Pub Date : 2022-06-22DOI: 10.1109/MeMeA54994.2022.9856475
Luisa Ruiz-Ruiz, Fernando Seco Granja, A. R. Jiménez, Sara Garcia, J. J. García
In the elderly, there are several pathologies that can be identified from gait parameters such as frailty, fall risk and cognitive decline. Gait analysis is a successful method for the detection and diagnosis of gait-related diseases, being Inertial Measurement Units (IMUs) one of the most widely used (low cost, accuracy and portability). In this work, we analyse the accuracy of gait parameters estimation using a commercial IMU (Physilog 6S from GaitUp) versus the Optitrack System as gold standard. We carry out an in-depth comparison of the gait parameters obtained using the manufacturer software (GaitUp Lab) and our own algorithms based on an inertial navigation with zero velocity update at stance algorithm (INS- ZUPT). Several tests were performed by 2 healthy subjects walking in different ways (normal, high step, dragging the feet and feet drop).
{"title":"Evaluation of gait parameter estimation accuracy: a comparison between commercial IMU and optical capture motion system","authors":"Luisa Ruiz-Ruiz, Fernando Seco Granja, A. R. Jiménez, Sara Garcia, J. J. García","doi":"10.1109/MeMeA54994.2022.9856475","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856475","url":null,"abstract":"In the elderly, there are several pathologies that can be identified from gait parameters such as frailty, fall risk and cognitive decline. Gait analysis is a successful method for the detection and diagnosis of gait-related diseases, being Inertial Measurement Units (IMUs) one of the most widely used (low cost, accuracy and portability). In this work, we analyse the accuracy of gait parameters estimation using a commercial IMU (Physilog 6S from GaitUp) versus the Optitrack System as gold standard. We carry out an in-depth comparison of the gait parameters obtained using the manufacturer software (GaitUp Lab) and our own algorithms based on an inertial navigation with zero velocity update at stance algorithm (INS- ZUPT). Several tests were performed by 2 healthy subjects walking in different ways (normal, high step, dragging the feet and feet drop).","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"54 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":"121363204","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/MeMeA54994.2022.9856504
Riccardo Nicola, G. L. Cerone, M. Caruso, Rachele Rossanigo, A. Cereatti, T. Vieira
Surface electromyograms (EMGs) have been often used to study muscle function in locomotor activities. Typically, EMGs are sampled with a single pair of electrodes, providing information on the timing and degree of muscle excitation. Additional information may be obtained when sampling EMGs with multiple electrodes from the same, target muscles. Studies using high-density EMGs (HD-EMGs) in locomotor activities are limited to laboratory settings and low speed tasks, likely due to the technical shortcomings in the commercially available systems for high-density recordings. This issue is further aggravated when kinematics data are necessary for associating EMGs with events of interest during the movement cycle. By combining two systems, ad hoc developed for the on-field recording of kinematics data and HD-EMGs, here we present single-case results during extreme-speed locomotion-the 80 m sprint on an official, athletic track. Our aim was to verify whether descriptors of quality documented in the EMG literature during well-controlled, isometric contractions, apply to the HD-EMGs we detected and segmented with respect to the running cycles. From a single, elite sprinter, we were able to obtain HD-EMGs with negligible movement artifacts and with temporal profiles typically characterizing action potentials of single motor units. Our results would seem to advocate the possibility of using HD-EMG to study muscle function during highly dynamic contractions outside the laboratory settings.
{"title":"On the Detection of High-Quality, High-Density Electromyograms During 80m Sprints: a Case Study","authors":"Riccardo Nicola, G. L. Cerone, M. Caruso, Rachele Rossanigo, A. Cereatti, T. Vieira","doi":"10.1109/MeMeA54994.2022.9856504","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856504","url":null,"abstract":"Surface electromyograms (EMGs) have been often used to study muscle function in locomotor activities. Typically, EMGs are sampled with a single pair of electrodes, providing information on the timing and degree of muscle excitation. Additional information may be obtained when sampling EMGs with multiple electrodes from the same, target muscles. Studies using high-density EMGs (HD-EMGs) in locomotor activities are limited to laboratory settings and low speed tasks, likely due to the technical shortcomings in the commercially available systems for high-density recordings. This issue is further aggravated when kinematics data are necessary for associating EMGs with events of interest during the movement cycle. By combining two systems, ad hoc developed for the on-field recording of kinematics data and HD-EMGs, here we present single-case results during extreme-speed locomotion-the 80 m sprint on an official, athletic track. Our aim was to verify whether descriptors of quality documented in the EMG literature during well-controlled, isometric contractions, apply to the HD-EMGs we detected and segmented with respect to the running cycles. From a single, elite sprinter, we were able to obtain HD-EMGs with negligible movement artifacts and with temporal profiles typically characterizing action potentials of single motor units. Our results would seem to advocate the possibility of using HD-EMG to study muscle function during highly dynamic contractions outside the laboratory settings.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"30 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":"128977136","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/MeMeA54994.2022.9856431
A. Fort, Elia Landi, Anna Lo Grasso, M. Mugnaini, E. Panzardi, V. Vignoli, Fariba Fahmideh Mahdizadeh, A. Magnani
The presence of bacteria forming biofilm is pervasive in our daily life and may lead to beneficial effects or, more frequently, to adverse consequences. The monitoring of the biofilm formation process and of the related physical parameters, is essential not only for the investigation of the biofilm internal structure but also because it offers the possibility to take prompt actions to either control or counteract the growth process. In this paper the measurement problem related to the real-time monitoring of biofilm growth through Quartz Crystal Microbalance (QCM) is analyzed. After a theoretical analysis, experimental data are discussed, consisting in the long-term monitoring of the activity of Pseudomonas fluorescens bacteria. The developed prototype measurement system is based on a Mecham bridge oscillator topology and allows to accurately monitor the quartz resonance frequency and the motional resistance in real time. In particular, the bacteria adhesion process, the biofilm growth and the complex impact which has on the QCM response, related to the soft particles and media attached on the quartz surface is analyzed. The presented results demonstrate the suitability of the developed system for this kind of applications. The excellent stability and frequency resolution of the measurement system allows for the analysis of biological processes and is a useful tool for collecting information concerning the physical characteristics of the observed biological media.
{"title":"Monitoring of the Viscoelastic Behaviour of Bacterial Biofilms Exploiting an Accurate QCM System","authors":"A. Fort, Elia Landi, Anna Lo Grasso, M. Mugnaini, E. Panzardi, V. Vignoli, Fariba Fahmideh Mahdizadeh, A. Magnani","doi":"10.1109/MeMeA54994.2022.9856431","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856431","url":null,"abstract":"The presence of bacteria forming biofilm is pervasive in our daily life and may lead to beneficial effects or, more frequently, to adverse consequences. The monitoring of the biofilm formation process and of the related physical parameters, is essential not only for the investigation of the biofilm internal structure but also because it offers the possibility to take prompt actions to either control or counteract the growth process. In this paper the measurement problem related to the real-time monitoring of biofilm growth through Quartz Crystal Microbalance (QCM) is analyzed. After a theoretical analysis, experimental data are discussed, consisting in the long-term monitoring of the activity of Pseudomonas fluorescens bacteria. The developed prototype measurement system is based on a Mecham bridge oscillator topology and allows to accurately monitor the quartz resonance frequency and the motional resistance in real time. In particular, the bacteria adhesion process, the biofilm growth and the complex impact which has on the QCM response, related to the soft particles and media attached on the quartz surface is analyzed. The presented results demonstrate the suitability of the developed system for this kind of applications. The excellent stability and frequency resolution of the measurement system allows for the analysis of biological processes and is a useful tool for collecting information concerning the physical characteristics of the observed biological media.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"9 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":"129073728","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/MeMeA54994.2022.9856479
Imran Ahmed, D. L. Carní, E. Balestrieri, F. Lamonaca
Measurements of Morphometric Parameters of Blood Cells (MPBC) playa key role in haematological examination, and it is considered as one of the principal needs for clinicians in the diagnosis of various diseases in human and animals. Obliviously, the correctness of the diagnosis, and, as a consequence, the effectiveness of clinician actions is highly dependent on the accuracy of MPBC measurements. In this context, deep learning based MPBC measurement systems are a promising solution. In recent studies, researchers have applied semantic segmentation with various backbone networks for white blood cell measurements. Vice versa, few investigations were done about the achieved accuracy. Indeed, accurate segmentation of white blood cell remains a challenging task because of the complex nature of cell images, staining techniques, and imaging conditions which strongly affects the accuracy of the MPBC measurements. This paper presents a comparison among the segmentation performance carried out by U-Net deep learning algorithm with different backbones typically used for MPBC. The goal is to make a first step towards a whole MPBC measurement system capable of evaluating the effects of the influencing magnitudes, attenuate them (if possible), and evaluate the accuracy of the measurements. The aims are to increase measurement reliability and to give clinicians further information to take their decisions.
{"title":"Comparison of U -NET backbones for morphometric measurements of white blood cell","authors":"Imran Ahmed, D. L. Carní, E. Balestrieri, F. Lamonaca","doi":"10.1109/MeMeA54994.2022.9856479","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856479","url":null,"abstract":"Measurements of Morphometric Parameters of Blood Cells (MPBC) playa key role in haematological examination, and it is considered as one of the principal needs for clinicians in the diagnosis of various diseases in human and animals. Obliviously, the correctness of the diagnosis, and, as a consequence, the effectiveness of clinician actions is highly dependent on the accuracy of MPBC measurements. In this context, deep learning based MPBC measurement systems are a promising solution. In recent studies, researchers have applied semantic segmentation with various backbone networks for white blood cell measurements. Vice versa, few investigations were done about the achieved accuracy. Indeed, accurate segmentation of white blood cell remains a challenging task because of the complex nature of cell images, staining techniques, and imaging conditions which strongly affects the accuracy of the MPBC measurements. This paper presents a comparison among the segmentation performance carried out by U-Net deep learning algorithm with different backbones typically used for MPBC. The goal is to make a first step towards a whole MPBC measurement system capable of evaluating the effects of the influencing magnitudes, attenuate them (if possible), and evaluate the accuracy of the measurements. The aims are to increase measurement reliability and to give clinicians further information to take their decisions.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"32 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":"129178367","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/MeMeA54994.2022.9856500
Simone Ranaldi, S. Conforto, C. D. Marchis
When characterizing human gait control strategies, theories based on the modularity of the neuromuscular system have been proven to be powerful in providing a compact description of the gait patterns. The planar covariation law of lower limb elevation angles has been proposed as a compact, modular description of gait kinematics. In this paper, we exploit this model for characterizing healthy subjects' spatial gait parameters during walking at different speeds, one self-selected and one slightly slower than the subject's comfortable pace. Different geometrical features have been calculated over the gait loop, that is the planar loop defined by the covariation of the thigh, shank and foot elevation angles. A correlation analysis has been carried out between these features and classical gait spatial parameters (step length, step width, stride length and foot clearance) by training a linear regressor on the dataset comprising both speeds. The results from this analysis have highlighted a correlation with some spatial gait parameters across the two speed conditions, indicating that this compact description of kinematics unravels a significant biomechanical meaning. These results can be exploited to guide the control mechanisms of external assistive devices, such as prostheses or exoskeletons, based purely on the measurement of few relevant kinematic quantities of the lower limb segments.
{"title":"Estimating Spatial Gait Parameters from the Planar Covariation of Lower Limb Elevation Angles: a Pilot Study","authors":"Simone Ranaldi, S. Conforto, C. D. Marchis","doi":"10.1109/MeMeA54994.2022.9856500","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856500","url":null,"abstract":"When characterizing human gait control strategies, theories based on the modularity of the neuromuscular system have been proven to be powerful in providing a compact description of the gait patterns. The planar covariation law of lower limb elevation angles has been proposed as a compact, modular description of gait kinematics. In this paper, we exploit this model for characterizing healthy subjects' spatial gait parameters during walking at different speeds, one self-selected and one slightly slower than the subject's comfortable pace. Different geometrical features have been calculated over the gait loop, that is the planar loop defined by the covariation of the thigh, shank and foot elevation angles. A correlation analysis has been carried out between these features and classical gait spatial parameters (step length, step width, stride length and foot clearance) by training a linear regressor on the dataset comprising both speeds. The results from this analysis have highlighted a correlation with some spatial gait parameters across the two speed conditions, indicating that this compact description of kinematics unravels a significant biomechanical meaning. These results can be exploited to guide the control mechanisms of external assistive devices, such as prostheses or exoskeletons, based purely on the measurement of few relevant kinematic quantities of the lower limb segments.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"48 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":"116873834","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/MeMeA54994.2022.9856440
F. Amitrano, A. Coccia, G. Pagano, L. Dileo, E. Losavio, G. Tombolini, G. D'Addio
Drop foot syndrome represents a deficit in locomotion, resulting from pathologies such as stroke, brain or spinal cord injury and other neurological diseases. In order to improve the quality of life of people suffering from this impairment, a widely used orthopaedic support is the “ankle foot orthosis-AFO”. This aid is applied externally to patients with drop foot syndrome in order to support plantar flexion after heel strike and subsequently allow the foot to be extended. The purpose of this study is to investigate the effect and clinical relevance of the use of an AFO on walking ability in patients suffering Drop-Foot syndrome. The experimental procedures to collect data consisted of gait analysis sessions performed with the Mobility Lab system by APDM, based on Inertial Measurement Units (IMUs) data. The analysis was carried out on a group of 19 patients with unilateral Drop-Foot syndrome, by means of ANOVA statistical test, to verify the differences among limbs and the effects of the use of the AFO. Results show a significant difference, between the affected and contralateral limb, in the following spatio-temporal metrics: Foot Clearance at Mid-Swing, Stance Duration and Swing Duration. Moreover, the considered AFO does not produce significant improvements on these parameters. The Step Duration differs significantly among limbs and improves when walking with AFO. Finally, the use of the orthotic device in the analysed population produces a significant change also in the following parameters: Gait Cycle Time and Cadence.
{"title":"The Impact of Ankle-Foot Orthoses on Spatio-Temporal Gait Parameters in Drop-Foot Patients","authors":"F. Amitrano, A. Coccia, G. Pagano, L. Dileo, E. Losavio, G. Tombolini, G. D'Addio","doi":"10.1109/MeMeA54994.2022.9856440","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856440","url":null,"abstract":"Drop foot syndrome represents a deficit in locomotion, resulting from pathologies such as stroke, brain or spinal cord injury and other neurological diseases. In order to improve the quality of life of people suffering from this impairment, a widely used orthopaedic support is the “ankle foot orthosis-AFO”. This aid is applied externally to patients with drop foot syndrome in order to support plantar flexion after heel strike and subsequently allow the foot to be extended. The purpose of this study is to investigate the effect and clinical relevance of the use of an AFO on walking ability in patients suffering Drop-Foot syndrome. The experimental procedures to collect data consisted of gait analysis sessions performed with the Mobility Lab system by APDM, based on Inertial Measurement Units (IMUs) data. The analysis was carried out on a group of 19 patients with unilateral Drop-Foot syndrome, by means of ANOVA statistical test, to verify the differences among limbs and the effects of the use of the AFO. Results show a significant difference, between the affected and contralateral limb, in the following spatio-temporal metrics: Foot Clearance at Mid-Swing, Stance Duration and Swing Duration. Moreover, the considered AFO does not produce significant improvements on these parameters. The Step Duration differs significantly among limbs and improves when walking with AFO. Finally, the use of the orthotic device in the analysed population produces a significant change also in the following parameters: Gait Cycle Time and Cadence.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"31 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":"115404504","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/MeMeA54994.2022.9856547
N. Giordano, S. Rosati, M. Knaflitz, G. Balestra
Phonocardiography (PCG) has proved a valuable tool over the years to monitor the status of at-risk patients for some cardiovascular diseases. Its multi-source version, consisting of the simultaneous recording of multiple acoustic signals from different points of the patient's chest, is currently under research as a solution to develop wearable devices based on PCG and bring PCG to the patient's domicile. When a high number of PCG signals are available, to define the most suitable auscultation area, depending on the clinical question, clustering comes into the picture. In this work, we applied agglomerative hierarchical clustering and k-means to multi-source PCG recordings. A similarity metrics based on the correlation of the signals was used to compare the signals based on their morphological characteristics. The two clustering methods resulted in a Rand Index averagely higher than 0.84, showing a high level of agreement and validating the usage of clustering for the application of interest. Hierarchical clustering allowed for obtaining a better trade-off between the intra-cluster variability and the inter-cluster distance. Adding to its deterministic nature, it should be considered as preferrable with respect to k-means. This work moves one step further to the development a reliable wearable device based on digital auscultation for the monitoring of the patient at its domicile.
{"title":"Comparison of Hierarchical and Partitional Clustering in Multi-Source Phonocardiography","authors":"N. Giordano, S. Rosati, M. Knaflitz, G. Balestra","doi":"10.1109/MeMeA54994.2022.9856547","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856547","url":null,"abstract":"Phonocardiography (PCG) has proved a valuable tool over the years to monitor the status of at-risk patients for some cardiovascular diseases. Its multi-source version, consisting of the simultaneous recording of multiple acoustic signals from different points of the patient's chest, is currently under research as a solution to develop wearable devices based on PCG and bring PCG to the patient's domicile. When a high number of PCG signals are available, to define the most suitable auscultation area, depending on the clinical question, clustering comes into the picture. In this work, we applied agglomerative hierarchical clustering and k-means to multi-source PCG recordings. A similarity metrics based on the correlation of the signals was used to compare the signals based on their morphological characteristics. The two clustering methods resulted in a Rand Index averagely higher than 0.84, showing a high level of agreement and validating the usage of clustering for the application of interest. Hierarchical clustering allowed for obtaining a better trade-off between the intra-cluster variability and the inter-cluster distance. Adding to its deterministic nature, it should be considered as preferrable with respect to k-means. This work moves one step further to the development a reliable wearable device based on digital auscultation for the monitoring of the patient at its domicile.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"137 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":"114169175","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/MeMeA54994.2022.9856485
N. Zholdas, M. Mansurova, Magzhan Sarsembayev, O. Postolache, A. Shomanov, T. Sarsembayeva
Our research has shown that the use of mobile technologies (mHealth) to improve self-control of children and adolescents with diabetes, as well as for parental control, gives positive results. A functional implemented in a mobile application has been developed that contains recommendations from endocrinologists based on the analysis of data from sensors, taking into account the individual characteristics of the patient's body. Digital health profiles of patients with diabetes mellitus, containing the values of state indicators obtained from various sensors, mobile phones, medical watches and fitness bracelets, make it possible to develop systems for monitoring and supporting personalized decision-making. By observing a patient's digital profile, clinicians can determine some of the possible causes of deviations in glucose readings in predetermined time segments. During the project, under the close supervision of endocrinologists and a pediatrician, patient data were collected, such as continuous monitoring glucose sensor values, fitness bracelet records, anthropometric data, disease and family history data, eating behavior data, HbAl c (glycated hemoglobin) level data in beginning and end of the study to assess carbohydrate metabolism compensation, FA (fructosamine) level data twice during the study period in order to short-term assess the degree of carbohydrate metabolism compensation, general blood analysis and general urine analysis data in order to additionally assess the reliability of previous tests for data analysis.
{"title":"Application of mHealth Technologies to Improve Self-Control of Children and Adolescents with Type 1 Diabetes","authors":"N. Zholdas, M. Mansurova, Magzhan Sarsembayev, O. Postolache, A. Shomanov, T. Sarsembayeva","doi":"10.1109/MeMeA54994.2022.9856485","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856485","url":null,"abstract":"Our research has shown that the use of mobile technologies (mHealth) to improve self-control of children and adolescents with diabetes, as well as for parental control, gives positive results. A functional implemented in a mobile application has been developed that contains recommendations from endocrinologists based on the analysis of data from sensors, taking into account the individual characteristics of the patient's body. Digital health profiles of patients with diabetes mellitus, containing the values of state indicators obtained from various sensors, mobile phones, medical watches and fitness bracelets, make it possible to develop systems for monitoring and supporting personalized decision-making. By observing a patient's digital profile, clinicians can determine some of the possible causes of deviations in glucose readings in predetermined time segments. During the project, under the close supervision of endocrinologists and a pediatrician, patient data were collected, such as continuous monitoring glucose sensor values, fitness bracelet records, anthropometric data, disease and family history data, eating behavior data, HbAl c (glycated hemoglobin) level data in beginning and end of the study to assess carbohydrate metabolism compensation, FA (fructosamine) level data twice during the study period in order to short-term assess the degree of carbohydrate metabolism compensation, general blood analysis and general urine analysis data in order to additionally assess the reliability of previous tests for data analysis.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"12 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":"114298998","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/MeMeA54994.2022.9856463
S. Banerjee, A. Arunachalakasi, S. Ramakrishnan
Measurement of skeletal muscle stiffness can provide a noninvasive estimation of its contraction level. Myotonometry is a novel technique for estimating muscle stiffness using digital palpation method. In this study, the reliability of myotonometric measurements with varied loading conditions is explored. For this purpose, eight healthy young participants (6 male, age 25.00 ± 3.94 years) are recruited to perform isometric elbow flexion tasks. Myotonometric signal is recorded from the biceps brachii muscle belly at resting and at isometric no-load, isometric 3 kg, and isometric 6 kg loading conditions from both hands. Three observations are made per trial and Dynamic Stiffness (DS) values are calculated from the recorded signals. Modified Bland and Altman's method and subsequent interclass correlation coefficients (ICCs) are determined for DS in each loading configuration. Point biserial correlation analysis has been performed to explore the effect of incremental loading on DS. Excellent agreement between the observations has been found for all the loading configurations with high ICC scores of more than 0.9. DS is observed to vary linearly with the increasing loading intensity with the R value of 0.73 for the right and 0.92 for the left hand. The results demonstrate that myotonometric measurements give reliable measurements of muscle stiffness in sub maximal contractions. Linear variation of DS with increasing loading intensity is observed for both hands, although the variation is more consistent in the left hand. The results of the present study might be clinically relevant in noninvasively estimating the muscle contraction level and designing better rehabilitative strategies.
{"title":"Reliability analysis of muscle stiffness estimation in varied loading levels by using dynamic myotonometric measurements","authors":"S. Banerjee, A. Arunachalakasi, S. Ramakrishnan","doi":"10.1109/MeMeA54994.2022.9856463","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856463","url":null,"abstract":"Measurement of skeletal muscle stiffness can provide a noninvasive estimation of its contraction level. Myotonometry is a novel technique for estimating muscle stiffness using digital palpation method. In this study, the reliability of myotonometric measurements with varied loading conditions is explored. For this purpose, eight healthy young participants (6 male, age 25.00 ± 3.94 years) are recruited to perform isometric elbow flexion tasks. Myotonometric signal is recorded from the biceps brachii muscle belly at resting and at isometric no-load, isometric 3 kg, and isometric 6 kg loading conditions from both hands. Three observations are made per trial and Dynamic Stiffness (DS) values are calculated from the recorded signals. Modified Bland and Altman's method and subsequent interclass correlation coefficients (ICCs) are determined for DS in each loading configuration. Point biserial correlation analysis has been performed to explore the effect of incremental loading on DS. Excellent agreement between the observations has been found for all the loading configurations with high ICC scores of more than 0.9. DS is observed to vary linearly with the increasing loading intensity with the R value of 0.73 for the right and 0.92 for the left hand. The results demonstrate that myotonometric measurements give reliable measurements of muscle stiffness in sub maximal contractions. Linear variation of DS with increasing loading intensity is observed for both hands, although the variation is more consistent in the left hand. The results of the present study might be clinically relevant in noninvasively estimating the muscle contraction level and designing better rehabilitative strategies.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"24 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":"115157892","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/MeMeA54994.2022.9856501
Z. Marinković, G. Gugliandolo, A. Quattrocchi, G. Campobello, G. Crupi, N. Donato
The focus of this paper is on the modeling of a gas sensor based on a microwave microstrip resonator aimed for humidity detection. This is because humidity sensors have been widely applied in different fields, like healthcare, environmental monitoring, meteorology, and industrial processes. The propagative structure of a microwave resonator sensor is covered with a humidity sensing layer whose frequency dielectric properties vary with the change of humidity, causing changes in the sensor microwave properties. The frequency- and humidity- dependent behavior of the reflection coefficient of the studied sensor is modelled by using artificial neural networks (ANNs). To achieve a model which will reliably and accurately predict the reflection coefficient, the prior knowledge input (PKI) approach is implemented. The data used for the model development have been acquired by measuring the reflection coefficient in the frequency range (3.4 ÷ 5.6) GHz and for different relative humidity values, in the range (0 ÷ 83) %rh. The ANN-based model has been developed and experimentally validated, allowing an accurate reproduction of the measured properties of such sensor under test and prediction even at an operating condition not used during the ANN training. This demonstrates the good capabilities of the achieved model to learn and generalize.
{"title":"Development and Experimental Validation of an Artificial Neural Network Model of a Microwave Microstrip Resonator for Humidity Sensing","authors":"Z. Marinković, G. Gugliandolo, A. Quattrocchi, G. Campobello, G. Crupi, N. Donato","doi":"10.1109/MeMeA54994.2022.9856501","DOIUrl":"https://doi.org/10.1109/MeMeA54994.2022.9856501","url":null,"abstract":"The focus of this paper is on the modeling of a gas sensor based on a microwave microstrip resonator aimed for humidity detection. This is because humidity sensors have been widely applied in different fields, like healthcare, environmental monitoring, meteorology, and industrial processes. The propagative structure of a microwave resonator sensor is covered with a humidity sensing layer whose frequency dielectric properties vary with the change of humidity, causing changes in the sensor microwave properties. The frequency- and humidity- dependent behavior of the reflection coefficient of the studied sensor is modelled by using artificial neural networks (ANNs). To achieve a model which will reliably and accurately predict the reflection coefficient, the prior knowledge input (PKI) approach is implemented. The data used for the model development have been acquired by measuring the reflection coefficient in the frequency range (3.4 ÷ 5.6) GHz and for different relative humidity values, in the range (0 ÷ 83) %rh. The ANN-based model has been developed and experimentally validated, allowing an accurate reproduction of the measured properties of such sensor under test and prediction even at an operating condition not used during the ANN training. This demonstrates the good capabilities of the achieved model to learn and generalize.","PeriodicalId":106228,"journal":{"name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"118 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":"115623358","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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