A hybrid linear discriminant analysis and genetic algorithm to create a linear model of aging when performing motor tasks through inertial sensors positioned on the hand and forearm.

BACKGROUND: During the aging process, cognitive functions and performance of the muscular and neural system show signs of decline, thus making the elderly more susceptible to disease and death. These alterations, which occur with advanced age, affect functional performance in both the lower and upper members, and consequently human motor functions. Objective measurements are important tools to help understand and characterize the dysfunctions and limitations that occur due to neuromuscular changes related to advancing age. Therefore, the objective of this study is to attest to the difference between groups of young and old individuals through manual movements and whether the combination of features can produce a linear correlation concerning the different age groups. METHODS: This study counted on 99 participants, these were divided into 8 groups, which were grouped by age. The data collection was performed using inertial sensors (positioned on the back of the hand and on the back of the forearm). Firstly, the participants were divided into groups of young and elderly to verify if the groups could be distinguished through the features alone. Following this, the features were combined using the linear discriminant analysis (LDA), which gave rise to a singular feature called the LDA-value that aided in verifying the correlation between the different age ranges and the LDA-value. RESULTS: The results demonstrated that 125 features are able to distinguish the difference between the groups of young and elderly individuals. The use of the LDA-value allows for the obtaining of a linear model of the changes that occur with aging in the performance of tasks in line with advancing age, the correlation obtained, using Pearson's coefficient, was 0.86. CONCLUSION: When we compare only the young and elderly groups, the results indicate that there is a difference in the way tasks are performed between young and elderly individuals. When the 8 groups were analyzed, the linear correlation obtained was strong, with the LDA-value being effective in obtaining a linear correlation of the eight groups, demonstrating that although the features alone do not demonstrate gradual changes as a function of age, their combination established these changes.

Prevalence of distinct types of hardware failures related to deep brain stimulation.

Deep brain stimulation (DBS) is an effective treatment of several types of neurological conditions, including Parkinson's disease, essential tremor, dystonia, and epilepsy. Despite technological progress in the past 10 years, the number of studies reporting side effects of DBS has increased, mainly due to hardware failures. This review investigated studies published between 2017 and 2021 to identify the prevalence of distinct types of hardware failures related to DBS. In total, fifteen studies were selected for the estimate of the prevalence of five distinct types of hardware failures: high impedance, fracture or failure of the lead or other parts of the implant, skin erosion and infection, lead malposition or migration, and implantable pulse generator (IPG) malfunction. The quality evaluation of the studies suggests a need to report results including populations from distinct regions of the world so that results can be generalized. The objective analysis of the prevalence of hardware failures showed that skin erosion and infection presented the highest prevalence in relation to other hardware failures. Despite the sophistication of the surgical technique of DBS over time, there is a considerable complication rate, about 7 per 100 individuals ([Formula: see text], in which CI is the confidence interval). Future research can also include correlation analysis with the aim of understanding the correlation between distinct hardware failures and variables such as gender, type of disorder, and age.

Discrimination between healthy and patients with Parkinson's disease from hand resting activity using inertial measurement unit.

BACKGROUND: Parkinson's disease (PD) is a neurological disease that affects the motor system. The associated motor symptoms are muscle rigidity or stiffness, bradykinesia, tremors, and gait disturbances. The correct diagnosis, especially in the initial stages, is fundamental to the life quality of the individual with PD. However, the methods used for diagnosis of PD are still based on subjective criteria. As a result, the objective of this study is the proposal of a method for the discrimination of individuals with PD (in the initial stages of the disease) from healthy groups, based on the inertial sensor recordings. METHODS: A total of 27 participants were selected, 15 individuals previously diagnosed with PD and 12 healthy individuals. The data collection was performed using inertial sensors (positioned on the back of the hand and on the back of the forearm). Different numbers of features were used to compare the values of sensitivity, specificity, precision, and accuracy of the classifiers. For group classification, 4 classifiers were used and compared, those being [Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes (NB)]. RESULTS: When all individuals with PD were analyzed, the best performance for sensitivity and accuracy (0.875 and 0.800, respectively) was found in the SVM classifier, fed with 20% and 10% of the features, respectively, while the best performance for specificity and precision (0.933 and 0.917, respectively) was associated with the RF classifier fed with 20% of all the features. When only individuals with PD and score 1 on the Hoehn and Yahr scale (HY) were analyzed, the best performances for sensitivity, precision and accuracy (0.933, 0.778 and 0.848, respectively) were from the SVM classifier, fed with 40% of all features, and the best result for precision (0.800) was connected to the NB classifier, fed with 20% of all features. CONCLUSION: Through an analysis of all individuals in this study with PD, the best classifier for the detection of PD (sensitivity) was the SVM fed with 20% of the features and the best classifier for ruling out PD (specificity) was the RF classifier fed with 20% of the features. When analyzing individuals with PD and score HY = 1, the SVM classifier was superior across the sensitivity, precision, and accuracy, and the NB classifier was superior in the specificity. The obtained result indicates that objective methods can be applied to help in the evaluation of PD.

Identification of arthropathy and myopathy of the temporomandibular syndrome by biomechanical facial features.

BACKGROUND: Temporomandibular disorders (TMDs) are pathological conditions affecting the temporomandibular joint and/or masticatory muscles. The current diagnosis of TMDs is complex and multi-factorial, including questionnaires, medical testing and the use of diagnostic methods, such as computed tomography and magnetic resonance imaging. The evaluation, like the mandibular range of motion, needs the experience of the professional in the field and as such, there is a probability of human error when diagnosing TMD. The aim of this study is therefore to develop a method with infrared cameras, using the maximum range of motion of the jaw and four types of classifiers to help professionals to classify the pathologies of the temporomandibular joint (TMJ) and related muscles in a quantitative way, thus helping to diagnose and follow up on TMD. METHODS: Forty individuals were evaluated and diagnosed using the diagnostic criteria for temporomandibular disorders (DC/TMD) scale, and divided into three groups: 20 healthy individuals (control group CG), 10 individuals with myopathies (MG), 10 individuals with arthropathies (AG). A quantitative assessment was carried out by motion capture. The TMJ movement was captured with camera tracking markers mounted on the face and jaw of each individual. Data was exported and analyzed using a custom-made software. The data was used to identify and place each participant into one of three classes using the K-nearest neighbor (KNN), Random Forest, Naïve Bayes and Support Vector Machine algorithms. RESULTS: Significant precision and accuracy (over 90%) was reached by KNN when classifying the three groups. The other methods tested presented lower values of sensitivity and specificity. CONCLUSION: The quantitative TMD classification method proposed herein has significant precision and accuracy over the DC/TMD standards. However, this should not be used as a standalone tool but as an auxiliary method for diagnostic TMDs.

Feature visualization and classification for the discrimination between individuals with Parkinson's disease under levodopa and DBS treatments.

BACKGROUND: Over the years, a number of distinct treatments have been adopted for the management of the motor symptoms of Parkinson's disease (PD), including pharmacologic therapies and deep brain stimulation (DBS). Efficacy is most often evaluated by subjective assessments, which are prone to error and dependent on the experience of the examiner. Our goal was to identify an objective means of assessing response to therapy. METHODS: In this study, we employed objective analyses in order to visualize and identify differences between three groups: healthy control (N = 10), subjects with PD treated with DBS (N = 12), and subjects with PD treated with levodopa (N = 16). Subjects were assessed during execution of three dynamic tasks (finger taps, finger to nose, supination and pronation) and a static task (extended arm with no active movement). Measurements were acquired with two pairs of inertial and electromyographic sensors. Feature extraction was applied to estimate the relevant information from the data after which the high-dimensional feature space was reduced to a two-dimensional space using the nonlinear Sammon's map. Non-parametric analysis of variance was employed for the verification of relevant statistical differences among the groups (p < 0.05). In addition, K-fold cross-validation for discriminant analysis based on Gaussian Finite Mixture Modeling was employed for data classification. RESULTS: The results showed visual and statistical differences for all groups and conditions (i.e., static and dynamic tasks). The employed methods were successful for the discrimination of the groups. Classification accuracy was 81 ± 6% (mean ± standard deviation) and 71 ± 8%, for training and test groups respectively. CONCLUSIONS: This research showed the discrimination between healthy and diseased groups conditions. The methods were also able to discriminate individuals with PD treated with DBS and levodopa. These methods enable objective characterization and visualization of features extracted from inertial and electromyographic sensors for different groups.

On the Effect of Vibrotactile Stimulation in Essential Tremor.

(1) Background: Vibrotactile stimulation has been studied for tremor, but there is little evidence for Essential Tremor (ET). (2) Methods: This research employed a dataset from a previous study, with data collected from 18 individuals subjected to four vibratory stimuli. To characterise tremor changes before, during, and after stimuli, time and frequency domain features were estimated from the signals. Correlation and regression analyses verified the relationship between features and clinical tremor scores. (3) Results: Individuals responded differently to vibrotactile stimulation. The 250 Hz stimulus was the only one that reduced tremor amplitude after stimulation. Compared to the baseline, the 250 Hz and random frequency stimulation reduced tremor peak power. The clinical scores and amplitude-based features were highly correlated, yielding accurate regression models (mean squared error of 0.09). (4) Conclusions: The stimulation frequency of 250 Hz has the greatest potential to reduce tremors in ET. The accurate regression model and high correlation between estimated features and clinical scales suggest that prediction models can automatically evaluate and control stimulus-induced tremor. A limitation of this research is the relatively reduced sample size.

A specialized motion capture system for real-time analysis of mandibular movements using infrared cameras.

BACKGROUND: In the last years, several methods and devices have been proposed to record the human mandibular movements, since they provide quantitative parameters that support the diagnosis and treatment of temporomandibular disorders. The techniques currently employed suffer from a number of drawbacks including high price, unnatural to use, lack of support for real-time analysis and mandibular movements recording as a pure rotation. In this paper, we propose a specialized optical motion capture system, which causes a minimum obstruction and can support 3D mandibular movement analysis in real-time. METHODS: We used three infrared cameras together with nine reflective markers that were placed at key points of the face. Some classical techniques are suggested to conduct the camera calibration and three-dimensional reconstruction and we propose some specialized algorithms to automatically recognize our set of markers and track them along a motion capture session. RESULTS: To test the system, we developed a prototype software and performed a clinical experiment in a group of 22 subjects. They were instructed to execute several movements for the functional evaluation of the mandible while the system was employed to record them. The acquired parameters and the reconstructed trajectories were used to confirm the typical function of temporomandibular joint in some subjects and to highlight its abnormal behavior in others. CONCLUSIONS: The proposed system is an alternative to the existing optical, mechanical, electromagnetic and ultrasonic-based methods, and intends to address some drawbacks of currently available solutions. Its main goal is to assist specialists in diagnostic and treatment of temporomandibular disorders, since simple visual inspection may not be sufficient for a precise assessment of temporomandibular joint and associated muscles.

A Novel Physical Mobility Task to Assess Freezers in Parkinson's Disease.

Freezing of gait (FOG), one of the most disabling features of Parkinson's disease (PD), is a brief episodic absence or marked reduction in stride progression despite the intention to walk. Progressively more people who experience FOG restrict their walking and reduce their level of physical activity. The purpose of this study is to develop and validate a physical mobility task that induces freezing of gait in a controlled environment, employing known triggers of FOG episodes according to the literature. To validate the physical mobility tasks, we recruited 10 volunteers that suffered PD-associated freezing (60.6 ± 7.29 years-old) with new FOG-Q ranging from 12 to 26. The validation of the proposed method was carried out using inertial sensors and video recordings. All subjects were assessed during the OFF and ON medication states. The total number of FOG occurrences during data collection was 144. The proposed tasks were able to trigger 120 FOG episodes, while the TUG test caused 24. The Inertial Measurement Unit (IMU) with accelerometer and gyroscope could not only detect FOG episodes but also allowed us to visualize the three types of FOG: akinesia, festination and trembling in place.

Wrist Movement Variability Assessment in Individuals with Parkinson's Disease.

(1) Background: Parkinson's disease (PD) is a neurodegenerative disorder represented by the progressive loss of dopamine-producing neurons, it decreases the individual's motor functions and affects the execution of movements. There is a real need to include quantitative techniques and reliable methods to assess the evolution of PD. (2) Methods: This cross-sectional study assessed the variability of wrist RUD (radial and ulnar deviation) and FE (flexion and extension) movements measured by two pairs of capacitive sensors (PS25454 EPIC). The hypothesis was that PD patients have less variability in wrist movement execution than healthy individuals. The data was collected from 29 participants (age: 62.13 ± 9.7) with PD and 29 healthy individuals (60.70 ± 8). Subjects performed the experimental tasks at normal and fast speeds. Six features that captured the amplitude of the hand movements around two axes were estimated from the collected signals. (3) Results: The movement variability was greater for healthy individuals than for PD patients (p < 0.05). (4) Conclusion: The low variability seen in the PD group may indicate they execute wrist RUD and FE in a more restricted way. The variability analysis proposed here could be used as an indicator of patient progress in therapeutic programs and required changes in medication dosage.

Single channel approach for filtering electroencephalographic signals strongly contaminated with facial electromyography.

Eliminating facial electromyographic (EMG) signal from the electroencephalogram (EEG) is crucial for the accuracy of applications such as brain computer interfaces (BCIs) and brain functionality measurement. Facial electromyography typically corrupts the electroencephalogram. Although it is possible to find in the literature a number of multi-channel approaches for filtering corrupted EEG, studies employing single-channel approaches are scarce. In this context, this study proposed a single-channel method for attenuating facial EMG noise from contaminated EEG. The architecture of the method allows for the evaluation and incorporation of multiple decomposition and adaptive filtering techniques. The decomposition method was responsible for generating EEG or EMG reference signals for the adaptive filtering stage. In this study, the decomposition techniques CiSSA, EMD, EEMD, EMD-PCA, SSA, and Wavelet were evaluated. The adaptive filtering methods RLS, Wiener, LMS, and NLMS were investigated. A time and frequency domain set of features were estimated from experimental signals to evaluate the performance of the single channel method. This set of characteristics permitted the characterization of the contamination of distinct facial muscles, namely Masseter, Frontalis, Zygomatic, Orbicularis Oris, and Orbicularis Oculi. Data were collected from ten healthy subjects executing an experimental protocol that introduced the necessary variability to evaluate the filtering performance. The largest level of contamination was produced by the Masseter muscle, as determined by statistical analysis of the set of features and visualization of topological maps. Regarding the decomposition method, the SSA method allowed for the generation of more suitable reference signals, whereas the RLS and NLMS methods were more suitable when the reference signal was derived from the EEG. In addition, the LMS and RLS methods were more appropriate when the reference signal was the EMG. This study has a number of practical implications, including the use of filtering techniques to reduce EEG contamination caused by the activation of facial muscles required by distinct types of studies. All the developed code, including examples, is available to facilitate a more accurate reproduction and improvement of the results of this study.

Multidimensional Assessment of Individuals with Parkinson's Disease: Development and Structure Validation of a Self-Assessment Questionnaire.

(1) Background: Several instruments are used to assess individuals with Parkinson's disease (PD). However, most instruments necessitate the physical presence of a clinician for evaluation, were not designed for PD, nor validated for remote application. (2) Objectives: To develop and validate a self-assessment questionnaire that can be used remotely, and to assess the respondents' health condition. (3) Methods: A questionnaire, so-called Multidimensional Assessment Questionnaire for Individuals with PD (MAQPD), was developed, administered remotely, and completed by 302 people with PD. MAQPD was validated using factor analysis (FA). The participants' level of impairment was estimated using factor loadings. The scale's accuracy was assessed estimating floor and ceiling effects and Cronbach's alpha. (4) Results: FA suggested classifying the questions into daily activities, cognition, and pain. The respondents did not have extremely severe impairment (most scores ranged from 100 to 180 points), and the factors with the lowest scores were cognition and pain. The instrument had no significant floor or ceiling effects (rates less than 15%), and the Cronbach's alpha value was larger than 0.90. (5) Conclusion: MAQPD is the only remote self-administered tool found in the literature capable of providing a detailed assessment of the general health status of individuals with PD.

Wrist Rigidity Evaluation in Parkinson's Disease: A Scoping Review.

(1) Background: One of the main cardinal signs of Parkinson's disease (PD) is rigidity, whose assessment is important for monitoring the patient's recovery. The wrist is one of the joints most affected by this symptom, which has a great impact on activities of daily living and consequently on quality of life. The assessment of rigidity is traditionally made by clinical scales, which have limitations due to their subjectivity and low intra- and inter-examiner reliability. (2) Objectives: To compile the main methods used to assess wrist rigidity in PD and to study their validity and reliability, a scope review was conducted. (3) Methods: PubMed, IEEE/IET Electronic Library, Web of Science, Scopus, Cochrane, Bireme, Google Scholar and Science Direct databases were used. (4) Results: Twenty-eight studies were included. The studies presented several methods for quantitative assessment of rigidity using instruments such as force and inertial sensors. (5) Conclusions: Such methods present good correlation with clinical scales and are useful for detecting and monitoring rigidity. However, the development of a standard quantitative method for assessing rigidity in clinical practice remains a challenge.

Open-source data management system for Parkinson's disease follow-up.

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunctions. The disease affects 1% of the world population over 60 years and remains cureless. Knowledge and monitoring of PD are essential to provide better living conditions for patients. Thus, diagnostic exams and monitoring of the disease can generate a large amount of data from a given patient. This study proposes the development and usability evaluation of an integrated system, which can be used in clinical and research settings to manage biomedical data collected from PD patients. METHODS: A system, so-called Sistema Integrado de Dados Biomédicos (SIDABI) (Integrated Biomedical Data System), was designed following the model-view-controller (MVC) standard. A modularized architecture was created in which all the other modules are connected to a central security module. Thirty-six examiners evaluated the system usability through the System Usability Scale (SUS). The agreement between examiners was measured by Kendall's coefficient with a significance level of 1%. RESULTS: The free and open-source web-based system was implemented using modularized and responsive methods to adapt the system features on multiple platforms. The mean SUS score was 82.99 ± 13.97 points. The overall agreement was 70.2%, as measured by Kendall's coefficient (p < 0.001). CONCLUSION: According to the SUS scores, the developed system has good usability. The system proposed here can help researchers to organize and share information, avoiding data loss and fragmentation. Furthermore, it can help in the follow-up of PD patients, in the training of professionals involved in the treatment of the disorder, and in studies that aim to find hidden correlations in data.

Electromiographic activity during single leg jump in adolescent athletes with chronic ankle instability: A pilot study.

Chronic ankle instability (CAI) is a common condition in athletes, which can alter the muscular activity of lower limb during jump. The objective of the study was to verify the magnitude of activation, onset timing and order of recruitment of the proximal and local muscles to the ankle of young athletes with CAI during a single leg vertical jump. Thirty-seven athletes were selected and divided into: 1) CAI group and 2) control group. An electromyographic evaluation was performed during the jump on force plate. The muscles evaluated were the proximal muscles - gluteus medius (GMed), rectus femoris (RF) and local ankle muscles - tibialis anterior (TA), peroneus longus (PL) and lateral gastrocnemius (LG). In propulsion, the CAI group showed early activation of all evaluated muscles, when compared to control group (p = 0.05). No diferences were found between groups concerning magnitude of electromyographic signal and order of muscle recruitment. During landing, an increase in magnitude of the electromyographic signal of TA in the CAI group was observed and no diferences were found between groups for onset activation and order of muscle recruitment. The results can be applied to athletes' rehabilitation through specific neuromuscular control exercises, such as reaction time and local and proximal joint stabilization to optimize muscle performance and injury incidence. Therefore, in the single leg vertical jump athletes with CAI presented higher activation of the TA in the landing and an early activation of the GMed, RF, TA, PL and LG in propulsion in relation to control group.

On the use of histograms of oriented gradients for tremor detection from sinusoidal and spiral handwritten drawings of people with Parkinson's disease.

Parkinson's disease (PD), whose cardinal signs are tremor, rigidity, bradykinesia, and postural instability, gradually reduces the quality of life of the patient, making early diagnosis and follow-up of the disorder essential. This study aims to contribute to the objective evaluation of tremor in PD by introducing and assessing histograms of oriented gradients (HOG) to the analysis of handwriting sinusoidal and spiral patterns. These patterns were digitized and collected from handwritten drawings of people with PD (n = 20) and control healthy individuals (n = 20). The HOG descriptor was employed to represent relevant information from the data classified by three distinct machine-learning methods (random forest, k-nearest neighbor, support vector machine) and a deep learning method (convolutional neural network) to identify tremor in participants with PD automatically. The HOG descriptor allowed for the highest discriminating rates (accuracy 83.1%, sensitivity 85.4%, specificity 80.8%, area under the curve 91%) on the test set of sinusoidal patterns by using the one-dimensional convolutional neural network. In addition, ANOVA and Tukey analysis showed that the sinusoidal drawing is more appropriate than the spiral pattern, which is the most common drawing used for tremor detection. This research introduces a novel and alternative way of quantifying and evaluating tremor by means of handwritten drawings.

Margins of stability of persons with transtibial or transfemoral amputations walking on sloped surfaces.

Gait is a complex motor skill. However, most falls in humans occur during gait, and people with lower limb amputation have an increased risk of falls. Thus, this study evaluated the stability of persons with unilateral amputation by quantifying the margin of stability (MoS) during gait, to contribute to understanding the strategies adopted by these people to reduce falls. The participants were divided into 3 groups: persons with transtibial amputations (n = 12, 32.27 ± 10.10 years, 76.9 ± 10.3 kg, 1.74 ± 0.06 m); persons with transfemoral amputations (n = 13, 32.21 ± 8.34 years, 72.55 ± 10.23 kg, 1.73 ± 0.05 m); and controls (n = 15, 32.2 ± 10.17 years, 75.4 ± 9.25 kg, 1.75 ± 0.05 m), who walked for 4 min on a level and sloped (8% down and up) treadmill. The pelvic and foot marker kinematic data were used to estimate the center of mass and base of support, and from these, the MoS was estimated. Although both groups of persons with amputations showed higher values for the ML MoS than did the control group (transtibial: 8.81 ± 1.79, 8.97 ± 1.74, 8.79 ± 1.76, transfemoral: 10.15 ± 2.03, 10.60 ± 1.98, 10.11 ± 1.75, control: 8.13 ± 1.30, 7.18 ± 1.85, 8.15 ± 1.57, level, down, and up, respectively), only the transfemoral group presented a significant higher value compared to the control group. Our findings suggest that the documented limitations in persons with amputations, especially with transfemoral amputation, are exacerbated in situations that require more skills, such as walking on sloped surfaces, triggering protective mechanisms.

Radiographic analysis of dental implant extensions using bone grafts on dogs.

BACKGROUND: Despite the wide use of dental implants they can bring inconveniences, as the moment one reaches osseointegration, these can no longer be extended. Therefore, if a problem occurs regarding its positioning, the options open are substitution or burial of the implant. With implant substitution, there exists the risk of local bone loss and/or future loss of the new implant. PURPOSE: This study proposes a new device (implant extender) for extending the dental implant. The feasibility of this technique is verified through installing dental implant extensions onto the humerus bone of dogs with autogenous bone grafts. MATERIALS AND METHODS: Implants of 3.3 mm in diameter by 6 mm in length and implant extensions with a 3.3 mm diameter and 2.2 mm length were installed onto humerus of 4 healthy dogs, using an autogenous bone graft in a block made from ilium. The biomechanical percussion tests were performed on the implant extensions and then the implant-extension sets were removed for radiographic analysis. RESULTS: In the biomechanical percussion, none of the extensions present clinical mobility. As for the x-rays, these were analyzed by 20 professionals, who concluded that there was a 100% success rate with bone formation around the implants, 74.1% for bone neoformation of the implant extensions, and 80.1% referring to the adaptation of the implant extension. DISCUSSION AND CONCLUSION: Bone formation occurred in every installed dental implant. In most cases, there occurred bone neoformation of the extensions and adaptation of the extension/implant set, according to the x-ray analysis performed by the evaluators. An absence of clinical mobility in the extensions was also observed. Although the results were promising, these techniques still need to be researched in humans, as an alternative for reducing elongated prosthetic crowns or poorly installed implants, as well as the modification of the type of implants among other applications.

Is there a difference in balance between continent and incontinent women? / Existe diferença no equilíbrio entre mulheres continentes e incontinentes?

Abstract Introduction Urinary incontinence is defined as any involuntary loss of urine. An imbalance in the transmission of forces between the bladder and urethra, associated with deficient support of the pelvic floor muscles, contributes to an alteration in balance in women. Objective To compare balance between continent and incontinent women. Methods This was a cross-sectional study with 13 women divided into incontinent (age: 41.50 ± 9.13 years) and continent (age: 35.29 ± 4.99 years) groups. Balance assessments were performed using a force platform and electromyography: standing, with eyes open (BI_OA); standing, with eyes closed (BI_OF); standing on foam, with eyes open (ESP_OA) and closed (ESP_OF); and standing with unipedal support, with eyes open (UNI_OA). Statistical analysis was initiated after resampling of the original data using the bootstrap technique, with the α value set at 5% (p < 0.05). Results In the BI_OA task, no significant differences were found between the groups. In the BI_OF task, incontinent women showed greater displacement in the anteroposterior axis (p < 0.001), and continent women showed greater displacement in the mediolateral axis (p = 0.008). In the ESP_OA task, incontinent women showed greater displacement in both the COP_X (p = 0.003) and COP_Y (p = 0.001) axes; in the ESP_OF task, continent women showed greater displacement in the COP_X (p < 0.001) axis. In the UNI_OA task, greater anteroposterior displacement was observed among incontinent women (p = 0.008). Conclusion Continent women showed greater displacement in the mediolateral axis in the tasks with eyes closed, and incontinent women showed greater displacement in the anteroposterior axis in the BI_OF, ESP_OA, and UNI_OA tasks.

Resumo Introdução A incontinência urinária é definida como qualquer perda involuntária de urina. Um desequilíbrio na transmissão de forças entre bexiga e uretra, associado a um suporte deficitário dos músculos do assoalho pélvico, contribui para uma alteração no equilíbrio de mulheres. Objetivo Comparar o equilíbrio entre mu-lheres continentes e incontinentes. Métodos Trata-se de um estudo transversal, com 13 mulheres divididas em incontinentes (idade: 41,50 ± 9,13 anos) e continentes (idade: 35,29 ± 4,99 anos). A avaliação do equilíbrio foi realizada na plataforma de força associada à eletromi-ografia: em pé, com olhos abertos (BI_OA); em pé, com olhos fechados (BI_OF); em pé sobre uma espuma, com olhos abertos (ESP_OA) e fechados (ESP_OF); e em pé com apoio unipodal, com olhos abertos (UNI_OA). A análise estatística foi iniciada após a reamostragem dos dados originais pela técnica Bootstrap, com valor de α fixado em 5% (p < 0,05). Resultados Na avaliação do equilíbrio BI_OA, não foram encontradas diferenças significativas entre os grupos. No BI_OF, as mulheres incontinentes apresentaram maior deslocamento no eixo anteroposterior (p < 0,001), enquanto as continen-tes, no médio-lateral (p = 0,008). Na tarefa ESP_OA, as incontinentes apresentaram maior deslocamento em ambos os eixos COP_X (p = 0,003) e COP_Y (p = 0,001); já na ESP_OF, as continentes apresentaram maior deslocamento no COP_X (p < 0,001). Na tarefa UNI_OA, observou-se maior deslocamento anteroposterior entre as incontinentes (p = 0,008). Conclusão Mulheres continentes apresentaram maiores deslocamentos no eixo médio-lateral nas tarefas de olhos fechados, enquanto as incontinentes, no eixo anteroposterior nas tarefas BI_OF, ESP_OA, UNI_OA.

Eletromyography of abdominal muscles in different physical exercises: An update protocol for systematic review and meta-analysis.

BACKGROUND: The abdominal muscles are extremely important because they are directly involved in the functions of support, containment of viscera, and help in the process of expiration, defecation, urination, vomiting, and also at the time of childbirth. Many exercises and equipment are used to strengthen the abdominal muscles, and the workouts are proposed for a variety of purposes, such as preventing and rehabilitating low back pain, improving sports performance, achieving aesthetic standards, among others. Exercises that potentiate the electromyographic activity promote a greater recruitment of muscle fibers and are more effective to improve or maintain of the force. The electromyographic activity analysis allows us to reflect on the quality of the exercises proposed, consequently, to choose and order the exercises properly in a training session. METHODS: Our systematic review protocol will developed following the reporting items for the systematic review. To identify relevant studies, we sought articles on the following bases: MEDLINE, PubMed, Europubmed, SciELO, Physiotherapy Evidences Data Base (PEDro), Cochrane, and Google Scholar. The methodological quality of the studies included in the review will evaluated using a checklist and quality assessment. For intervention studies, risk of bias will estimated using the Cochrane Collaboration tool. RESULTS: The results of this study will show the electromyographic activation of the abdomen in the different types of exercises. CONCLUSION: Ethics approval was not required for this study because it was based on published studies. The results and findings of this study will be submitted and published in a scientific peer-reviewed journal. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018086172.

Gait variability and symmetry assessment with inertial sensors for quantitative discrimination of Trendelenburg sign in total hip arthroplasty patients: a pilot study based on convenience sampling

Abstract Introduction The aim of this pilot study based on convenience sampling was to analyze the feasibility to quantitatively discriminate Trendelenburg sign (TS), a characteristic drop in pelvic position during gait in hip disfunctions, in patients with total hip arthroplasty (THA), by assessing gait variability and symmetry using inertial sensors. Methods Thirteen patients with right THA, divided into two groups with (GTS, n=4) and without TS (GnTS, n=9) assessed by experienced physician, were enrolled in the study. Harris Hip Score was applied for specific evaluation of THA. The protocol consisted in walking on a level treadmill during 3 minutes with two inertial sensors attached at anterior superior iliac spine of both sides. For each left and right step, features were extracted from the Y-axis gyroscope signals: peak value, mean absolute value, standard deviation and range. For each feature, a symmetry ratio was calculated as the ratio between left and right side. Results No significant differences were found in Harris Hip Score between groups. The variability assessed by standard deviation for left step, contralateral to the replaced side, was significantly larger for GTS group (p<0.001). Significant differences in the symmetry ratios were found between GTS and GnTS for all features extracted from gyroscopes Y-axis (W=144, p<0.001). The symmetry ratios for GnTS group were approximately equal one (except for range), whereas for the GTS group they exceed the 10% criterion. Conclusion The variability and symmetry ratios of gait features extracted from inertial sensors were successful to discriminate TS in THA patients.