A Smart Health Monitoring Application for Patients to Improve Health

2022 ◽  
pp. 369-382
Author(s):  
Paola Ariza-Colpas ◽  
Shariq Aziz Butt ◽  
Muhammad Imran Tariq ◽  
Roberto Cesar Morales Ortega ◽  
Muhammad Waqas Anjum ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Smart Health ◽  
Monitoring Application ◽  
Improve Health

scholarly journals Smart Health Monitoring Bodyarea Network Using Raspberry Pi

2021 ◽  
Vol 1916 (1) ◽  
pp. 012218
Author(s):  
K Mohil Varmaa ◽  
K Prendra ◽  
K V Ranjith ◽  
T Robinsingh ◽  
V Nandalal ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Raspberry Pi ◽  
Smart Health

Wearable energy-efficient fitness tracking system for sports person health monitoring application

2021 ◽  
pp. 1-13
Author(s):  
Dan Xie ◽  
Ming Zhang ◽  
Priyan Malarvizhi Kumar ◽  
Bala Anand Muthu
Keyword(s):  
Health Monitoring ◽  
Energy Efficient ◽  
Tracking System ◽  
Path Loss ◽  
Integrated Approach ◽  
Smartphone Application ◽  
Sensor Nodes ◽  
Engineering Research ◽  
Fitness Tracking ◽  
Monitoring Application

The high potential of wearable physiological sensors in regenerative medicine and continuous monitoring of human health is currently of great interest. In measuring in real-time and non-invasively highly heterogeneous constituents, have a great deal of work and therefore been pushed into creating several sports monitoring sensors. The advanced engineering research and technology lead to the design of a wearable energy-efficient fitness tracking (WE2FT) system for sports person health monitoring application. Instantaneous accelerations are measured against pulses, and specific walking motions can be tracked by this system using a deep learning-based integrated approach of an intelligent algorithm for gait phase detection for the proposed system (WE2FT). The algorithm’s effects are addressed, and the performance has been evaluated. In this study, the algorithm uses a smartphone application to track steps using the Internet of Things (IoT) technology. For this initiative, the central node’s optimal location is measured with the antenna reflectance coefficient and CM3A path loss model (IEEE 802.15.6) among the sensor nodes for energy-efficient communication. The simulation experiment results in the highest performance in terms of energy efficiency and path loss.

scholarly journals Introducing the Special Issue on “Ubiquitous Sensing for Smart Health Monitoring”

Information ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 74
Author(s):  
Yusuf A. Bhagat
Keyword(s):  
Health Monitoring ◽  
Special Issue ◽  
Ubiquitous Sensing ◽  
Smart Health

Sensors continue to pervade our surroundings in undiminished ways [...]

Smart Health Monitoring System Using GSM Technique

2021 ◽  
Author(s):  
Hanan Fathi Busedra ◽  
Lamia Fathi Abusedra ◽  
Mohamed Aljahani ◽  
Jamal Sultan
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Health Monitoring System ◽  
Smart Health

Smart health monitoring using AI techniques in AAL environments

2021 ◽  
Author(s):  
Alexandros Spournias ◽  
Panagiotis Bountas ◽  
Evanthia Faliagka ◽  
Dimitris Kontargiris ◽  
Christos Antonopoulos ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Smart Health

scholarly journals Internet of Things in the Bathroom: Smart Health-Monitoring Bidet System

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Sung-Phil Heo ◽  
Suyong Jeong
Keyword(s):  
Internet Of Things ◽  
Health Monitoring ◽  
Oxygen Sensors ◽  
Error Rates ◽  
The Internet ◽  
Spinal Diseases ◽  
International Protection ◽  
Pressure Oxygen ◽  
Smart Health ◽  
The Internet Of Things

The Internet of things (IoT) helps our everyday lives such as by monitoring objects and tracking behaviors in various settings, but studies on enhancing the bathroom experience are rare. This article describes full details about development and implementation of a smart health-monitoring bidet based on our study published previously in the conference. A smart bidet system is designed to monitor the users’ health through several contact-type sensors, such as pressure, oxygen, and thermometer. The system is equipped with a built-in artificial intelligence software platform and is designed to detect anal and spinal diseases. The attached sensors normally operate under waterproof conditions: we tested their performances under X6 international protection marking conditions. These devices were designed to operate properly even in extremely waterproof conditions. The temperature, pressure, and oxygen sensors of the bidet system had error rates of about 4.1, 0.6, and 1.1 percent, respectively.

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