This article discusses the possibilities of self-regulation processes and control of physiological functions of the human body to restore the biochemical components of disturbances in various pathologies. The possibilities of research and forecasting of the functional state on the basis of the previously proposed methods and technical means of the functional state control by evaluating of physiological parameters in the operator activities were studied. Using the technology of research in operator activity and on the basis of the obtained data, the technique to control the functional state of human body at drug intake according to a diagnosis was developed. For this purpose a self-regulatory system with the afferent and efferent connections, proposed by P. K. Anokhin, was applied. The technical means are provided by an information feedback, which activates the efferent feed-back and gives possibility of control the functional state of the organism when receiving information in coded forms. In this article, the original is the drug dosage control depending on the state changes of the human body. To ensure information feedback and generating signals in coded forms, the physiological parameters depending on the diagnosis are registered. The results are compared with normalized values, which are stored in the memory unit. According to the obtained data, an image on the monitor, which is used as a source of information for the patient, is formed.
Abstract
This paper presents an Open Platform Activity and health monitoring systems which are also called e-Health systems. These systems measure and store parameters that reflect changes in the human body. Due to continuous monitoring (e.g. in rest state and in physical effort state), a specialist can learn about the individual's physiological parameters. Because the human body is a complex system, the examiner can notice some changes within the body by looking at the physiological parameters. Six different sensors ensure us that the patient's individual parameters are monitored. The main components of the device are: A Raspberry Pi 3 small single-board computer, an e-Health Sensor Platform by Cooking-Hacks, a Raspberry Pi to Arduino Shields Connection Bridge and a 7-inch Raspberry Pi 3 touch screen. The processing unit is the Raspberry Pi 3 board. The Raspbian operating system runs on the Raspberry Pi 3, which provides a solid base for the software. Every examination can be controlled by the touch screen. The measurements can be started with the graphical interface by pressing a button and every measured result can be represented on the GUI’s label or on the graph. The results of every examination can be stored in a database. From that database the specialist can retrieve every personalized data.
A systematic case study is presented in which eight chronic adult stutterers underwent an electromyographic (EMG) biological feedback training program designed to reduce masseter muscle tension in an effort to improve fluency. All subjects mastered the program within 10 30-min. sessions. Measures of muscle tension and fluency indicated improvements at the end of treatment that were maintained at 3- to 6-mo. follow-up.
The Dong carpentry rule is reflective of the Dong's culture, traditions and construction methods related to human measurement. It is dimensioned by a comparable set of lucky and unlucky units instead of abstract geometries, indicating the favorable and unfavorable units that can be applied in construction. As a measurement system derived from the human body, the units celebrate more critical sections such as the head, feet or joints, relating to the proportions of the ‘master craftsman's body. Thus, on a construction site, the representation of the human body acts to convey scale and measurement, and particularly, this ruler holds the human proportion for sacred and public buildings, specifically Drum Towers and ‘Wind and Rain’ bridges. In this paper, the measuring system will be explored to show how it is made and assists the carpenters in dimensioning their buildings. This measurement system establishes a relationship between the construction and their beliefs.
Air speed affects convective and evaporative heat losses from the human body. Some physiological parameters such as conduction speeds of nerves and body temperature are considered to can directly indicate the responses of human body to air speed. The aim of this paper is to seek the appropriate physiological parameters and acquire the primary affected trends. The research methods included questionnaire, physic test, and physiology test. Through changing the indoor air speed, tested the body temperature, conduction speeds of sensory nerve and motorial nerve of the subjects and recorded the subjects subjective thermal senses. With the increase of blowing time, the conduction speeds of sensory nerve and motorial nerve both tend to diminish. The thermal senses vote changes quickly from neutrality to light cool and cool. This experiment also shows thermal comfort senses can be expressed with the quantification form of the physiology indexes.
The research aim was to analyse the influence of velocity and size of markers
on the accuracy of motion capture measurement utilising image processing with
the use of OpenCV. On the basis of the obtained results, the usefulness of the
applied measurement method in studying the kinematics of the human body
while driving operating a wheelchair was determined. This article presents the
test results for a low-budget motion capture measurement system for testing
the kinematics of the human body in a single plane. The tested measuring
system includes a standard activity camera Xiaomi Yi4K, expanded polystyrene
markers with printed ArUco codes, and original software for marker position
detection developed by the author. The analysis of the measurement method
with regard to its applicability in biomechanical studies has highlighted several
key factors: the number of measuring points, measurement accuracy expressed
as a relative error and the limit velocity at which the marker trajectory is correctly
represented. The article shows that the limit velocity of the marker is 2.2 m/s
for 50x50 mm markers and 1.4 m/s for 30x30 mm markers. The number of
measured points ranged from 233 to 2,457 depending on the marker velocity.
The relative error did not exceed 5% for the marker velocities and thus provided
a correct representation of its trajectory.
Activity and health monitoring systems