vocal signal analysis in patients affected by multiple sclerosis

Abstract Multiple Sclerosis (MS) is one of the most common neurodegenerative disorder that presents specific manifestations among which the impaired speech (known also as dysarthria). The evaluation of the speech plays a crucial role in the diagnosis and follow-up since the identification of anomalous patterns in vocal signal may represent a valid support to physician in diagnosis and monitoring of these neurological diseases. In this contribution, we present a method to perform voice analysis of neurologically impaired patients affected by MS aiming to early detection, differential diagnosis, and monitoring of disease progression. This method integrates two well-known methodologies to support the health structure in MS diagnosis in clinical practice. Acoustic analysis and vowel metric methodologies have been considered to implement this procedure to better define the pathological voices compared to healthy voices. Specifically, the method acquires and analyzes vocal signals performing features extraction and identifying possible important patterns useful to associate impaired speech with this neurological disease. The contribution consists in furnishing to physician a guide method to support MS trend. As result, this method furnishes patterns that could be valid indicators for physician in monitoring of patients affected by MS. Moreover, the procedure is appropriate to be used in early diagnosis that is critical in order to improve the patient's quality of life

Applying Mining Techniques to Analyze Vestibular Data

AbstractThe vestibular apparatus allows to perform audiological and equilibrium human functions and to capture movements with respect to gravity. Damages to the vestibular system causes diseases that can be measured by using Vestibular Evoked Myogenic Potentials (VEMPs) test. The test produces a lot of data that has to be collected and analyzed to allow a disease study and classification. We propose a framework that includes algorithms able to perform pathology distribution and classification. It has been tested on electronic patient records loaded from the University Hospital database. The software allows to manage the structure and framework and a blind application of one of the available classification techniques shows a relation among gender and vestibular apparatus disease

Effects of 26 weeks of treatment with empagliflozin versus glimepiride on the myocardial glucose metabolic rate in patients with type 2 diabetes. The randomized, open-label, crossover, active-comparator FIORE trial

Aim To determine whether treatment with empagliflozin was able to affect the myocardial glucose metabolic rate, as assessed by cardiac dynamic F-18-fluorodeoxyglucose-positron emission tomography (F-18-FDG-PET) combined with euglycaemic-hyperinsulinaemic clamp compared with glimepiride in patients with type 2 diabetes. Materials and Methods To further investigate the cardioprotective mechanism of sodium-glucose co-transporter-2 inhibitors, we performed a 26-week, randomized, open-label, crossover, active-comparator study to determine the effects of empagliflozin 10 mg versus glimepiride 2 mg daily on the myocardial glucose metabolic rate assessed by cardiac dynamic F-18-FDG-PET combined with euglycaemic-hyperinsulinaemic clamp in 23 patients with type 2 diabetes. We also measured cardiac geometry and myocardial mechano-energetic efficiency, as well as systolic and diastolic function by echocardiography. Results Compared with glimepiride, treatment with empagliflozin resulted in a greater reduction in the myocardial glucose metabolic rate from baseline to 26 weeks (adjusted difference -6.07 [-8.59, -3.55] mu mol/min/100 g; P < .0001). Moreover, compared with glimepiride, empagliflozin led to significant reductions in left atrial diameter, left ventricular end-systolic and end-diastolic volumes, N-terminal pro b-type natriuretic peptide levels, blood pressure, heart rate, stroke work, and myocardial oxygen consumption estimated by the rate pressure product, and increases in ejection fraction, myocardial mechano-energetic efficiency, red blood cells, and haematocrit and haemoglobin levels. Conclusions The present study provides evidence that empagliflozin treatment in subjects with type 2 diabetes without coronary artery disease leads to a significant reduction in the myocardial glucose metabolic rate

DNA damage and repair biomarkers in cervical cancer patients treated with neoadjuvant chemotherapy: An exploratory analysis

Cervical cancer cells commonly harbour a defective G1/S checkpoint owing to the interaction of viral oncoproteins with p53 and retinoblastoma protein. The activation of the G2/M checkpoint may thus become essential for protecting cancer cells from genotoxic insults, such as chemotherapy. In 52 cervical cancer patients treated with neoadjuvant chemotherapy, we investigated whether the levels of phosphorylated Wee1 (pWee1), a key G2/M checkpoint kinase, and y-H2AX, a marker of DNA double-strand breaks, discriminated between patients with a pathological complete response (pCR) and those with residual disease. We also tested the association between pWee1 and phosphorylated Chk1 (pChk1), a kinase acting upstream Wee1 in the G2/M checkpoint pathway. pWee1, y-H2AX and pChk1 were retrospectively assessed in diagnostic biopsies by immunohistochemistry. The degrees of pWee1 and pChk1 expression were defined using three different classification methods, i.e., staining intensity, Allred score, and a multiplicative score. y-H2AX was analyzed both as continuous and categorical variable. Irrespective of the classification used, elevated levels of pWee1 and y-H2AX were significantly associated with a lower rate of pCR. In univariate and multivariate analyses, pWee1 and y-H2AX were both associated with reduced pCR. Internal validation conducted through a re-sampling without replacement procedure confirmed the robustness of the multivariate model. Finally, we found a significant association between pWee1 and pChk1. The message conveyed by the present analysis is that biomarkers of DNA damage and repair may predict the efficacy of neoadjuvant chemotherapy in cervical cancer. Further studies are warranted to prospectively validate these encouraging findings

On the analysis of biomedical signals for disease classification

The analysis of biomedical signals and images is relevant for early diagnosis, detection and treatment of diseases. It represents the first step in the proper management of pathological conditions. Therefore, it is essential to support clinical practice during the diagnosis process by extracting relevant information and by classifying different diseases. This contribution outlines the methodologies of the most frequently used analysis techniques in biomedicine and their applications. The aim is to report about typical biosignals and bioimages and their analysis to enhance the importance of signal processing in the study and classification of specific diseases

Social health recommender system: application for healthcare and pandemia information diffusion

The amount of information and services available on the web represents an important opportunity for people to enrich and share knowledges. The easy access and the continuous growth of data in the web are responsible of an overload of information that leads the user to navigate in a saturated and often uninteresting and non-comprehensive environment. In the medical-clinical context, a lot of information on the web is often incomplete, inaccurate or completely wrong due to an incorrect sharing and a lack of control of the sources. In this context, recommendation systems become essential to filter truthful information and to target users with respect to their needs. The status of recent covid-19 pandemic highlighted the necessity of having health reliable sources. Health recommender systems support user in medical environment to find right information. In this contribution, we report about a project of health recommender system aiming to: (i) aggregate similar users and (ii) guarantee the truthful and quality of the extracted information through a check of the sources and a validation by the medical scientific community

Vaginal atrophy in breast cancer survivors: role of vaginal estrogen therapy

Early menopause and related vaginal atrophy is a well known side-effect of hormone adjuvant treatment in breast cancer patients, particularly during aromatase-inhibitors therapy. Due to estrogens contra-indication, proper therapy for such symptom remains often an inadequately addressed clinical problem. After an accurate assessment of the risk/benefit ratio, vaginal low-dose estrogen treatment (better with estriol) may have a role in controlling vaginal atrophy in selected and informed breast cancer women

On the Use of Voice Signals for Studying Sclerosis Disease

Multiple sclerosis (MS) is a chronic demyelinating autoimmune disease affecting the central nervous system. One of its manifestations concerns impaired speech, also known as dysarthria. In many cases, a proper speech evaluation can play an important role in the diagnosis of MS. The identification of abnormal voice patterns can provide valid support for a physician in the diagnosing and monitoring of this neurological disease. In this paper, we present a method for vocal signal analysis in patients affected by MS. The goal is to identify the dysarthria in MS patients to perform an early diagnosis of the disease and to monitor its progress. The proposed method provides the acquisition and analysis of vocal signals, aiming to perform feature extraction and to identify relevant patterns useful to impaired speech associated with MS. This method integrates two well-known methodologies, acoustic analysis and vowel metric methodology, to better define pathological compared to healthy voices. As a result, this method provides patterns that could be useful indicators for physicians in identifying patients affected by MS. Moreover, the proposed procedure could be a valid support in early diagnosis as well as in monitoring treatment success, thus improving a patient’s life quality

REHABS: An Innovative and User-Friendly Device for Rehabilitation

: Rehabilitation is a complex set of interventions involving the assessment, management, and treatment of injuries. It aims to support and facilitate an individual's recovery process by restoring a physiological function, e.g., limb movement, compromised by physical impairments, injuries or diseases to a condition as close to normal as possible. Innovative devices and solutions make the rehabilitation process of patients easier during their daily activities. Devices support physicians and physiotherapists in monitoring and measuring patients' physical improvements during rehabilitation. In this context, we report the design and implementation of a low-cost rehabilitation system, which is a programmable device designed to support tele-rehabilitation of the upper limbs. The proposed system includes a mechanism to acquire and analyze data and signals related to rehabilitation processes