cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5792823.v1
title: Low cost system to measure active power in electrosurgical units

description: Abstract Introduction: The real-time measurement of active power delivered to patients during the electrosurgical act is still an engineering challenge. Besides, there is no electrosurgical unit on the market capable of doing it according to the normative requirement. Methods This work presents the design of an electronic structure capable to probe the electrosurgical equipment output electrical signals, using low-costs very common resistors, and High Frequency distortions compensation circuits, and process them to provide an analogue signal proportional to the active power, allowing the knowledge and control of the energy delivered to the biological tissue. The reading circuits and the active power calculation method are presented. The power calculation is performed in two stages. The first one consists of a multiplier circuit that uses the readings voltage and current quantities to determine the instantaneous output power, and the second stage is formed by an integrating circuit which determines the average power value, resulting in a rippled continuous voltage, proportional to the active power delivered to the patient or biological tissue. Results Practical tests of the compensation technical are statistically evaluated by means of linear regressions. Results of 23 tests are summarized in a way to demonstrate de effectiveness of the proposed system. Conclusion Analysis of the results demonstrate the efficiency of the proposed system, whose average error is lower than 5%, and correlating them with the standard IEC 60601-2-2, that regulates the operation of electrosurgery units.
DOI: 10.6084/m9.figshare.5792286
title: Development of a skateboarding trick classifier using accelerometry and machine learning

description: Abstract Introduction Skateboarding is one of the most popular cultures in Brazil, with more than 8.5 million skateboarders. Nowadays, the discipline of street skating has gained recognition among other more classical sports and awaits its debut at the Tokyo 2020 Summer Olympic Games. This study aimed to explore the state-of-the-art for inertial measurement unit (IMU) use in skateboarding trick detection, and to develop new classification methods using supervised machine learning and artificial neural networks (ANN). Methods State-of-the-art knowledge regarding motion detection in skateboarding was used to generate 543 artificial acceleration signals through signal modeling, corresponding to 181 flat ground tricks divided into five classes (NOLLIE, NSHOV, FLIP, SHOV, OLLIE). The classifier consisted of a multilayer feed-forward neural network created with three layers and a supervised learning algorithm (backpropagation). Results The use of ANNs trained specifically for each measured axis of acceleration resulted in error percentages inferior to 0.05%, with a computational efficiency that makes real-time application possible. Conclusion Machine learning can be a useful technique for classifying skateboarding flat ground tricks, assuming that the classifiers are properly constructed and trained, and the acceleration signals are preprocessed correctly.
DOI: 10.6084/m9.figshare.5792589
title: An automatic gain control circuit to improve ECG acquisition

description: Abstract Introduction Long-term electrocardiogram (ECG) recordings are widely employed to assist the diagnosis of cardiac and sleep disorders. However, variability of ECG amplitude during the recordings hampers the detection of QRS complexes by algorithms. This work presents a simple electronic circuit to automatically normalize the ECG amplitude, improving its sampling by analog to digital converters (ADCs). Methods The proposed circuit consists of an analog divider that normalizes the ECG amplitude using its absolute peak value as reference. The reference value is obtained by means of a full-wave rectifier and a peak voltage detector. The circuit and tasks of its different stages are described. Results Example of the circuit performance for a bradycardia ECG signal (40bpm) is presented; the signal has its amplitude suddenly halved, and later, restored. The signal is automatically normalized after 5 heart beats for the amplitude drop. For the amplitude increase, the signal is promptly normalized. Conclusion The proposed circuit adjusts the ECG amplitude to the input voltage range of ADC, avoiding signal to noise ratio degradation of the sampled waveform in order to allow a better performance of processing algorithms.
DOI: 10.6084/m9.figshare.5792589.v1
title: An automatic gain control circuit to improve ECG acquisition

description: Abstract Introduction Long-term electrocardiogram (ECG) recordings are widely employed to assist the diagnosis of cardiac and sleep disorders. However, variability of ECG amplitude during the recordings hampers the detection of QRS complexes by algorithms. This work presents a simple electronic circuit to automatically normalize the ECG amplitude, improving its sampling by analog to digital converters (ADCs). Methods The proposed circuit consists of an analog divider that normalizes the ECG amplitude using its absolute peak value as reference. The reference value is obtained by means of a full-wave rectifier and a peak voltage detector. The circuit and tasks of its different stages are described. Results Example of the circuit performance for a bradycardia ECG signal (40bpm) is presented; the signal has its amplitude suddenly halved, and later, restored. The signal is automatically normalized after 5 heart beats for the amplitude drop. For the amplitude increase, the signal is promptly normalized. Conclusion The proposed circuit adjusts the ECG amplitude to the input voltage range of ADC, avoiding signal to noise ratio degradation of the sampled waveform in order to allow a better performance of processing algorithms.
DOI: 10.6084/m9.figshare.5792286.v1
title: Development of a skateboarding trick classifier using accelerometry and machine learning

description: Abstract Introduction Skateboarding is one of the most popular cultures in Brazil, with more than 8.5 million skateboarders. Nowadays, the discipline of street skating has gained recognition among other more classical sports and awaits its debut at the Tokyo 2020 Summer Olympic Games. This study aimed to explore the state-of-the-art for inertial measurement unit (IMU) use in skateboarding trick detection, and to develop new classification methods using supervised machine learning and artificial neural networks (ANN). Methods State-of-the-art knowledge regarding motion detection in skateboarding was used to generate 543 artificial acceleration signals through signal modeling, corresponding to 181 flat ground tricks divided into five classes (NOLLIE, NSHOV, FLIP, SHOV, OLLIE). The classifier consisted of a multilayer feed-forward neural network created with three layers and a supervised learning algorithm (backpropagation). Results The use of ANNs trained specifically for each measured axis of acceleration resulted in error percentages inferior to 0.05%, with a computational efficiency that makes real-time application possible. Conclusion Machine learning can be a useful technique for classifying skateboarding flat ground tricks, assuming that the classifiers are properly constructed and trained, and the acceleration signals are preprocessed correctly.
DOI: 10.6084/m9.figshare.6179849
title: Neuro-behavioral pattern of sleep bruxism in wakefulness

description: AbstractIntroduction: Sleep Bruxism (SB) is a non-functional rhythmic movement of the mandible with multifactorial aetiology and complex diagnose. It has been the subject of various studies over the past decades and it is considered a result of actions of the Central Nervous System modulated by Autonomous Nervous System. In this work, we test the hypothesis that SB subjects present a typical and defined neurobehavioral pattern that can be distinct from that of non-bruxers subjects and can be measured during wakefulness. Methods Fifteen sleep bruxers (experimental-group EG) and fifteen non-bruxers (control-group CG) took part in the experiments. To verify the presence and severity of SB, clinical examinations, anamneses and questionnaires, including Visual Analogic Scale - faces (VAS-f) and State-Trait Anxiety Inventory (STAI) were applied. To legitimate the diagnoses of SB, a disposable instrument (Bitestrip®) to assess the masseter activity during sleep was employed. All subjects were submitted to a set of experiments for measuring various visual evoked responses during the presentation of visual stimuli (pleasant, unpleasant and neutral images). Events in Visual Evoked Potential (VEP) were used to compare the neural responses of both CG and EG. Results VAS-f showed EG with higher perception of stress than CG (trait: p=0.05), and lower quality of life for (state: p=0.007). STAI I and II showed significant differences of anxiety between CG and EG (p=0.013 and p=0.004, respectively), being EG the highest. The EG Bitestrip scores confirmed that 100% of subjects were sleep bruxers. Significant differences were found between EG and CG for events associated with emotional (pleasant and unpleasant) images in the first 250 ms after stimulation. In general, EG subjects showed higher amplitude and shorter latency of VEP events. Conclusion It is possible to distinguish between SB and non-bruxers subjects during wakefulness, based on differences in amplitude and latency of cortical event related potentials elicited by visual stimulation. SB subjects show greater amplitudes in specific events in frontal areas when non-pleasant images are shown. Latencies tend to be anticipated in SB compared to CG subjects.
DOI: 10.6084/m9.figshare.6179849.v1
title: Neuro-behavioral pattern of sleep bruxism in wakefulness

description: AbstractIntroduction: Sleep Bruxism (SB) is a non-functional rhythmic movement of the mandible with multifactorial aetiology and complex diagnose. It has been the subject of various studies over the past decades and it is considered a result of actions of the Central Nervous System modulated by Autonomous Nervous System. In this work, we test the hypothesis that SB subjects present a typical and defined neurobehavioral pattern that can be distinct from that of non-bruxers subjects and can be measured during wakefulness. Methods Fifteen sleep bruxers (experimental-group EG) and fifteen non-bruxers (control-group CG) took part in the experiments. To verify the presence and severity of SB, clinical examinations, anamneses and questionnaires, including Visual Analogic Scale - faces (VAS-f) and State-Trait Anxiety Inventory (STAI) were applied. To legitimate the diagnoses of SB, a disposable instrument (Bitestrip®) to assess the masseter activity during sleep was employed. All subjects were submitted to a set of experiments for measuring various visual evoked responses during the presentation of visual stimuli (pleasant, unpleasant and neutral images). Events in Visual Evoked Potential (VEP) were used to compare the neural responses of both CG and EG. Results VAS-f showed EG with higher perception of stress than CG (trait: p=0.05), and lower quality of life for (state: p=0.007). STAI I and II showed significant differences of anxiety between CG and EG (p=0.013 and p=0.004, respectively), being EG the highest. The EG Bitestrip scores confirmed that 100% of subjects were sleep bruxers. Significant differences were found between EG and CG for events associated with emotional (pleasant and unpleasant) images in the first 250 ms after stimulation. In general, EG subjects showed higher amplitude and shorter latency of VEP events. Conclusion It is possible to distinguish between SB and non-bruxers subjects during wakefulness, based on differences in amplitude and latency of cortical event related potentials elicited by visual stimulation. SB subjects show greater amplitudes in specific events in frontal areas when non-pleasant images are shown. Latencies tend to be anticipated in SB compared to CG subjects.
DOI: 10.6084/m9.figshare.6179840.v1
title: Kinematic and electromyographic analysis of school children gait with and without load in the backpack

description: AbstractIntroduction: Excessive load on the backpacks can lead to musculoskeletal injuries and gait alterations. The objective of this study was to analyze the electromyographic (EMG) activity in association to the kinematic during the stance and balance phases of gait performed with and without the use of the backpack. Methods Twelve volunteers have executed a gait cycle in 3 tasks: without the school backpack (SM), with a backpack with load equivalent to 10% (M10) and 20% (M20) of the body weight (BW). It was evaluated the ankle, knee and hip angular excursion (AE), linear displacement (LD) of the toe and ankle, knee, hip, shoulder, head and EMG activity of the tibialis anterior (TA), vastus medialis (VM), rectus abdominis (RA), gastrocnemius lateral (GL), biceps femoris (BF) and spinal erector (EE) muscles. Results In the LD in the stance phase there was an AP increase for the toe and ankle, hip and head (p&lt;0.043). In the balance phase for VT (vertical) direction, the shoulder presented a smaller displacement as well as the toe, ankle, knee, hip, shoulder and head in the ML direction. In the AP direction, the toe displacement was smaller as well as the ankle (p &lt; 0.038). The AE in both phases was smaller for the hip (p &lt;0.006). In the balance phase the IEMG was higher for the RA (p = 0.034). Conclusion These results suggest that the transport of school backpacks with loads of more than 10%BW causes changes in the kinematic and in the muscular recruitment pattern.
DOI: 10.6084/m9.figshare.6179840
title: Kinematic and electromyographic analysis of school children gait with and without load in the backpack

description: AbstractIntroduction: Excessive load on the backpacks can lead to musculoskeletal injuries and gait alterations. The objective of this study was to analyze the electromyographic (EMG) activity in association to the kinematic during the stance and balance phases of gait performed with and without the use of the backpack. Methods Twelve volunteers have executed a gait cycle in 3 tasks: without the school backpack (SM), with a backpack with load equivalent to 10% (M10) and 20% (M20) of the body weight (BW). It was evaluated the ankle, knee and hip angular excursion (AE), linear displacement (LD) of the toe and ankle, knee, hip, shoulder, head and EMG activity of the tibialis anterior (TA), vastus medialis (VM), rectus abdominis (RA), gastrocnemius lateral (GL), biceps femoris (BF) and spinal erector (EE) muscles. Results In the LD in the stance phase there was an AP increase for the toe and ankle, hip and head (p&lt;0.043). In the balance phase for VT (vertical) direction, the shoulder presented a smaller displacement as well as the toe, ankle, knee, hip, shoulder and head in the ML direction. In the AP direction, the toe displacement was smaller as well as the ankle (p &lt; 0.038). The AE in both phases was smaller for the hip (p &lt;0.006). In the balance phase the IEMG was higher for the RA (p = 0.034). Conclusion These results suggest that the transport of school backpacks with loads of more than 10%BW causes changes in the kinematic and in the muscular recruitment pattern.
DOI: 10.6084/m9.figshare.6179618.v1
title: AD-SISCOLO: a decision-support tool to aid the management of a cervical cancer screening program

description: AbstractIntroduction: This paper aims to develop a data warehouse (AD-SISCOLO) in order to support the management of the cervical cancer screening program in the municipality of Rio de Janeiro/Brazil. As a part of the management process, the program managers of the municipality perform tedious manual work in order to calculate a series of performance indicators and then take decisions based on them. Methods AD-SISCOLO was implemented using the Pentaho BI Suite Business Intelligence Platform and the MySQL database management system. The indicators to be calculated and visualized in the tool were based on the municipal data of the cytopathology and histopathology tests from January 2012 until December 2014, which was obtained from the Information System of Cervical Cancer (SISCOLO) after a record linkage process. The follow-up indicators were based on a simplified version of the Brazilian guidelines for the cervical cancer screening. Results AD-SISCOLO allows the visualization of a set of test-based and follow-up indicators from different views and dimensions, which enable managers to monitor all the phases of the screening process and to identify the process’ failures. Conclusions Compared with the current available environments in Brazil, AD-SISCOLO is unique in its visualization of the follow-up indicators of groups of women, according to their test results and age. Thereby it provides presentation flexibility to suit the program manager's needs.
DOI: 10.6084/m9.figshare.6179618
title: AD-SISCOLO: a decision-support tool to aid the management of a cervical cancer screening program

description: AbstractIntroduction: This paper aims to develop a data warehouse (AD-SISCOLO) in order to support the management of the cervical cancer screening program in the municipality of Rio de Janeiro/Brazil. As a part of the management process, the program managers of the municipality perform tedious manual work in order to calculate a series of performance indicators and then take decisions based on them. Methods AD-SISCOLO was implemented using the Pentaho BI Suite Business Intelligence Platform and the MySQL database management system. The indicators to be calculated and visualized in the tool were based on the municipal data of the cytopathology and histopathology tests from January 2012 until December 2014, which was obtained from the Information System of Cervical Cancer (SISCOLO) after a record linkage process. The follow-up indicators were based on a simplified version of the Brazilian guidelines for the cervical cancer screening. Results AD-SISCOLO allows the visualization of a set of test-based and follow-up indicators from different views and dimensions, which enable managers to monitor all the phases of the screening process and to identify the process’ failures. Conclusions Compared with the current available environments in Brazil, AD-SISCOLO is unique in its visualization of the follow-up indicators of groups of women, according to their test results and age. Thereby it provides presentation flexibility to suit the program manager's needs.
DOI: 10.6084/m9.figshare.6179456
title: Finite element simulation of fracture in a restored premolar tooth using high aspect ratio elements

description: Abstract Introduction The term cracked tooth syndrome refers to an incomplete fracture of a vital posterior tooth that involves the dentin and occasionally extends into the pulp. There is a very limited number of publications trying to model dentin crack growth using numerical techniques. Therefore, it is essential to numerically model this phenomenon in order to improve the clinical procedures. Methods A 2D finite element model is proposed to simulate crack initiation and propagation in a restored premolar tooth. The geometric model was based on computed tomography data. A special finite element technique, named mesh fragmentation technique, is used to model and analyze the behavior of the tooth. This technique was used to model cracks in quasi-brittle materials based on the use of interface solid finite elements with high aspects ratio. A tension damage constitutive relation between stresses and strains consistent with the continuous strong discontinuity approach is used to describe crack formation and propagation. Results The main aspects of modeling technique and procedures are explained in detail as well as the whole results, including both elastic and fracture analyses of the restored tooth. Conclusion The results of the current fracture analysis show that, under various loading conditions, there is no crack initiation in the restored tooth under typical loading magnitude. However, in the case of tooth with a pre-existing crack, which can be aroused during the restoration process, a crack propagation was observed, while they did not reach a critical fracture state.
DOI: 10.6084/m9.figshare.6179456.v1
title: Finite element simulation of fracture in a restored premolar tooth using high aspect ratio elements

description: Abstract Introduction The term cracked tooth syndrome refers to an incomplete fracture of a vital posterior tooth that involves the dentin and occasionally extends into the pulp. There is a very limited number of publications trying to model dentin crack growth using numerical techniques. Therefore, it is essential to numerically model this phenomenon in order to improve the clinical procedures. Methods A 2D finite element model is proposed to simulate crack initiation and propagation in a restored premolar tooth. The geometric model was based on computed tomography data. A special finite element technique, named mesh fragmentation technique, is used to model and analyze the behavior of the tooth. This technique was used to model cracks in quasi-brittle materials based on the use of interface solid finite elements with high aspects ratio. A tension damage constitutive relation between stresses and strains consistent with the continuous strong discontinuity approach is used to describe crack formation and propagation. Results The main aspects of modeling technique and procedures are explained in detail as well as the whole results, including both elastic and fracture analyses of the restored tooth. Conclusion The results of the current fracture analysis show that, under various loading conditions, there is no crack initiation in the restored tooth under typical loading magnitude. However, in the case of tooth with a pre-existing crack, which can be aroused during the restoration process, a crack propagation was observed, while they did not reach a critical fracture state.
DOI: 10.6084/m9.figshare.6179801.v1
title: A wavelet-based method for power-line interference removal in ECG signals

description: Abstract Introduction The analysis of electrocardiogram (ECG) signals allows the experts to diagnosis several cardiac disorders. However, the accuracy of such diagnostic depends on the signals quality. In this paper it is proposed a simple method for power-line interference (PLI) removal based on the wavelet decomposition, without the use of thresholding techniques. Methods This method consists in identifying the ECG and noise frequency range for further zeroing wavelet detail coefficients in the subbands with no ECG coefficients in the frequency content. Afterward, the enhanced ECG signal is obtained by the inverse discrete wavelet transform (IDWT). In order to choose the wavelet function, several experiments were performed with synthetic signals with worse Signal-to-Noise Ratio (SNR). Results Considering the relative error metrics and runtime, the best wavelet function for denoising was Symlet 8. Twenty synthetic ECG signals with different features and eight real ECG signals, obtained in the Physionet Challenge 2011, were used in the experiments. Results show the advantage of the proposed method against thresholding and notch filter techniques, considering classical metrics of assessment. The proposed method performed better for 75% of the synthetic signals and for 100% of the real signals considering most of the evaluation measures, when compared with a thresholding technique. In comparison with the notch filter, the proposed method is better for all signals. Conclusion The proposed method can be used for PLI removal in ECG signals with superior performance than thresholding and notch filter techniques. Also, it can be applied for high frequencies denoising even without a priori frequencies knowledge.