RESUMO
During vertical jump evaluations in which jump height is estimated from flight time (FT), the jumper must maintain the same body posture between vertical takeoff and landing. As maintaining identical posture is rare during takeoff and landing between different jump attempts and in different individuals, we simulated the effect of changes in ankle position from takeoff to landing in vertical jumping to determine the range of errors that might occur in real-life scenarios. Our simulations account for changes in center of mass position during takeoff and landing, changes in ankle position, different subject statures (1.44-1.98 m), and poor to above-average jump heights. Our results show that using FT to estimate jump height without controlling for ankle position (allowing dorsiflexion) during the landing phase of the vertical jump can overestimate jump height by 18% in individuals of average stature and performing an average 30 cm jump or may overestimate by ≤60% for tall individuals performing a poor 10 cm jump, which is common for individuals jumping with added load. Nevertheless, as assessing jump heights based on FT is common practice, we offer a correction equation that can be used to reduce error, improving jump height measurement validity using the FT method allowing between-subject fair comparisons.
Assuntos
Postura , Humanos , Fenômenos Biomecânicos/fisiologia , Postura/fisiologia , Masculino , Tornozelo/fisiologia , Adulto , Articulação do Tornozelo/fisiologia , Feminino , Simulação por Computador , Adulto Jovem , Movimento/fisiologiaRESUMO
Background: We investigated the concurrent validity and test-retest reliability of the Jumpo 2 and MyJump 2 apps for estimating jump height, and the mean values of force, velocity, and power produced during countermovement (CMJ) and squat jumps (SJ). Methods: Physically active university aged men (n = 10, 20 ± 3 years, 176 ± 6 cm, 68 ± 9 kg) jumped on a force plate (i.e., criterion) while being recorded by a smartphone slow-motion camera. The videos were analyzed using Jumpo 2 and MyJump 2 using a Samsung Galaxy S7 powered by the Android system. Validity and reliability were determined by regression analysis, typical error of estimates and measurements, and intraclass correlation coefficients. Results: Both apps provided a reliable estimate of jump height and the mean values of force, velocity, and power. Furthermore, estimates of jump height for CMJ and SJ and the mean force of the CMJ were valid. However, the apps presented impractical or poor validity correlations for velocity and power. Compared with criterion, the apps underestimated the velocity of the CMJ. Conclusions: Therefore, Jumpo 2 and MyJump 2 both provide a valid measure of jump height, but the remaining variables provided by these apps must be viewed with caution since the validity of force depends on jump type, while velocity (and as consequence power) could not be well estimated from the apps.
Assuntos
Postura , Smartphone , Masculino , Humanos , Idoso , Reprodutibilidade dos Testes , Movimento (Física) , Gravação de VideoteipeRESUMO
BACKGROUND: In this work, we share the enhancements made in our system to take part in the CYBATHLON 2020 Global Edition Functional Electrical Stimulation (FES) Bike Race. Among the main improvements, firstly an overhaul, an overhaul of the system and user interface developed with User-centered design principles with remote access to enable telerehabilitation. Secondly, the implementation and experimental comparison between the traditional single electrode stimulation (SES) and spatially distributed sequential stimulation (SDSS) applied for FES Cycling. METHODS: We report on the main aspects of the developed system. To evaluate the user perception of the system, we applied a System Usability Scale (SUS) questionnaire. In comparing SDSS and SES, we collected data from one subject in four sessions, each simulating one race in the CYBATHLON format. RESULTS: User perception measured with SUS indicates a positive outcome in the developed system. The SDSS trials were superior in absolute and average values to SES regarding total distance covered and velocity. We successfully competed in the CYBATHLON 2020 Global Edition, finishing in 6th position in the FES Bike Race category. CONCLUSIONS: The CYBATHLON format induced us to put the end-user in the center of our system design principle, which was well perceived. However, further improvements are required if the intention is to progress to a commercial product. FES Cycling performance in SDSS trials was superior when compared to SES trials, indicating that this technique may enable faster and possibly longer FES cycling sessions for individuals with paraplegia. More extensive studies are required to assess these aspects.
Assuntos
Terapia por Estimulação Elétrica , Traumatismos da Medula Espinal , Ciclismo , Estimulação Elétrica , Terapia por Estimulação Elétrica/métodos , Humanos , Paraplegia , Traumatismos da Medula Espinal/reabilitação , Design Centrado no UsuárioRESUMO
Background and Introduction: In Brazil, the Telemedicine University Network (RUTE) initiative promotes collaboration between university hospitals, teaching hospitals, health professionals, and students using information and communication technology infrastructure to support special interest groups (SIGs) in health care. Health professionals in institutions belonging to RUTE plan a program of video conferences and/or web conferences to discuss specific themes. This article presents the results of an analysis of collaboration in these SIGs. Materials and Methods: This study uses descriptive statistical analysis and visualization of data contained in management reports provided by RUTE national coordinators for the period between 2007 and 2016 to evaluate the extent of participation in SIGs between institutions associated with RUTE. In this data visualization, we employ concepts from social network theory. Results: The analysis identified the most influential institutions as measured by social network theory metrics. A small number of institutions were found to have many participating SIGs, but most had only a few participating institutions (more than 130 institutions have only one participating SIG). Over the study period, a significant quantitative growth in collaboration occurred, increasing from 21 institutions and 92 participating SIGs in 2007 to 380 institutions and 1,912 participating SIGs in 2016. Conclusion: The growth in collaboration within the network indicates increasing interest and participation in telehealth initiatives in Brazil.
Assuntos
Comportamento Cooperativo , Rede Social , Telemedicina , Universidades , Brasil , Bases de Dados Factuais , Humanos , Opinião PúblicaRESUMO
Objetivo: Investigar o uso de técnicas para extração de conhecimento de diagnósticos provenientes de laudos de biópsia renal. Métodos: Foram aplicadas técnicas de extração de conhecimento em um conjunto de laudos de biópsia renal do Serviço de Patologia do Hospital do Rim e Hipertensão, São Paulo. Resultados: Foram extraídos 694 diagnósticos completos diferentes do conjunto de 3.018 laudos. Foi obtida uma árvore de três níveis diagnósticos e uma nuvem de palavras com os termos extraídos dos diagnósticos. A extração de terminologia resultou em 206 termos candidatos únicos que ocorreram 20.599 vezes no corpus avaliado. Conclusão: O resultado da extração de terminologia apresentou-se como satisfatório para criar uma taxonomia sobre biópsia renal. A árvore com ligação entre diagnósticos pode auxiliar novos profissionais em treinamento na área de patologia para confecção dos laudos.
Objective: To present techniques for extracting knowledge of diagnosis from renal biopsy reports. Methods: Knowledge extraction techniques were applied in a set of reports of the Pathology service of the Kidney and Hypertension Hospital. Results: From 3,018 reports 694 different complete diagnoses were extracted. A tree with three diagnostic levels and a word cloud with terms extracted from diagnoses were obtained. The terminology extraction resulted in 206 unique candidate terms that occurred 20,599 times in the evaluated corpus. Conclusion: The results of terminology extraction is suitable to create a taxonomy about renal biopsy. Trees with link between diagnoses can help new professionals in the area of pathology for writing the reports.
Objetivo: Investigar el uso de técnicas de extracción de conocimiento a partir de los informes de diagnóstico de la biopsia renal. Métodos: técnicas de extracción de conocimientos se aplicaron a un conjunto de informes de biopsia renal del Servicio de Patología del Hospital do Rim e Hipertensão, Sao Paulo. Resultados: Se obtuvieron 694 diagnósticos completos diferentes de un conjunto de 3.018 informes. Se obtuvo un árbol de tres niveles de diagnóstico y una nube de palabras con los términos extraídos de diagnóstico. La extracción de terminología resultó en 206 términos candidatos únicos que se produjeron 20.599 veces el corpus nominal. Conclusión: El resultado de la extracción de terminología se presentó como satisfactoria para crear una taxonomía acerca de biopsia renal. El árbol con la conexión entre el diagnóstico puede ayudar a los profesionales jóvenes en formación en el área de la patología para la preparación de informes.
Assuntos
Biópsia por Agulha , Mineração de Dados , Nefropatias/classificação , Nefropatias/diagnóstico , Terminologia como AssuntoRESUMO
In Brazil the Telemedicine University Network (Rede Universitária de Telemedicina RUTE) is an initiative that among others promotes collaboration between university hospitals, universities, and health professionals through information technology infrastructure and special interest groups (SIGs) support. This paper presents results of analyses on collaboration during implementation and coordination activities of RUTE SIGs. This study is based on descriptive statistics and data visualization previously collected by RUTE national coordination relative to the status in July 2014. The analysis through collaboration graph identified the strongest collaboration RUTE units. The graph also highlights the collaborative relationship of RUTE units in form of communities, the most collaborative with each other in a communion in the same SIGs, and the less the collaborative units in the network. It should be stated that the most active units are also the oldest in the community.
Assuntos
Relações Interinstitucionais , Colaboração Intersetorial , Modelos Organizacionais , Telemedicina/organização & administração , Universidades/organização & administração , Comunicação por Videoconferência/organização & administração , Brasil , Disseminação de Informação/métodosRESUMO
OBJECTIVE: To propose a semi-automated method for pattern classification to predict individuals' stage of growth based on morphologic characteristics that are described in the modified cervical vertebral maturation (CVM) method of Baccetti et al. MATERIALS AND METHODS: A total of 188 lateral cephalograms were collected, digitized, evaluated manually, and grouped into cervical stages by two expert examiners. Landmarks were located on each image and measured. Three pattern classifiers based on the Naïve Bayes algorithm were built and assessed using a software program. The classifier with the greatest accuracy according to the weighted kappa test was considered best. RESULTS: The classifier showed a weighted kappa coefficient of 0.861 ± 0.020. If an adjacent estimated pre-stage or poststage value was taken to be acceptable, the classifier would show a weighted kappa coefficient of 0.992 ± 0.019. CONCLUSION: Results from this study show that the proposed semi-automated pattern classification method can help orthodontists identify the stage of CVM. However, additional studies are needed before this semi-automated classification method for CVM assessment can be implemented in clinical practice.
Assuntos
Determinação da Idade pelo Esqueleto/métodos , Cefalometria/métodos , Vértebras Cervicais/crescimento & desenvolvimento , Teorema de Bayes , Vértebras Cervicais/anatomia & histologia , Vértebras Cervicais/diagnóstico por imagem , Técnicas de Apoio para a Decisão , Feminino , Humanos , Masculino , SoftwareRESUMO
Objetivos: Este trabalho propõe o desenvolvimento de um classificador de padrões baseado no método Cervical Vertebral Maturation (CVM), que auxilia o profissional ortodontista na determinação do período ideal para o tratamento de uma série de deformidades dentofaciais. Métodos: Para o desenvolvimento do classificador, foram coletadas 187 radiografias cefalométricas laterais e um especialista em ortodontia realizou a avaliação da idade óssea manualmente em cada imagem. Por meio de um programa computacional desenvolvido para este fim, um segundo especialista marcou os pontos de interesse das vértebras nas imagens, formando assim uma base de dados para avaliação do classificador. Algoritmos de classificação foram então avaliados por meio do software Weka. Resultados: Seis classificadores foram obtidos com base no algoritmo Bayesiano Ingênuo, um para cada estágio cervical. Os resultados da avaliação da área sob a curva ROC (AUC) para os classificadores foram: CS1, 0,88; CS2, 0,74; CS3, 0,86; CS4, 0,76; CS5, 0,82; CS6, 0,92. O software de marcação de pontos mostrou ser útil ao ortodontista, armazenando dados em longo prazo podendo ser reproduzidos de forma exata a qualquer momento. Conclusão: Os resultados indicam que o classificador de padrões obtido auxilia o ortodontista a identificar o estágio cervical em que um indivíduo se encontra.
Objectives: This paper proposes the development of a pattern classifier based on the Cervical Vertebral Maturation (CVM) method, which helps the orthodontist to determine the optimal period for treatment of a variety of dentofacial deformities. Methods: For the development of the pattern classifier, 187 lateral radiographs were taken. Then, an orthodontist did the bone age assessment in each image manually. Through a computer program developed for this purpose, a second specialist pointed the landmarks on the vertebrae in each image resulting in a database for evaluate the classifier. Classification algorithms were then evaluated using Weka software. Results: Six classifiers were obtained based on Naive Bayes algorithm, one for each cervical stage. The results of the evaluation of the area under the ROC curve (AUC) for the classifiers were: CS1, 0,88; CS2, 0,74; CS3, 0,86; CS4, 0,76; CS5, 0,82; CS6, 0,92. The landmark pointer software proved to be useful for the orthodontist, storing data for long term and be accurately reproduced at any time. Conclusion: The results indicate that a pattern classifier assists the orthodontist to identify the cervical stage an individual is.
Objetivo: En este trabajo se propone el desarrollo de un clasificador de patrones sobre la base de la maduración cervical vertebral (CVM), el cual ayuda al ortodoncista para determinar el período óptimo para el tratamiento de una variedad de deformidades dentofaciales. Método: Para el desarrollo de lo clasificador de patrones, 187 radiografías laterales fueron tomadas. Entonces, un ortodoncista hizo la evaluación de la edad ósea en cada imagen de forma manual. A través de un programa informático desarrollado para este propósito, el segundo especialista señaló los puntos de referencia en las vértebras en cada imagen en la base de datos resultante para evaluar los clasificadores. Algoritmos de clasificación utilizando el software WEKA fueron evaluados. Resultados: Seis clasificadores se obtuvieron sobre la base de algoritmo Naive Bayes, uno para cada estadio cervical. Los resultados de la evaluación del área bajo la curva ROC (AUC) para los clasificadores son: CS1, 0,88; CS2, 0,74; CS3, 0,86; CS4, 0,76; CS5, 0,82; CS6, 0,92. El software para la puntuación demostró ser útil para el ortodoncista, el almacenamiento de datos en el largo plazo puede ser reproducido con exactitud en cualquier momento. Conclusión: Los resultados indican que lo SADC ayuda al ortodoncista para identificar lo estadio cervical que una persona es.