Nine-Axis IMU sensor fusion using the AHRS algorithm and neural networks

This paper presents data processing method for Attitude Heading and Reference System (AHRS) based on Artificial Neural Networks (ANN). The system consist of MEMS (Micro Electro-Mechanical Systems) based on Inertial Measurement Unit (IMU) consisting of tri-axis gyroscopes, accelerometers and magnetometers providing three dimensional linear accelerations and angular rates. Training data was generated by simulation fusion of samples collected during the flight of Quadcopter. The presented results shows proper functioning of the neural network. Moreover, the presented system provide the possibility to easily add other sensors e.g. GPS, in order to achieve better performance

Edge Impulse: An MLOps Platform for Tiny Machine Learning

Edge Impulse is a cloud-based machine learning operations (MLOps) platform for developing embedded and edge ML (TinyML) systems that can be deployed to a wide range of hardware targets. Current TinyML workflows are plagued by fragmented software stacks and heterogeneous deployment hardware, making ML model optimizations difficult and unportable. We present Edge Impulse, a practical MLOps platform for developing TinyML systems at scale. Edge Impulse addresses these challenges and streamlines the TinyML design cycle by supporting various software and hardware optimizations to create an extensible and portable software stack for a multitude of embedded systems. As of Oct. 2022, Edge Impulse hosts 118,185 projects from 50,953 developers

Low back pain in women before and after menopause

Low back pain is a massive problem in modern population, both in social and economic terms. It affects large numbers of women, especially those aged 45-60. Going through a perimenopausal period is associated with many symptoms, including low back pain. This paper is a review of published research on the association between the perimenopausal age and low back pain. PubMed databases were investigated. After the search was narrowed to “menopausal status, back pain”, 35 studies were found. Seven studies, which suited our area of research best, were thoroughly analyzed. All studies show increased pain when women enter this period of their life. There is no agreement among researchers regarding which stage of menopause is the most burdensome. Examples of possible treatments and physiotherapeutic methods targeting low back pain are also presented. Physiotherapeutic procedures used to treat low back pain include exercises in safe positions, balance exercises, manual therapy, massage and physical measures

Nine-Axis IMU sensor fusion using the AHRS algorithm and neural networks

This paper presents data processing method for Attitude Heading and Reference System (AHRS) based on Artificial Neural Networks (ANN). The system consist of MEMS (Micro Electro-Mechanical Systems) based on Inertial Measurement Unit (IMU) consisting of tri-axis gyroscopes, accelerometers and magnetometers providing three dimensional linear accelerations and angular rates. Training data was generated by simulation fusion of samples collected during the flight of Quadcopter. The presented results shows proper functioning of the neural network. Moreover, the presented system provide the possibility to easily add other sensors e.g. GPS, in order to achieve better performance

Gradient method of learning for stochastic kinetic model of neuron

In this paper we are focusing on the kinetic extension [4] of classic model of Hodgkin and Huxley [2]. We are showing the descent gradient method used in the learning process of neuron, which is described with stochastic kinetic model. In comparison with [1] we use only 3 weights instead of 9: gNa; gK and gL: We show that this model behaves equally accurate as the model of Hodgkin and Huxley with slighter system description

Time synchronization in distributed sensor network

Time synchronization in a distributed sensor network is a key issue. Data from the sensors are properly synchronized are very good material for further analysis. In the paper a network of medical sensors is presented. It is important to obtain a properly synchronized data from the sensors. This guarantee that the data can be processed to detect correlation between different signals. For the purpose of accurate time synchronization, the simple and efficient algorithm is presented

Multi-agent system based on Artificial Neural Network for terrain exploration

In the presented paper Multi Agent System (MAS) with automatic formation selection based on the Artificial Neural Networks (ANN) is described. Presented system aims at testing the collective behavior of robots in unknown territory, their ability to cooperate in case where information and communication are extremely limited. As an example of MAS usage, the task of searching the experimental area to find a specific point is presented

Neural controller implementation in embedded system with use of FPGA coprocessor

In this paper we propose implementation of neural control system as embedded system with coprocessor in extensible processing platform