Sleep Stage Estimation ALgorithm as a One Application for the Ubiquitous Medical and Health Care Monitoring

2013 ◽  
pp. 680-699
Keyword(s):  
Health Care ◽  
Sleep Stage ◽  
Estimation Algorithm ◽  
Stage Estimation ◽  
Health Care Monitoring

Health Care Monitoring System

2019 ◽  
Vol 7 (9) ◽  
pp. 44-48
Author(s):  
Rahul Pawar ◽  
M.M. Sardeshmukh ◽  
Sagar Shinde
Keyword(s):  
Health Care ◽  
Monitoring System ◽  
Health Care Monitoring

Review on Health Care Monitoring System

2019 ◽  
Vol 7 (6) ◽  
pp. 1114-1117
Author(s):  
Rahul Pawar ◽  
M.M. Sardeshmukh ◽  
Sagar Shinde
Keyword(s):  
Health Care ◽  
Monitoring System ◽  
Health Care Monitoring

scholarly journals All-Fiber Pyro- and Piezo-electric Nanogenerator for IoT Based Self-Powered Health-Care Monitoring

2021 ◽  
Author(s):  
Biswajit Mahanty ◽  
Sujoy Kumar Ghosh ◽  
Kuntal Maity ◽  
KRITTISH ROY ◽  
Subrata Sarkar ◽  
...  
Keyword(s):  
Health Care ◽  
Carbon Nanotube ◽  
Vinylidene Fluoride ◽  
Electrospun Nanofibers ◽  
Multiwall Carbon Nanotube ◽  
Poly Vinylidene Fluoride ◽  
Self Powered ◽  
Health Care Monitoring ◽  
Multiwall Carbon ◽  
Piezo Electric

In this work, an all-fiber pyro- and piezo-electric nanogenerator (PPNG) is designed by multiwall carbon nanotube (MWCNT) doped poly(vinylidene fluoride) (PVDF) electrospun nanofibers as the active layer and interlocked conducting...

scholarly journals Cloud based smart wireless and health care monitoring system

2021 ◽  
Vol 1059 (1) ◽  
pp. 012035
Author(s):  
S Nithya Priya ◽  
M Ranjith Kumar ◽  
N Nibin Sabari Anand
Keyword(s):  
Health Care ◽  
Monitoring System ◽  
Health Care Monitoring

Electrospun gelatin nanofiber based self-powered bio-e-skin for health care monitoring

Nano Energy ◽  
2017 ◽  
Vol 36 ◽  
pp. 166-175 ◽  
Author(s):  
Sujoy Kumar Ghosh ◽  
Prakriti Adhikary ◽  
Santanu Jana ◽  
Anirban Biswas ◽  
Vitor Sencadas ◽  
...  
Keyword(s):  
Health Care ◽  
Self Powered ◽  
Health Care Monitoring ◽  
Electrospun Gelatin

Learning Multiple Band-Pass Filters for Sleep Stage Estimation: Towards Care Support for Aged Persons

2010 ◽  
Vol E93-B (4) ◽  
pp. 811-818 ◽  
Author(s):  
Keiki TAKADAMA ◽  
Kazuyuki HIROSE ◽  
Hiroyasu MATSUSHIMA ◽  
Kiyohiko HATTORI ◽  
Nobuo NAKAJIMA
Keyword(s):  
Sleep Stage ◽  
Multiple Band ◽  
Band Pass ◽  
Stage Estimation ◽  
Care Support

scholarly journals Architecture of Ultra Low Power Micro Energy Harvester Using RF Signal for Health Care Monitoring System: A Review

2015 ◽  
Vol 12 (5) ◽  
pp. 335-344 ◽  
Author(s):  
Farah Fatin Zulkifli ◽  
Jahariah Sampe ◽  
Muhammad Shabiul Islam ◽  
Mohd Ambri Mohamed
Keyword(s):  
Health Care ◽  
Low Power ◽  
Monitoring System ◽  
Energy Harvester ◽  
Ultra Low Power ◽  
System A ◽  
Health Care Monitoring ◽  
Rf Signal

Review on the wearable health-care monitoring system with robust motion artifacts reduction techniques

Sensor Review ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aarthy Prabakaran ◽  
Elizabeth Rufus
Keyword(s):  
Health Care ◽  
Monitoring System ◽  
Learning Algorithm ◽  
Motion Artifacts ◽  
Sensor Data ◽  
Monitoring Systems ◽  
Design Modification ◽  
Content Type ◽  
Wearable Monitoring Systems ◽  
Health Care Monitoring

Purpose Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users. Design/methodology/approach MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored. Findings According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems. Originality/value This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

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