1109/memea54994.2022.9856411
F. Simini, Isabel Morales, Natalia Garay, Darío Santos, Maria Rene Ledezma, Estefania Della Mea, Pablo Sánchez, Lucia Belen Ribeiro
Biomedical equipment has evolved from marginal auxiliaries to become central elements in patient physician relationship of today. Clinical records, once a separate item, become fully integrated as the Electronic Clinical Record with medical notes, images, monitoring, medication, lab results and life style information under the supervision of physicians. Three variants of standard biomedical equipment architecture are derived from twelve original Biomedical Equipment.
{"title":"Standard Classification of Biomedical Equipment According to Measurements, Medical Information and Electronic Clinical Records","authors":"F. Simini, Isabel Morales, Natalia Garay, Darío Santos, Maria Rene Ledezma, Estefania Della Mea, Pablo Sánchez, Lucia Belen Ribeiro","doi":"10.1109/memea54994.2022.9856411","DOIUrl":"https://doi.org/10.1109/memea54994.2022.9856411","url":null,"abstract":"Biomedical equipment has evolved from marginal auxiliaries to become central elements in patient physician relationship of today. Clinical records, once a separate item, become fully integrated as the Electronic Clinical Record with medical notes, images, monitoring, medication, lab results and life style information under the supervision of physicians. Three variants of standard biomedical equipment architecture are derived from twelve original Biomedical Equipment.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115932114","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}
Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856528
L. E. Sebar, E. Angelini, A. Baldi, A. Comba, M. Parvis, S. Grassini
The employment of innovative all-ceramic materi-als and adhesive cement, as well as the development of new bonding procedures, allow clinicians to use minimally invasive approaches in conservative restorations. In particular, dual-cure cement allows for obtaining higher aesthetic and functional results. However, the reduced light transmission through ceramic materials could prevent the proper curing and affect the adhesion of these materials to the tooth surface. In this context, the development of an accurate measurement methodology to assess the extent of polymerization of dental resin-based luting cement and to correlate the conversion degree with the mechanical properties is of particular importance from the clinical and scientific point of view. A measurement approach that exploits Raman Spectroscopy and nano-hardness measurements is hereby proposed. In particular, in this study, two different light-curing protocols are employed on a dual-cure luting cement, usually used for the full-crown restoration of single-rooted teeth. The effect of different times and tack-curing steps on the polymerization shrinkage of resin-based luting cement is investigated. The pre-liminary results allow concluding that both curing protocols lead to a good polymerization, without significant differences in the degree of conversion along the cement-tooth interfacial surface, as proved by the almost constant ratio of the Raman vibration characteristic peaks. However, the nanoindentation modulus was lower in the case of the tack-cured protocol.
{"title":"Nanoindentation and Raman spectroscopy measurements on dual-cure luting cement for dental conservative restoration","authors":"L. E. Sebar, E. Angelini, A. Baldi, A. Comba, M. Parvis, S. Grassini","doi":"10.1109/MeMeA54994.2022.9856528","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856528","url":null,"abstract":"The employment of innovative all-ceramic materi-als and adhesive cement, as well as the development of new bonding procedures, allow clinicians to use minimally invasive approaches in conservative restorations. In particular, dual-cure cement allows for obtaining higher aesthetic and functional results. However, the reduced light transmission through ceramic materials could prevent the proper curing and affect the adhesion of these materials to the tooth surface. In this context, the development of an accurate measurement methodology to assess the extent of polymerization of dental resin-based luting cement and to correlate the conversion degree with the mechanical properties is of particular importance from the clinical and scientific point of view. A measurement approach that exploits Raman Spectroscopy and nano-hardness measurements is hereby proposed. In particular, in this study, two different light-curing protocols are employed on a dual-cure luting cement, usually used for the full-crown restoration of single-rooted teeth. The effect of different times and tack-curing steps on the polymerization shrinkage of resin-based luting cement is investigated. The pre-liminary results allow concluding that both curing protocols lead to a good polymerization, without significant differences in the degree of conversion along the cement-tooth interfacial surface, as proved by the almost constant ratio of the Raman vibration characteristic peaks. However, the nanoindentation modulus was lower in the case of the tack-cured protocol.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129001575","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}
Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856412
S. Arlati, N. Keijsers, G. Paolini, G. Ferrigno, M. Sacco
Immersive virtual reality (VR) represents a viable technology to support rehabilitation and promote the recovery of upper limb functions after stroke. Nonetheless, it has not been determined yet if VR can elicit movements that share the same kinematic characteristics of those occurring in the real world (RW), thus positively impacting arm use in daily life. A previous study enrolling young adults showed promising results: joints' ranges of motion were preserved, although movement times were longer and peak velocity lower in VR. Starting from these results, this work aimed at comparing young and older adults' (i.e., an age-matched sample to stroke survivors) upper limb kinematics while performing aimed movements in RW and immersive VR. The presented study was a within-subject repeated-measures design in which participants had to reach, grasp and transport grocery items from a simplified supermarket shelf unit. The VR condition was performed using an HTC Vive head-mounted display; its controller was used to interact with virtual objects. Three conditions were tested: VR, RW, and RW while holding the controller (RWC, to account for carrying a weight). Ten healthy young adults $(26.7pm 5.46$ and three older adults $(69.0pm 2.0)$ were enrolled. The collected data showed that older adults moved slower, more curved, and reached lower peak velocity during both reaching and transfer in VR compared to young adults. Arm ranges of motion seemed to be preserved, whereas thorax movements were different. We hypothesized that these differences might be dependent on age-related vision and cognitive decline, lack of familiarity with VR technology, and lack of force feedback. Further studies are needed to address these issues and confirm or reject our hypotheses.
{"title":"Age-related differences in the kinematics of aimed movements in immersive virtual reality: a preliminary study","authors":"S. Arlati, N. Keijsers, G. Paolini, G. Ferrigno, M. Sacco","doi":"10.1109/MeMeA54994.2022.9856412","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856412","url":null,"abstract":"Immersive virtual reality (VR) represents a viable technology to support rehabilitation and promote the recovery of upper limb functions after stroke. Nonetheless, it has not been determined yet if VR can elicit movements that share the same kinematic characteristics of those occurring in the real world (RW), thus positively impacting arm use in daily life. A previous study enrolling young adults showed promising results: joints' ranges of motion were preserved, although movement times were longer and peak velocity lower in VR. Starting from these results, this work aimed at comparing young and older adults' (i.e., an age-matched sample to stroke survivors) upper limb kinematics while performing aimed movements in RW and immersive VR. The presented study was a within-subject repeated-measures design in which participants had to reach, grasp and transport grocery items from a simplified supermarket shelf unit. The VR condition was performed using an HTC Vive head-mounted display; its controller was used to interact with virtual objects. Three conditions were tested: VR, RW, and RW while holding the controller (RWC, to account for carrying a weight). Ten healthy young adults $(26.7pm 5.46$ and three older adults $(69.0pm 2.0)$ were enrolled. The collected data showed that older adults moved slower, more curved, and reached lower peak velocity during both reaching and transfer in VR compared to young adults. Arm ranges of motion seemed to be preserved, whereas thorax movements were different. We hypothesized that these differences might be dependent on age-related vision and cognitive decline, lack of familiarity with VR technology, and lack of force feedback. Further studies are needed to address these issues and confirm or reject our hypotheses.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128100930","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}
Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856444
Vinothini Selvaraju, P. Karthick, S. Ramakrishnan
Preterm birth (gestational age <37 weeks) is one of the most critical global concerns that causes maternal and fetal morbidity and mortality. Early detection of this condition allows for timely intervention to delay labor by providing tocolytic drugs and rest. The objective of this work is to explore the cyclostationary behavior in electrohysterography (EHG) signals and to predict preterm conditions. The signals recorded prior to the 26 weeks of pregnancy are considered in this work. It is pre-processed using Butterworth bandpass filters to remove artifacts. The fast Fourier transform accumulation method (FAM) is applied to the pre-processed signals to estimate the spectral correlation density (SCD). The degree of cyclostationarity (DCS) is calculated from SCD to evaluate the presence of cyclostationarity in the signals. Features, such as mean, variance, cyclic frequency spectral area (CFSA), and full width half maximum (FWHM), are extracted from the spectra and statistically analyzed. The results illustrate that SCD and DCS confirm the existence of cyclostationarity in EHG signals. All the extracted features are observed to decrease in preterm conditions. This might be due to the increased coordination that is reflected in the signal in terms of reduced frequency components. Further, extracted features are found to have statistical significance (p < 0.05) in discriminating both the conditions. Thus, it appears that cyclostationary features might be clinically beneficial in the early prediction of preterm birth.
{"title":"Spectral Correlation Density based Electrohysterography Signal Analysis for the Detection of Preterm Birth","authors":"Vinothini Selvaraju, P. Karthick, S. Ramakrishnan","doi":"10.1109/MeMeA54994.2022.9856444","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856444","url":null,"abstract":"Preterm birth (gestational age <37 weeks) is one of the most critical global concerns that causes maternal and fetal morbidity and mortality. Early detection of this condition allows for timely intervention to delay labor by providing tocolytic drugs and rest. The objective of this work is to explore the cyclostationary behavior in electrohysterography (EHG) signals and to predict preterm conditions. The signals recorded prior to the 26 weeks of pregnancy are considered in this work. It is pre-processed using Butterworth bandpass filters to remove artifacts. The fast Fourier transform accumulation method (FAM) is applied to the pre-processed signals to estimate the spectral correlation density (SCD). The degree of cyclostationarity (DCS) is calculated from SCD to evaluate the presence of cyclostationarity in the signals. Features, such as mean, variance, cyclic frequency spectral area (CFSA), and full width half maximum (FWHM), are extracted from the spectra and statistically analyzed. The results illustrate that SCD and DCS confirm the existence of cyclostationarity in EHG signals. All the extracted features are observed to decrease in preterm conditions. This might be due to the increased coordination that is reflected in the signal in terms of reduced frequency components. Further, extracted features are found to have statistical significance (p < 0.05) in discriminating both the conditions. Thus, it appears that cyclostationary features might be clinically beneficial in the early prediction of preterm birth.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129900488","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}
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