Local web-server of telemetric system with modbus interaction sensors

With the development of microprocessor components and, accordingly, a significant expansion of the use of computer technologies, remote measurement techniques are being developed. These include telemetry and remote control of technical systems or their components in industry, research, home appliances and other fields. In this paper, the author suggests how to build a local web-server based on a microcontroller with an ARM Cortex-M4 core, which can be interacted with via an http-browser with Internet access. The block diagram of the local web-server on the basis of the STM32F407 microcontroller with the ARM Cortex-M4 core is suggested. Hardware modeling of the local web-server with a two-processor architecture including the main controller and the Modbus processor with the RS-485 interface, which provides information exchange via the Modbus RTU protocol, is done. The main controller is equipped with an indicator system based on functionally programmable LED indicators, an LCD indicator of type BC1602A, a local keyboard, USB and SWD ports for debugging and programming of the microcontroller, an external Ethernet module providing a temperature sensor and the Modbus RTU relay module, which interacts with the main controller of the local web-server via the Modbus processor with the RS-485 interface using the Modbus RTU protocol. A software for interaction of the local web-server and a http-browser has been developed. The local web-server was tested with different types of http browsers, proved to be reliable and showed the response time which depends on the number of sensors and is less than 1 second in case of 9 sensors.

REMOTE MEASUREMENT OF FIRE PARAMETERS OF THE INDUSTRIAL ACCELERATOR ELECTRON GUN

A device designed for continuous remote control of the parameters of the incandescent circuit of the electronic gun of the accelerator LU-10 has been developed. The created device allows to measure with galvanic isolation of electric quantities of operating voltage and current which are under potential of 5 kV concerning the earth bus.

Automatic device for remote measuring of circularity: Development and implementation in education courses

In conjunction with the development of technology, teaching in educational institutions around the world has also changed from traditional teaching, where blackboards and chalk were used, to modern teaching with blended or completely online learning environments. Online teaching became a necessity over the past year as the COVID-19 pandemic occurred throughout the world. One of the biggest problems that arose was the impossibility of students to work with equipment on the spot during laboratory exercises. In turn, many universities have used labs with physical devices that can be launched remotely through the Internet from anywhere. One such device is presented in this paper. An automatic device for the remote measurement of geometric tolerances, circularity, was developed and applied in the teaching process at the University of Novi Sad. The exercises were performed by students who remotely started and controlled the device and measured the deviation of the actual from the defined diameter of the work piece in the desired cross section. At the end of the semester, students completed an evaluation questionnaire and expressed satisfaction with the implementation of this exercise.

Is It Possible to Estimate Average Heart Rate from Facial Thermal Imaging?

The remote measurement of heart rate (HR) could have many applications, such as health and emotional conditions monitoring. Currently, methods based on visible cameras have been developed for HR estimation. However, the employment of such techniques with scarce illumination conditions could be challenging. Infrared Thermography (IRT) could be a valuable tool to overcome this limitation. This study investigated the possibility of estimating average HR with facial IRT through a cross-validated machine learning (ML) approach. The correlation coefficient between the estimated and the measured HR was 0.7. Although preliminary, these results demonstrate the feasibility of estimating HR with IRT.

Quantitative Digitography Solves the Remote Measurement Problem in Parkinson's disease

Background: Assessment of motor signs in Parkinson's disease (PD) has required an in-person examination. However, 50% of people with PD do not have access to a neurologist. Wearable sensors can provide remote measures of some motor signs but require continuous data acquisition for several days. A major unmet need is reliable metrics of all cardinal motor signs, including rigidity, from a simple short active task that can be performed remotely or in the clinic. Objective: Investigate whether thirty seconds of repetitive alternating finger tapping (RAFT) on a portable quantitative digitography (QDG) device, which measures amplitude and timing, produces reliable metrics of all cardinal motor signs in PD Methods: Ninety-six individuals with PD and forty-two healthy controls performed a thirty-second QDG-RAFT task and clinical motor assessment. Eighteen individuals were followed longitudinally with repeated assessments for an average of three years and up to six years. Results: QDG-RAFT metrics differentiated individuals with PD from controls and provided validated metrics for total motor disability (MDS-UPDRS III) and for rigidity, bradykinesia, tremor, gait impairment and freezing of gait (FOG). Additionally, QDG-RAFT tracked disease progression over several years off therapy, and differentiated akinetic rigid from tremor dominant phenotypes, as well as people with from those without FOG. Conclusions: QDG is a reliable technology, which will improve access to care, allows complex remote disease management, and accurate monitoring of disease progression over time in PD. QDG-RAFT also provides the comprehensive PD motor metrics needed for therapeutic trials.

COVID-19 Pandemic Impacts on the Mental Health of Professional Soccer: Comparison of Anxiety Between Genders

This study verifies associated factors with trait and state anxiety in professional soccer teams during the COVID-19 pandemic. The sample was composed of 315 athletes, coaches, and physical trainers of professional soccer teams during the COVID-19 pandemic. From this amount, 214 were classified with trait anxiety, and 315 were classified with state anxiety using the State-Trait Anxiety Inventory (STAI). This study is an epidemiological and cross-sectional study. We applied an observational method, and we performed a remote measurement. The measurement was made via online questionnaires in male and female individuals working on soccer teams (soccer professionals or athletes) who could be affected by anxiety during social isolation in the COVID-19 pandemic. Each questionnaire was composed of sociodemographic questions, self-perceived performance, and STAI. The main results indicated a significant difference between female vs. male soccer professionals in state anxiety (54.97 ± 9.43 vs. 57.65 ± 9.48 index) and trait anxiety (54.21 ± 5.74 vs. 55.76 ± 6.41 index) with higher results in men. Sociodemographic variables impacted significant differences between female and male athletes and professionals of soccer clubs, and anxiety during the pandemic COVID-19 period impacted self-perceived performance analysis. The present results highlight the importance of cognitive behavior therapy for professional soccer teams.

Analysis of the vibro-acoustic data from test rig -comparison of acoustic and vibrational methods

Detection of damage is a significant issue in providing efficiency and safety in industrial processes. In underground mining much research effort is made for developing an automatic system of diagnosing the machinery using robots. One of the major groups of equipment utilized and maintained in the mines is rotating machinery. Local damage occurring in such machines commonly have a cyclostationary character in short term as any change in their characteristics is expected to repeat periodically. In most cases they can be easily detected based on vibration signals measured with contact sensors (accelerometers). However if mobile robots such as UAV (unmanned aerial vehicles) are planned to be used, remote measurement is firmly preferred. In this paper we compare vibrational detection with a novel approach based on analysing an acoustic signal recorded by a microphone.

The impact of data from remote measurement technology on the clinical practice of healthcare professionals in depression, epilepsy and multiple sclerosis: survey

Background A variety of smartphone apps and wearables are available both to help patients monitor their health and to support health care professionals (HCPs) in providing clinical care. As part of the RADAR-CNS consortium, we have conducted research into the application of wearables and smartphone apps in the care of people with multiple sclerosis, epilepsy, or depression. Methods We conducted a large online survey study to explore the experiences of HCPs working with patients who have one or more of these conditions. The survey covered smartphone apps and wearables used by clinicians and their patients, and how data from these technologies impacted on the respondents' clinical practice. The survey was conducted between February 2019 and March 2020 via a web-based platform. Detailed statistical analysis was performed on the answers. Results Of 1009 survey responses from HCPs, 1006 were included in the analysis after data cleaning. Smartphone apps are used by more than half of responding HCPs and more than three quarters of their patients use smartphone apps or wearable devices for health-related purposes. HCPs widely believe the data that patients collect using these devices impacts their clinical practice. Subgroup analyses show that views on the impact of this data on different aspects of clinical work varies according to whether respondents use apps themselves, and, to a lesser extent, according to their clinical setting and job role. Conclusions Use of smartphone apps is widespread among HCPs participating in this large European survey and caring for people with epilepsy, multiple sclerosis and depression. The majority of respondents indicate that they treat patients who use wearables and other devices for health-related purposes and that data from these devices has an impact on clinical practice.