cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7511624.v1
title: AACVOX: mobile application for augmentative alternative communication to help people with speech disorder and motor impairment

description: AbstractIntroduction: Communication is a fundamental element for the development of human beings, promoting their coexistence in society. However, changes in muscle tone, associated with cerebral palsy (CP), among other conditions, cause phono-articulatory dysfunctions hindering speech capabilities. Although there are resources for augmentative and alternative communication (AAC), most of them do not completely satisfy the needs of individuals with motor impairment. Therefore, this study proposes a tool based on mobile technology for AAC, which can be adapted to the characteristics of the motor limitations of CP users. Methods Mobile system development was conducted employing user-centered design and development methods. Functions were developed allowing the communication of phrases through pictographic resources and a mechanism of speech synthesis, that can be customized according to specific communication needs. To validate this system, 20 CP volunteers with speech difficulties and motor impairment were recruited from two institutions in the State of São Paulo, Brazil. They operated the system following a pre-defined test protocol, and they answered a system usability scale (SUS) questionnaire, to rate the ease of learning, memorization, efficiency, occurrence of runtime errors, and the level of user satisfaction. Results The results showed a score of 85.85 ± 2.28 above the average SUS scale, for each one of the quality components assessed by the volunteers. Conclusion The developed software is user-friendly, representing a new option for AAC, and is customized according to the communication needs of people with speech disorder and motor impairment.
DOI: 10.6084/m9.figshare.7304609
title: Real-time premature ventricular contractions detection based on Redundant Discrete Wavelet Transform

description: Abstract Introduction Premature Ventricular Contraction (PVC) is among the most common types of ventricular cardiac arrhythmia. However, it only poses danger if the person suffers from a heart disease, such as heart failure. Hence, this is an important factor to consider in heart disease people. This paper presents an ECG real-time analysis system for PVC detection. Methods This system is based on threshold adaptive methods and Redundant Discrete Wavelet Transform (RDWT), with a real-time approach. This analysis is based on wavelet coefficients energy for PVC detection. It is presented also a study to find the most indicated wavelet mother for ECG analysis application among the following wavelet families: Daubechies, Coiflets and Symlets. The system detection performance was validated on the MIT-BIH Arrhythmia Database. Results The best results were verified with db2 wavelet mother: the Sensitivity Se = 99.18%, Positive Predictive Value P+ = 99.15% and Specificity Sp = 99.94%, on 80.872 annotated beats, and 61.2 s processing speed for a half-hour record. Conclusion The proposed system exhibits reliable PVC detection, with real-time approach, and a simple algorithmic structure that can be implemented in many platforms.
DOI: 10.6084/m9.figshare.7304609.v1
title: Real-time premature ventricular contractions detection based on Redundant Discrete Wavelet Transform

description: Abstract Introduction Premature Ventricular Contraction (PVC) is among the most common types of ventricular cardiac arrhythmia. However, it only poses danger if the person suffers from a heart disease, such as heart failure. Hence, this is an important factor to consider in heart disease people. This paper presents an ECG real-time analysis system for PVC detection. Methods This system is based on threshold adaptive methods and Redundant Discrete Wavelet Transform (RDWT), with a real-time approach. This analysis is based on wavelet coefficients energy for PVC detection. It is presented also a study to find the most indicated wavelet mother for ECG analysis application among the following wavelet families: Daubechies, Coiflets and Symlets. The system detection performance was validated on the MIT-BIH Arrhythmia Database. Results The best results were verified with db2 wavelet mother: the Sensitivity Se = 99.18%, Positive Predictive Value P+ = 99.15% and Specificity Sp = 99.94%, on 80.872 annotated beats, and 61.2 s processing speed for a half-hour record. Conclusion The proposed system exhibits reliable PVC detection, with real-time approach, and a simple algorithmic structure that can be implemented in many platforms.
DOI: 10.6084/m9.figshare.7304711
title: Control of a robotic knee exoskeleton for assistance and rehabilitation based on motion intention from sEMG

description: Introduction: This work presents the development of a novel robotic knee exoskeleton controlled by motion intention based on sEMG, which uses admittance control to assist people with reduced mobility and improve their locomotion. Clinical research remark that these devices working in constant interaction with the neuromuscular and skeletal human system improves functional compensation and rehabilitation. Hence, the users become an active part of the training/rehabilitation, facilitating their involvement and improving their neural plasticity. For recognition of the lower-limb motion intention and discrimination of knee movements, sEMG from both lower-limb and trunk are used, which implies a new approach to control robotic assistive devices. Methods A control system that includes a stage for human-motion intention recognition (HMIR), based on techniques to classify motion classes related to knee joint were developed. For translation of the user’s intention to a desired state for the robotic knee exoskeleton, the system also includes a finite state machine and admittance, velocity and trajectory controllers with a function that allows stopping the movement according to the users intention. Results The proposed HMIR showed an accuracy between 76% to 83% for lower-limb muscles, and 71% to 77% for trunk muscles to classify motor classes of lower-limb movements. Experimental results of the controller showed that the admittance controller proposed here offers knee support in 50% of the gait cycle and assists correctly the motion classes. Conclusion The robotic knee exoskeleton introduced here is an alternative method to empower knee movements using sEMG signals from lower-limb and trunk muscles.
DOI: 10.6084/m9.figshare.7304711.v1
title: Control of a robotic knee exoskeleton for assistance and rehabilitation based on motion intention from sEMG

description: Introduction: This work presents the development of a novel robotic knee exoskeleton controlled by motion intention based on sEMG, which uses admittance control to assist people with reduced mobility and improve their locomotion. Clinical research remark that these devices working in constant interaction with the neuromuscular and skeletal human system improves functional compensation and rehabilitation. Hence, the users become an active part of the training/rehabilitation, facilitating their involvement and improving their neural plasticity. For recognition of the lower-limb motion intention and discrimination of knee movements, sEMG from both lower-limb and trunk are used, which implies a new approach to control robotic assistive devices. Methods A control system that includes a stage for human-motion intention recognition (HMIR), based on techniques to classify motion classes related to knee joint were developed. For translation of the user’s intention to a desired state for the robotic knee exoskeleton, the system also includes a finite state machine and admittance, velocity and trajectory controllers with a function that allows stopping the movement according to the users intention. Results The proposed HMIR showed an accuracy between 76% to 83% for lower-limb muscles, and 71% to 77% for trunk muscles to classify motor classes of lower-limb movements. Experimental results of the controller showed that the admittance controller proposed here offers knee support in 50% of the gait cycle and assists correctly the motion classes. Conclusion The robotic knee exoskeleton introduced here is an alternative method to empower knee movements using sEMG signals from lower-limb and trunk muscles.
DOI: 10.6084/m9.figshare.7304708.v1
title: Prediction of 3D ground reaction forces during gait based on accelerometer data

description: Abstract Introduction The aim of this study was to predict 3D ground reaction force signals based on accelerometer data during gait, using a feed-forward neural network (MLP). Methods Seventeen healthy subjects were instructed to walk at a self-selected speed with a 3D accelerometer attached to the distal and anterior part of the shank. A force plate was embedded into the middle of the walkway. MLP neural networks with one hidden layer and three output layers were selected to simulate the anteroposterior (AP), vertical (Vert) and mediolateral (ML) ground reaction forces (GRF). The input layer was composed of fourteen inputs obtained from accelerometer signals, selected based on previous studies. Principal component analysis (PCA) was used to compare the simulated and collected curves. The Pearson correlation coefficient and the mean absolute deviation (MAD) between signals were calculated. Results PCA identified small, but significant differences between collected and simulated signals in the loading response phases of AP and ML GRF, while Vert did not show differences. The correlation between the simulated and collected signals was high (AP: 0.97; Vert: 0.98; ML: 0.80). MAD was 1.8%BW for AP, 4.5%BW for Vert and 1.4%BW for ML. Conclusion This study confirmed that multilayer perceptron neural network can predict the highly non-linear relationship of shank acceleration parameters and ground reaction forces, as well as other studies have done using plantar pressure devices. The greater advantages of this device are the low cost and the possibility of use outside the laboratory environment.
DOI: 10.6084/m9.figshare.7304708
title: Prediction of 3D ground reaction forces during gait based on accelerometer data

description: Abstract Introduction The aim of this study was to predict 3D ground reaction force signals based on accelerometer data during gait, using a feed-forward neural network (MLP). Methods Seventeen healthy subjects were instructed to walk at a self-selected speed with a 3D accelerometer attached to the distal and anterior part of the shank. A force plate was embedded into the middle of the walkway. MLP neural networks with one hidden layer and three output layers were selected to simulate the anteroposterior (AP), vertical (Vert) and mediolateral (ML) ground reaction forces (GRF). The input layer was composed of fourteen inputs obtained from accelerometer signals, selected based on previous studies. Principal component analysis (PCA) was used to compare the simulated and collected curves. The Pearson correlation coefficient and the mean absolute deviation (MAD) between signals were calculated. Results PCA identified small, but significant differences between collected and simulated signals in the loading response phases of AP and ML GRF, while Vert did not show differences. The correlation between the simulated and collected signals was high (AP: 0.97; Vert: 0.98; ML: 0.80). MAD was 1.8%BW for AP, 4.5%BW for Vert and 1.4%BW for ML. Conclusion This study confirmed that multilayer perceptron neural network can predict the highly non-linear relationship of shank acceleration parameters and ground reaction forces, as well as other studies have done using plantar pressure devices. The greater advantages of this device are the low cost and the possibility of use outside the laboratory environment.
DOI: 10.6084/m9.figshare.7304603
title: New insight on the relationship between lethal electrical fields versus cardiomyocyte orientation

description: Abstract Introduction Cardiovascular diseases represent a major cause of death world-wide and one of their greatest complications is the development of cardiac arrhythmias, in which ventricular fibrillation (VF) stands out as the most severe one. The only therapy that reverses VF is defibrillation. However defibrillatory shock is capable of killing heart cells and it is known that the orientation of the cell major axis with respect to the electrical field (E) direction is a determining factor for cellular excitation and injury, which is leading to the development of new defibrillation protocols. The aim of this work is to fill the gap in information about cell lethality for intermediate cell orientation angles. Methods Ventricular myocytes were extracted from adult male Wistar rats and the cells were plated in a chamber for perfusion and stimulation with bipolar voltage pulses to determine the stimulation threshold (ET). Then, monopolar stimulus was applied and amplitude was increased until cell lethal injury. This protocol was performed on four experimental groups: cells oriented at 0°, 30°, 60° and 90°, with respect to E direction. Results 87 cells were analyzed and an increase in amplitude of E associated with 50% lethality (E50) was verified as the direction of E application and cell major axis orientation departed. Conclusion Taken the same probability of lethality, our data suggest a nonlinear increase of E amplitude from 0° to 90° similar to that of ET. These in-between data had not yet been shown and are important for service-based future defibrillation protocols.
DOI: 10.6084/m9.figshare.7304603.v1
title: New insight on the relationship between lethal electrical fields versus cardiomyocyte orientation

description: Abstract Introduction Cardiovascular diseases represent a major cause of death world-wide and one of their greatest complications is the development of cardiac arrhythmias, in which ventricular fibrillation (VF) stands out as the most severe one. The only therapy that reverses VF is defibrillation. However defibrillatory shock is capable of killing heart cells and it is known that the orientation of the cell major axis with respect to the electrical field (E) direction is a determining factor for cellular excitation and injury, which is leading to the development of new defibrillation protocols. The aim of this work is to fill the gap in information about cell lethality for intermediate cell orientation angles. Methods Ventricular myocytes were extracted from adult male Wistar rats and the cells were plated in a chamber for perfusion and stimulation with bipolar voltage pulses to determine the stimulation threshold (ET). Then, monopolar stimulus was applied and amplitude was increased until cell lethal injury. This protocol was performed on four experimental groups: cells oriented at 0°, 30°, 60° and 90°, with respect to E direction. Results 87 cells were analyzed and an increase in amplitude of E associated with 50% lethality (E50) was verified as the direction of E application and cell major axis orientation departed. Conclusion Taken the same probability of lethality, our data suggest a nonlinear increase of E amplitude from 0° to 90° similar to that of ET. These in-between data had not yet been shown and are important for service-based future defibrillation protocols.
DOI: 10.6084/m9.figshare.7304480
title: Automatic respiratory phase detection for functional electrical stimulation synchronization

description: Abstract Introduction People with cervical or high thoracic spinal cord injury usually have respiratory muscle weakness. When transcutaneous functional electrical stimulation (TFES) synchronized with the patient’s natural breathing is applied to respiratory muscles, their strength and resistance are increased. In this work, we propose a novel method to perform an automatic synchronization, composed of a signal acquisition system and an algorithm that recognizes both respiratory cycle phases during quiet breathing. Methods The respiratory signal acquisition unit consists of a load cell attached to an elastic belt. The algorithm is based on statistical evaluation and linear approximation for detecting the beginning of both inhalation and exhalation phases. Ten volunteers remained steady, breathing quietly for one minute for signal acquisition. Results The system’s automatic detection of inspiratory events reached 87.5% of true positives, 6.7% of false negatives and 5.8% of false positives. Both hit and error ratios obtained in the detection of expiratory events reached 94.3% true positives, 4.9% false positives and 0.8% false negatives. Conclusion The developed algorithm can identify the respiratory phases properly and it can be used in future synchronized TFES applications whether the patient remains in a quasi-static position during treatment.
DOI: 10.6084/m9.figshare.7304480.v1
title: Automatic respiratory phase detection for functional electrical stimulation synchronization

description: Abstract Introduction People with cervical or high thoracic spinal cord injury usually have respiratory muscle weakness. When transcutaneous functional electrical stimulation (TFES) synchronized with the patient’s natural breathing is applied to respiratory muscles, their strength and resistance are increased. In this work, we propose a novel method to perform an automatic synchronization, composed of a signal acquisition system and an algorithm that recognizes both respiratory cycle phases during quiet breathing. Methods The respiratory signal acquisition unit consists of a load cell attached to an elastic belt. The algorithm is based on statistical evaluation and linear approximation for detecting the beginning of both inhalation and exhalation phases. Ten volunteers remained steady, breathing quietly for one minute for signal acquisition. Results The system’s automatic detection of inspiratory events reached 87.5% of true positives, 6.7% of false negatives and 5.8% of false positives. Both hit and error ratios obtained in the detection of expiratory events reached 94.3% true positives, 4.9% false positives and 0.8% false negatives. Conclusion The developed algorithm can identify the respiratory phases properly and it can be used in future synchronized TFES applications whether the patient remains in a quasi-static position during treatment.
DOI: 10.6084/m9.figshare.7304744
title: Methods for quantification of cerebral glycolytic metabolism using 2-deoxy-2-[18 F]fluoroglucose in small animals

description: Abstract Introduction The use of the same imaging and quantification techniques in small animals and clinical studies presents the opportunity for direct translational research in drug discovery and development, in neuropharmacological basis of neurological and psychiatric diseases, and in optimization of drug therapy. Thus, positron emission tomography (PET) studies in rodents can bridge the gap between pre-clinical and clinical research. The aim should be to find a method with capability to measure, without compromising accuracy, glucose distribution in the structures of the brain, which can also be used in pathological situations and with applicability for other substances than glucose analogue. Methods This is a systematic review of several assessment techniques available, including visual and quantitative methods that enable the investigation of the transport mechanisms and enzymes involved in glucose metabolism in the brain. In addition to the ex vivo methods, PET with glucose analogues allows in vivo analyses using qualitative, semiquantitative and quantitative methods. Results These techniques provide different results, and the applicability of a specific method is related to the purpose of the study and the multiple factors that may interfere in the process. Conclusion This review provides a solid background of tools and quantification methods for medical physicists and other professionals interested in cerebral glycolytic metabolism quantification in experimental animals. It also addresses the main factors related to animals, equipment and techniques that are used, as well as how these factors should be understood to better interpret the results obtained from experiments.
DOI: 10.6084/m9.figshare.7304744.v1
title: Methods for quantification of cerebral glycolytic metabolism using 2-deoxy-2-[18 F]fluoroglucose in small animals

description: Abstract Introduction The use of the same imaging and quantification techniques in small animals and clinical studies presents the opportunity for direct translational research in drug discovery and development, in neuropharmacological basis of neurological and psychiatric diseases, and in optimization of drug therapy. Thus, positron emission tomography (PET) studies in rodents can bridge the gap between pre-clinical and clinical research. The aim should be to find a method with capability to measure, without compromising accuracy, glucose distribution in the structures of the brain, which can also be used in pathological situations and with applicability for other substances than glucose analogue. Methods This is a systematic review of several assessment techniques available, including visual and quantitative methods that enable the investigation of the transport mechanisms and enzymes involved in glucose metabolism in the brain. In addition to the ex vivo methods, PET with glucose analogues allows in vivo analyses using qualitative, semiquantitative and quantitative methods. Results These techniques provide different results, and the applicability of a specific method is related to the purpose of the study and the multiple factors that may interfere in the process. Conclusion This review provides a solid background of tools and quantification methods for medical physicists and other professionals interested in cerebral glycolytic metabolism quantification in experimental animals. It also addresses the main factors related to animals, equipment and techniques that are used, as well as how these factors should be understood to better interpret the results obtained from experiments.
DOI: 10.6084/m9.figshare.7677854.v1
title: Biomechanical alterations of gait on overweight subjects

description: Abstract Introduction Obesity is a major global public health issue and approximately half of the population is classified as overweight. Many studies have investigated gait modification in obese people; however, no research has been carried out in overweight subject´s gait influence. Methods The goal of this study was to identify biomechanical changes on gait in overweight subjects by the application of principal component analysis (PCA). Two groups of adults participated of this study: overweight (n = 9; 25.0 &lt; Body Mass Index &lt; 29.9 kg/m2), and normal-weight (n = 15; 20.0 &lt; Body Mass Index &lt; 24.9 kg/m2. Three-dimensional kinematics of the lower limb and ground reaction forces (GRF) were recorded during gait. PCA was performed on data. Results PCA evidenced statistical differences at the first principal component (PC) of the sagittal ankle movement, anteroposterior and mediolateral GRF, as well as at the third PC of the sagittal hip movement and mediolateral GRF. Overweight subjects walked with reduced ankle plantarflexion at toe-off and reduced hip flexion at the heel strike and at mid swing, as well as a reduced hip extension during push off. Additionally, increased anteroposterior and mediolateral GRF on overweight subjects were observed. Conclusion overweight individuals might adjust their gait characteristics in response to their increased weight to reduce overload lower limbs joints. These gait modifications pointed to a possible increase in the risk of musculoskeletal pathology in this population.