Arduino and Kinect Projects

Melgar, Enrique Ramos; Díez, Ciriaco Castro; Jaworski, Przemek

doi:10.1007/978-1-4302-4168-3

Cited by 15 publications

(3 citation statements)

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“…No desenvolvimento deste trabalho foi utilizado o dispositivo Microsoft Kinect (em sua versão 360) que faz uso de uma técnica chamada Structured-Light 3D Scanning, bem explicada na referência a seguir [Melgar e Diez 2012]. Com base nessa técnica, o Kinect cria um modelo de esqueleto composto pelas coordenadas dos pontos do corpo.…”

Section: Dispositivo Kinectunclassified

Modelagem de Captura de Movimentos para Estudo da Estabilidade Corporal Utilizando Kinect

Oliveira¹,

Menuchi²,

Ambrósio³

2022

Anais Estendidos Do XXII Simpósio Brasileiro De Computação Aplicada À Saúde (SBCAS 2022)

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O presente trabalho teve como objetivo obter um modelo de utilização do sensor de movimento Kinect para experimentação e análise da cinemática corporal, com vistas ao estudo das oscilações posturais, uma vez que a literatura traz pouca informação sobre modelos computacionais utilizados na utilização de dispositivos de captura de movimentos. Portanto, uma rotina para o cálculo do CM foi desenvolvida com a utilização do método cinemático e de dados antropométricos para processar os dados em conjunto com os teste em postura ortostática (teste estático).

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Section: Dispositivo Kinectunclassified

Modelagem de Captura de Movimentos para Estudo da Estabilidade Corporal Utilizando Kinect

Oliveira¹,

Menuchi²,

Ambrósio³

2022

Anais Estendidos Do XXII Simpósio Brasileiro De Computação Aplicada À Saúde (SBCAS 2022)

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“…Through skeletal tracking, the real coordinates of the entire user's skeletal joint are stored, which is used to calculate the width of the arm, forearm, thigh, calf and shoulder. The similarity between two user skeleton data is measured by multidimensional vector subtraction and vector based Cartesian coordinate system [21], as shown in Equation 1…”

Section: User Recognitionmentioning

confidence: 99%

Applying Creative Computing in the Analysis of Smart Tourism Research in China

Peng¹,

Peng²,

Li³

et al. 2019

IJPE

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In order to satisfy the needs of people's intelligent home environment, this paper proposes an intelligent home control system based on gesture recognition technology. To obtain and recognize gestures of human by the depth data, skeleton data and 3D point clouds uses Kinect. The Arduino microprocessor is used to process the received data to realize the intelligent control of home appliances. The body mass index BMI was generated by the acquired biological characteristics, and detects the user's physical condition. The experimental results show that the system can achieve effective control of household appliances and accurately measure human biological characteristics by receiving and recognizing human body posture. It proves that the system is innovative and practical.

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“…Для калібрування сенсорів та отримання даних, використано середовище для програмування мікроконтролерів Arduino IDE[6]. Код програми для калібрування представлено наступним чином:…”

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Розробка Стенду Для Вимірювання Метрологічних Характеристик Електродвигунів

Kvasnikov¹,

Квашук²,

Kataieva³

2021

aktt

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The problems of accurate measurement of the forces transmitted to the rotating shafts of electric motors have been solved for more than one century. At the same time, they have not lost their relevance, which is due to the wide development and variety of electric motors and power plants, the specific operating conditions of which require the use of a wide arsenal of measuring instruments. An important aspect in the process of using high-precision electric motors in such areas as medicine, vehicles, military-industrial complex is the improvement of the metrological characteristics of measuring equipment. In such conditions, power measurements at high-speed installations, where in some cases conventional measurement systems are either unsuitable or have low accuracy, are of particular importance. At the same time, in the absence of means of accurate determination of the error, attempts are made to predict them, which makes it possible to determine the influence of subtle factors on the efficiency of power plants. Even under optimal conditions for the functioning of measuring instruments, due to the influence of a number of factors, gross errors may appear. Such errors are unpredictable, and their significance is difficult to predict. To prevent the impact of negative factors on the operation of measuring instruments, additional sensors are often used, for example, to identify unnecessary vibrations, vibrometers are used in parallel with strain gauges. In the absence of such additional measuring sensors, in order to identify gross errors in diagnosing the characteristics of the moment of force, it is advisable to use machine learning tools, factor analysis techniques, simulation modeling, and other forecasting tools. With the help of such methods, among the sampling of data obtained from strain gauges, or other sensors, for measuring the moment of force, it is possible to identify deviations from normal operation, through certain frequency patterns of such influences. Among the many works describing the characteristics of errors in measuring physical quantities, there are not many that are devoted to predicting the accuracy of measuring sensors. Thus, when the measured conditions change, gross errors occur that negate the process of controlling electric motors, which is often the cause of an emergency condition. To solve this problem, you need simple and affordable tools that will allow you to form a classification of deviations in measurement errors. However, taking into account a significant number of factors of influence on the measuring medium, this can be realized only under the condition of an individual approach to the construction of measuring instruments. For this purpose, a stand was developed for measuring the metrological characteristics of electric motors. It was tested in conditions of increased vibration. The results of such tests made it possible to determine the deviations from the nominal error value of the strain gauge sensor.And also highlight a number of features of such a deviation caused by the frequency characteristics of the pulse source. The structure of the software and technical characteristics of the proposed stand and its comparison with existing analogs, as well as the functional and electrical circuit are presented. As a result of testing the proposed stand, a classification of factors influencing the accuracy of strain gauges was developed.

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Arduino and Kinect Projects

Cited by 15 publications

References 0 publications

Modelagem de Captura de Movimentos para Estudo da Estabilidade Corporal Utilizando Kinect

Modelagem de Captura de Movimentos para Estudo da Estabilidade Corporal Utilizando Kinect

Applying Creative Computing in the Analysis of Smart Tourism Research in China

Розробка Стенду Для Вимірювання Метрологічних Характеристик Електродвигунів

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