Vaishali Balakarthikeyan, Amalan Sebastin, P. PreejithS., J. Joseph, M. Sivaprakasam
{"title":"HRV based Stress Assessment of Individuals in a Work Environment","authors":"Vaishali Balakarthikeyan, Amalan Sebastin, P. PreejithS., J. Joseph, M. Sivaprakasam","doi":"10.1109/MeMeA49120.2020.9137299","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137299","url":null,"abstract":"Workplace Stress can impact the employees especially when their perception of job demands are more than what they can meet. Excessive and long term stress can have detrimental effects on both physiological and mental health. Building resilience is necessary for an individual, which helps combat the mental strain of work stress and exercise control over the work demands. At their core, stress responses are often linked to resolving the threats by increasing an individual's ability to cope. Unobtrusive and continuous monitoring of stress during work can help in understanding how stress levels change throughout a work day. In this study, stress has been evaluated from Electrocardiogram (ECG) derived Heart Rate Variability (HRV) obtained using an unobtrusive chest wearable. A total of 85 employees participated in the study and their measured stress levels were classified into four different levels as no, low, medium and high stress. The stress levels were evaluated every 5 minutes as the employees engaged in tasks like review meeting and accomplishing deadlines. Analysis revealed stress levels of employees reduced when they took breaks during work time. Females generally experienced high stress levels for much longer duration than males, whereas males experienced no, low and medium stress only a little longer than females. Also, variations in stress levels of the employees before, during and after lunch were studied to understand how food affects stress and the decrease in stress levels observed shows the impact of food intake in coping with stress.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"66 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":"114551460","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}
Ilaria Conforti, Stefano Fiore, Ilaria Mileti, L. Dinia, F. Mangini, F. Frezza, Z. Prete, E. Palermo
{"title":"Measuring immediate effects of patellar taping on balance kinematics","authors":"Ilaria Conforti, Stefano Fiore, Ilaria Mileti, L. Dinia, F. Mangini, F. Frezza, Z. Prete, E. Palermo","doi":"10.1109/MeMeA49120.2020.9137145","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137145","url":null,"abstract":"Individuals with patellofemoral pain syndrome present biomechanical alterations of lower limb kinematics and difficulties in postural control. Taping techniques like McConnell’s were adopted to reduce pain and avert lower extremity injury, especially on the knee joint complex. Although the patellar taping appears to be an effective tool in reducing patellofemoral pain by stabilizing the patellofemoral joint, its immediate effects on balance, and trunk and lower limb kinematics are still not clear. The assessment of the immediate taping-induced biomechanical modifications on balance and kinematics could provide a deeper insight into the mechanical actions of the McConnell’s. Nine healthy young adults (age: 29.1 ± 4.7 years) were equipped with eight wireless inertial measurement units placed on trunk and lower limbs. Participants were asked to perform the Star Excursion Balance Test (SEBT) and the Single Leg Squat (SLS) task in five different directions on a force plate. Kinematics of lumbosacral and lower limb joints, as well as balance indices such as spatiotemporal parameters of the center of pressure, were estimated with and without the McConnell taping. No mechanical effects were observed for spatiotemporal indices of the center of pressure and for all considered kinematic parameters, except for kinematics of the knee. Results demonstrated significant differences due to taping condition (p=0.01) for the knee joint in the SLS task. A similar trend was observed in SEBT. This interesting result highlights the instantaneous effect of McConnell taping on knee joint complex, without impairing any self-selected strategies adopted by healthy subjects.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"54 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":"122053561","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}
Sara Burini, P. Marchionni, L. Scalise, S. Spinsante, E. Ferretti, V. Carnielli
{"title":"Non-contact anthropometric measurements in newborn patients","authors":"Sara Burini, P. Marchionni, L. Scalise, S. Spinsante, E. Ferretti, V. Carnielli","doi":"10.1109/MeMeA49120.2020.9137154","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137154","url":null,"abstract":"New born patients require a frequent and periodic collection of some anthropometric data to evaluate their correct growth, particularly during the first weeks of their life. This information allows to eventual detect slow growth rate potentially related to some pathologies of the neonate. Among the many anthropometric data of interest, in this study, specific attention has been dedicated to tibial length (TL), cranial circumference (CC) and body height (H); such parameters that are routinely collected in clinical environment. Available measurement methods to measure these parameters are not useful for our purpose, because the aim of this study is to obtain reliable non-contact measurements on infants. In this paper, we propose the use of stereophotogrammetry, in which images are elaborated by a software in order to obtain the 3D reconstruction of the subject. This semi-automatic approach is contactless and completely safe for the infant. In our experiments, a cohort of 9 subjects (7 infants and 2 simulators) has been used and images were taken using a smart watch, CCD camera. From obtained results, measurements calculated by the proposed method are comparable with the data collected by the clinical expert. Moreover, data repeatability of the proposed measurement method is lower respect to the one estimated from the operator (±0.7 cm). For this reason, it is possible to consider the proposed method, based on stereophotogrammetry, applicable to the anthropometric measurements of infants, offering an alternative to the manual measurements routinely performed by clinicians.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"73 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":"129389532","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}
Marco Recenti, C. Ricciardi, R. Aubonnet, L. Esposito, H. Jónsson, P. Gargiulo
{"title":"A Regression Approach to Assess Bone Mineral Density of Patients undergoing Total Hip Arthroplasty through Gait Analysis","authors":"Marco Recenti, C. Ricciardi, R. Aubonnet, L. Esposito, H. Jónsson, P. Gargiulo","doi":"10.1109/MeMeA49120.2020.9137182","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137182","url":null,"abstract":"Total Hip Arthroplasty (THA) is the gold standard for hip replacement surgery. It can be performed with two different kinds of prostheses: cemented and uncemented. The surgeons have always decided on the type of prosthesis based on the age, sex of the patient and bone stock on x rays. In this paper 42 subjects underwent THA and performed both gait analysis and bone mineral density (BMD) evaluation through CT scans; spatial and temporal gait parameters were used to predict BMD of the distal and proximal parts of the femur before and one year after surgery using machine learning regression analysis. A simple linear regression (LR) and k-nearest neighbor (KNN) were implemented coding with Python Scikit-Learn libraries and some evaluation metrics were computed: the coefficient of determination (R2), mean absolute error, mean squared error and root mean squared error. Both the algorithms had a R2 greater than 75% in predicting both proximal and distal; particularly, LR obtained the highest score of 88.4% in predicting the BMD before the THA and of 81.3% after the THA. All the R2 of KNN ranged from 75% and 77%. All the calculated errors were always below 0.001. In conclusion, this research shows the feasibility of gait parameters for assessing the follow-up after 52 weeks of patients undergoing THA by predicting the BMD. Moreover, the results give insights about the relationship between the patterns of gait and BMD.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"4 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":"129459014","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}
S. Rosati, P. Franco, C. Fiandra, F. Arcadipane, P. Silvetti, E. Gallio, J. Panić, U. Ricardi, G. Balestra
{"title":"Comparison of different classifiers to recognize active bone marrow from CT images","authors":"S. Rosati, P. Franco, C. Fiandra, F. Arcadipane, P. Silvetti, E. Gallio, J. Panić, U. Ricardi, G. Balestra","doi":"10.1109/MeMeA49120.2020.9137173","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137173","url":null,"abstract":"One of the main problems during in the treatment of anal cancer with chemotherapy and radiation is the occurrence of Hematologic Toxicity (HT). In particular, during radiotherapy it is crucial to spare Bone Marrow (BM), since the radiation dose received by BM in pelvic bones predicts the onset of HT. In this direction, the most popular strategies are based on the identification of the hematopoietically active BM (actBM), that is the part of BM in charge of blood cells generation, using MRI, SPECT or PET, but no approached have been proposed based on CT. In this study we compare four different classifiers in recognizing actBM from CT images using 36 radiomic features. We used Genetic Algorithms (GAs) to simultaneously optimize the feature subsets and the classifier parameters, separately for three pelvic subregions: iliac bone marrow (IBM), lower pelvis bone marrow (LPBM), and lumbosacral bone marrow (LSBM). The obtained classifiers were applied to CT sequences of a cohort of 25 patients affected by carcinoma of the anal canal. Classifiers results were compared with the actBM identified from 18FDG-PET (reference standard, RS). It emerged that the performances of the 4 classifiers are similar and they are satisfactory for IBM and LSBM subregions (Dice > 0.7) whereas they are poor for LPBM (Dice < 0.5).","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"16 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":"128231704","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}
Enrico Picariello, E. Balestrieri, F. Picariello, S. Rapuano, IOAN TUDOSA, L. D. Vito
{"title":"A New Method for Dictionary Matrix Optimization in ECG Compressed Sensing","authors":"Enrico Picariello, E. Balestrieri, F. Picariello, S. Rapuano, IOAN TUDOSA, L. D. Vito","doi":"10.1109/MeMeA49120.2020.9137165","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137165","url":null,"abstract":"This paper proposes a new method for dictionary matrix optimization with the aim of improving the reconstruction quality of ECG signals delivered by a Compressed Sensing (CS) algorithm. The method exploits the features common to all the records of the ECG signal of the same patient to obtain an optimized dictionary with reduced size. In this way, the signal reconstruction from the compressed samples is performed in a do-main defined by a base with a reduced cardinality, thus allowing to increase the signal’s reconstruction quality and to reduce the execution time of the reconstruction algorithm. The mathematical model for the patient specific ECG signals dictionary optimization is described, and a preliminary experimental assessment is presented. The obtained results clearly demonstrates that the proposed method exhibits a reconstruction quality in terms of Percentage of Root-mean-squared Difference (PRD) lower than a method adopting the non-optimized dictionary matrix.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"26 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":"128586546","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":"ADLs Monitoring by Accelerometer-Based Wearable Sensors: Effect of Measurement Device and Data Uncertainty on Classification Accuracy","authors":"A. Poli, L. Scalise, S. Spinsante, A. Strazza","doi":"10.1109/MeMeA49120.2020.9137265","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137265","url":null,"abstract":"Machine Learning algorithms are often used for automatic recognition and classification of Activities of Daily Living, and they rely on the computation of several features capturing the relevant characteristics of the collected signals, either in the time and frequency domains. While the accuracy of the measurement device used may be assessed by the manufacturer’s specifications or by specific tests, the propagated uncertainty of the computed features is typically not considered in the framework of automatic classification approaches. In this paper, the impact of the measurement devices on data quality, and consequently on the performance of automatic classifiers, is evaluated, in the context of accelerometer-based recognition of Activities of Daily Living with a wrist-worn device. Results show that different accuracy performance may be attained in the classification process, depending on the wearable device used, despite the same environmental and operational conditions.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"84 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":"127028448","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}
G. Laudato, R. Oliveto, Simone Scalabrino, A. Colavita, L. D. Vito, F. Picariello, IOAN TUDOSA
{"title":"Identification of R-peak occurrences in compressed ECG signals","authors":"G. Laudato, R. Oliveto, Simone Scalabrino, A. Colavita, L. D. Vito, F. Picariello, IOAN TUDOSA","doi":"10.1109/MeMeA49120.2020.9137207","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137207","url":null,"abstract":"Heart Rate (HR) is one of the mostly used electrocardiogram (ECG) feature in many automatic detectors of anomalies. This paper deals with a preliminary study on a novel approach which, through the combination of Machine Learning (ML) and Compressed Sensing (CS), aims at retrieving vital information from a digital compressed single-lead electrocardiogram (ECG) signal. As a potential key information to estimate the heart rate, this study focuses on the identification of R-peak occurrences. The study has been conducted on two different types of signal both obtained from the compressed samples provided by a CS algorithm, already available in literature. The results demonstrate that the use of CS in combination with a ML technique can find high competitiveness when compared to a state of the art method working on the uncompressed ECG signal.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"03 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":"129960909","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}
Michela Franzo', Simona Pascucci, M. Serrao, F. Marinozzi, F. Bini
{"title":"Kinect-based wearable prototype system for ataxic patients neurorehabilitation: control group preliminary results","authors":"Michela Franzo', Simona Pascucci, M. Serrao, F. Marinozzi, F. Bini","doi":"10.1109/MeMeA49120.2020.9137244","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137244","url":null,"abstract":"The aim of this study is to validate the wearable prototype system for ataxic patients’ neurorehabilitation based on the Microsoft Kinect device and to archive a preliminary results of a control group of healthy subjects. The system acquires kinematics quantities as 3D position, rotation angles, linear acceleration and angular velocity of the wrist joint during a rehabilitation exercise replayed in 2 different difficulties. The trajectories performed by the 20 subjects were analysed to find the best trajectory and the one completed in the least time. Comparing the acquired performances with the ideal ones, a reference range with which train the patients was obtained. Analysis related to gender and skill abilities were executed.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"51 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":"129128375","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":"Fitts’ Evaluation of a Developed Human-in-the-Loop Assistive Device","authors":"R. Antunes, Luís Brito Palma","doi":"10.1109/MeMeA49120.2020.9137343","DOIUrl":"https://doi.org/10.1109/MeMeA49120.2020.9137343","url":null,"abstract":"In this work, a new human-computer assistive technology gadget designed for people with impairments is evaluated. The developed human-in-the-loop interface device has an embedded assistance controller and can replace the traditional mouse, gamepad and keyboard, enabling human-computer hands-free full access. This work is concerned with the assistive device performance characterization aspects. Based on the experiments carried out, the human-computer performance improvement with the embedded controller is analysed in detail. Results show that adding the human-in-the-loop assistance controller improves human-computer hands-free skills, which is an innovative contribution for the replacement of computer interfaces that depend on the human hands.","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":"131085863","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}