scholarly journals On-Line and Off-Line ECG and Motion Activity Monitoring System for Athletes

2018 ◽  
Vol 3 (66) ◽  
Author(s):  
Stasys Korsakas ◽  
Alfonsas Vainoras ◽  
Liudas Gargasas ◽  
Vytenis Miškinis ◽  
Rimtautas Ruseckas ◽  
...  
Keyword(s):  
Physical Activity ◽  
Monitoring System ◽  
Activity Monitoring ◽  
Activity Level ◽  
Respiration Frequency ◽  
Hardware System ◽  
Motion Activity ◽  
On Line ◽  
Analysis System ◽  
Line Analysis

The aim of this paper is to present a new ECG and motion activity monitoring and on-line analysis system for athle-tes. The developed system is intended to facilitate the coach in optimizing and individualizing the training of elite athletes.The hardware system consists of the device for registration of ECG and accelerometer signals and wireless trans-mission to computer. The coach software works in two modes: on-line version is used during training and off-line version is designed for detailed data analysis after training. The new method for respiration frequency evaluation was developed and checked on 28 persons, and in most cases the developed algorithm correctly evaluated the respiration frequency of the investigated persons. The evaluation of athlete’s functional state from calculated and measured pa-rameters and formation of warning signals (green — normal state, yellow — limitary state and red — premonitory state) is based on the analysis applying Moore and Mealy automata algorithms. The software for the evaluation of the patient’s activity was tested on 11 healthy students: the increase in physical activity level during the brisk walk was 1.4 times higher compared to the level during the slow walk, and during the jogging sessions it was 1.89 times higher than during the slow walk.The results obtained during the investigations show that the developed ECG and motion activity monitoring system with two packages of software allows to measure cardio respiratory changes and changes in intensities of physical activity under daily conditions. The comprehensive off-line analysis by monitoring data provides the possibility for coaches to make more detailed analysis of cardio respiratory changes and changes in intensities during training.Keywords: monitoring system for athletes, electrocardiogram, accelerometry, respiration frequency.

On-Line Analysis System for Use in Obstetrical Ultrasonography

1982 ◽  
Vol 61 (s109) ◽  
pp. 127-128
Author(s):  
Russell L. Deter ◽  
George W. Batten
Keyword(s):  
On Line ◽  
Analysis System ◽  
Line Analysis

Acquisition Module Design of Fault Monitoring System of Wind Turbine

2014 ◽  
Vol 521 ◽  
pp. 108-112
Author(s):  
Yong Gui Dou ◽  
Ai Guo Chen ◽  
Shi Yong Wang ◽  
Xun Zeng Yin ◽  
Qian Wang
Keyword(s):  
Data Acquisition ◽  
Monitoring System ◽  
Fault System ◽  
Monitoring Point ◽  
Measuring Point ◽  
Module Design ◽  
Hardware System ◽  
Fault Monitoring ◽  
Wind Power Generator ◽  
On Line

In view of the present, the data acquisition system of the fault monitoring system is not perfect, so the data acquisition module of mechanical fault system of wind power generator is developed based on DSP, which better improves the on-line monitoring system. Firstly, the paper introduces the working principle of the module and the selection principle of set measuring point and monitoring point. Then, it introduces the design of hardware system in detail.

A Multi-Parameter Distributed Processing Data Acquisition, Display, and on-Line Analysis System

1979 ◽  
Vol 26 (1) ◽  
pp. 750-756
Author(s):  
R. Berube ◽  
G. Gaughran ◽  
D. Hoppe ◽  
R. Linser ◽  
D. Samsky
Keyword(s):  
Data Acquisition ◽  
Distributed Processing ◽  
Processing Data ◽  
On Line ◽  
Analysis System ◽  
Line Analysis

Research on On-Line Oil Monitoring System for High Power Mining Gearbox

2011 ◽  
Vol 130-134 ◽  
pp. 2600-2603
Author(s):  
Xue Wen Huang
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
High Power ◽  
Initial Application ◽  
System A ◽  
On Line ◽  
Analysis System ◽  
Oil Monitoring ◽  
Level Monitoring ◽  
Wear Condition

In order to realizing real-time on-line oil monitoring for high-power gearbox’s wear state during operation, a monitoring system is developed on the basis of the ferrograph sensors in this paper. By means of a multi-level monitoring system, a real-time remote monitoring and analysis system of unattended machine wear condition is achieved which can real-time display the image of the wear particles and the wear information of the gears, thus getting such advantages as timely notice and warning, reducing equipment’s damage and maintenance costs . The initial application of system on the real machine shows good results and effects.

Ambulatory Behavior Map, Physical Activity and Biosignal Monitoring System

1997 ◽  
Vol 36 (04/05) ◽  
pp. 360-363 ◽  
Author(s):  
D. Murakami ◽  
M. Makikawa
Keyword(s):  
Physical Activity ◽  
Monitoring System ◽  
Human Behavior ◽  
Daily Life ◽  
Memory Device ◽  
Physical Activities ◽  
Activity Monitoring ◽  
Physical Activity Monitoring ◽  
New System

Abstract:In this study, we have developed an ambulatory human behavior map and physical activity monitoring system. This was accomplished by equipping our portable digital biosignal memory device developed previously with GPS sensors and piezoresistive accelerometers. Using this new system, we can get a subject’s behavior map, and estimate his physical activities and posture changes in daily life.

Accelerometry-Based Motion Pattern Analysis for Physical Activity Recognition and Activity Level Assessment

2013 ◽  
Vol 479-480 ◽  
pp. 818-822 ◽  
Author(s):  
Kai Chun Liu ◽  
Chung Tse Liu ◽  
Chao Wei Chen ◽  
Chih Ching Lin ◽  
Chia Tai Chan
Keyword(s):  
Physical Activity ◽  
Chronic Diseases ◽  
Activity Recognition ◽  
Pattern Analysis ◽  
Activity Monitoring ◽  
Activity Level ◽  
Motion Pattern ◽  
Raw Data ◽  
Physical Activity Monitoring ◽  
Physical Activity Recognition

Physical inactivity is becoming a major public health concern and lead to a variety of chronic diseases. Since adequate moderate or vigorous activity can reduce the incidence of chronic diseases, noncommunicable disease and obesity. The evidence is supporting the importance of physical activity on health and well-being. However, many people nowadays live without adequate physical activity, and do not aware whether their daily activity is enough or not. The activity recognition and activity level can be used to survey the effectiveness and achievement of goals aimed at increasing physical activity. Physical activity monitoring has become a more proactive healthcare service that should build on the real-time reminding offered by healthcare solutions. Therefore, physical activity monitoring and activity level assessment are critical to maintain adequate physical activity and improve health. In this work, we present a motion patterns analysis for physical activity recognition and activity level assessment by using a wearable sensor. The proposed mechanism uses triaxial accelerometer as a sensing device. The sensor node is mounted in the right front waist, sensing and transmitting sensing data to server. The time series of raw data will be preprocessed through the aggregation technique of jumping window. The raw data will be divided into small segments and separated to gravity signal and body acceleration by filter. Through feature extraction and proposed classifier, motion pattern analysis is achieved. The classifier consists of activity recognition and activity level assessment algorithms. The results have demonstrated that the proposed methods can achieve 94.7%, 87.0% accuracy of activity recognition and activity level estimation respectively.

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