scholarly journals Activity and health monitoring systems

2018 ◽  
Vol 11 (1) ◽  
pp. 11-14
Author(s):  
Béla-Csaba Simon ◽  
Stefan Oniga ◽  
Iuliu Alexandru Pap
Keyword(s):  
Human Body ◽  
Health Monitoring ◽  
Touch Screen ◽  
Physiological Parameters ◽  
The Body ◽  
Raspberry Pi ◽  
Monitoring Systems ◽  
Solid Base ◽  
Processing Unit ◽  
Health Monitoring Systems

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.

scholarly journals Multichannel ECG Recording from Waist using Textile Sensors

2020 ◽  
Author(s):  
Milad Alizadeh Meghrazi ◽  
Yupeng Tian ◽  
Amin Mahnam ◽  
Presish Bhattachan ◽  
Ladan Eskandarian ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Health Monitoring ◽  
Probabilistic Approach ◽  
Wearable Devices ◽  
The Body ◽  
Monitoring Systems ◽  
Multiple Sensors ◽  
Non Invasive ◽  
Health Monitoring Systems ◽  
Wearable Health Monitoring Systems

Abstract Background: The development of wearable health monitoring systems is garnering substantial interest in research and technology due to their unique capabilities in continuous, real-time, and non-invasive tracking of the physiological states of the human body. Wearable devices provide insights into the performance and health of individuals. Despite recent advances in biosensors, most of the currently available wearable devices rely solely on a single sensor attached to the body, limiting the ability to obtain reliable bio-information. However, in engineering systems, sensor fusion, which is the optimal integration and processing of data from multiple sensors, has been a common theme. In recent years due to an increase in the availability and variety of different types of sensors, the possibility of achieving sensor fusion in wearable systems has become more attainable. Sensor fusion in multi-sensing systems results in a significant enhancement of information inference compared to that from systems with a sole sensor. One step towards the development of sensor fusion for wearable health monitoring systems is the accessibility to multiple reliable electrophysiological signals, which can be recorded continuously.Results: In this paper, we develop a textile-based multi-channel ECG band that has the ability to measure from multiple locations on the waist. As a proof of concept, we show that ECG signals can be reliably obtained from different locations on the waist where the shape of the QRS complex is comparable with that recorded from the chest using traditional gel electrodes. As well, we develop a probabilistic approach to detect R-Peaks from noisy textile data in different sitting, standing, and jogging statuses. We show that the performance of the proposed algorithm is significantly better than that based on Pan-Tompkins and optimal-threshold methods. Conclusion: This band can be easily integrated into garments such as underwear, bras or pants. We predict that the textile-based multi-channel ECG band can be considered as an effective wearable system which enables the development of sensor fusion methodology for pervasive and non-invasive health monitoring through continuous tracking of heart rate variability (HRV) from the waist.

Dynamic Computation Offloading for Low-Power Wearable Health Monitoring Systems

2017 ◽  
Vol 64 (3) ◽  
pp. 621-628 ◽  
Author(s):  
Haik Kalantarian ◽  
Costas Sideris ◽  
Bobak Mortazavi ◽  
Nabil Alshurafa ◽  
Majid Sarrafzadeh
Keyword(s):  
Low Power ◽  
Health Monitoring ◽  
Computation Offloading ◽  
Monitoring Systems ◽  
Dynamic Computation ◽  
Health Monitoring Systems ◽  
Wearable Health Monitoring Systems

scholarly journals The Concept of Geodetic Analyses of the Measurement Results Obtained by Hydrostatic Leveling

Geosciences ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 406
Author(s):  
Kamiński ◽  
Makowska
Keyword(s):  
Structural Health Monitoring ◽  
Kalman Filtering ◽  
Health Monitoring ◽  
Systematic Errors ◽  
Monitoring Systems ◽  
Measurement Results ◽  
Vertical Displacements ◽  
Complete Computation ◽  
Computation Scheme ◽  
Health Monitoring Systems

The article discusses the issue of hydrostatic leveling. Its application is presented in structural health monitoring systems in order to determine vertical displacements of controlled points. Moreover, the article includes a complete computation scheme that utilizes the estimation from observation differences, allowing the elimination of the influence of individual sensors’ systematic errors. The authors suggest two concepts of processing the measurement results depending on the sensors’ connection method. Additionally, the second concept is extended by the elements allowing the prediction of the displacements by means of Kalman filtering.

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