scholarly journals Outcome data for the remote patient monitoring over three years of over 1000 patients in Northern Ireland with a long-term chronic illness

2012 ◽  
Vol 12 (4) ◽  
Author(s):  
Peter Edward Range
Keyword(s):  
Chronic Illness ◽  
Northern Ireland ◽  
Patient Monitoring ◽  
Outcome Data ◽  
Remote Patient Monitoring ◽  
Remote Patient

scholarly journals TMT Interview: Milton Chen, CEO, VSee

2018 ◽  
Vol 2 (5) ◽  
Author(s):  
Milton Chen
Keyword(s):  
Patient Monitoring ◽  
Early Stage ◽  
Digital Health ◽  
Opinion Leaders ◽  
Remote Patient Monitoring ◽  
Term Care ◽  
Patient Deterioration ◽  
Medicine Today ◽  
Remote Patient

No abstract available. Editor’s note:  On March 16th and 17th, 2017, Telehealth and Medicine Today convened a national conference of opinion leaders to discuss and debate “Technologies and Tactics Transforming Long-term Care.” What follows is an interview with Milton Chen, who is who is CEO of VSee, a digital health solution leveraging machine for learning and remote patient monitoring to enable identification of patient deterioration at an early stage.

scholarly journals REMOTE MONITORING OF PATIENTS WITH LONG-TERM MECHATRONIC CIRCULATORY SUPPORT SYSTEM

2016 ◽  
Vol 18 (2) ◽  
pp. 65-73
Author(s):  
A. V. Adaskin ◽  
K. N. Dozorov ◽  
I. A. Filatov ◽  
G. P. Itkin
Keyword(s):  
Remote Monitoring ◽  
Patient Monitoring ◽  
Circulatory Support ◽  
Remote Patient Monitoring ◽  
Assist Device ◽  
Monitoring Technology ◽  
Patient Interaction ◽  
Mobile Satellite ◽  
Remote Patient

The article describes the technology of remote patient monitoring and the parameters of circulatory assist device AVK-N as well as the advantages of said technology to improve the efficiency of personalized medicine in diagnosis and treatment of patients with AVK-N in the postoperative period. Authors show the capabilities of remote monitoring technology to determine the location of the patient by satellite navigation in the case of emergency call for medical and technical services, and present the structure and modes of the displayed information for mobile devices and Web-server. Doctor-patient interaction based on remote monitoring technology via mobile/ satellite/wired Internet is also shown. 

scholarly journals Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 776
Author(s):  
Xiaohui Tao ◽  
Thanveer Basha Shaik ◽  
Niall Higgins ◽  
Raj Gururajan ◽  
Xujuan Zhou
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Radio Frequency Identification ◽  
Patient Monitoring ◽  
Vital Signs ◽  
Remote Patient Monitoring ◽  
Rfid Technology ◽  
Rpm System ◽  
Frequency Identification ◽  
Remote Patient

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient’s daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM system was built using radio frequency identification (RFID) technology for early detection of suicidal behaviour in a hospital-based mental health facility. A range of machine learning models such as Linear Regression, Decision Tree, Random Forest, and XGBoost were investigated to help determine the optimum fixed positions of RFID reader–antennas in a simulated hospital ward. Empirical experiments showed that Decision Tree had the best performance compared to Random Forest and XGBoost models. An Ensemble Learning model was also developed, took advantage of these machine learning models based on their individual performance. The research set a path to analyse dynamic moving RFID tags and builds an RPM system to help retrieve patient vital signs such as heart rate, pulse rate, respiration rate and subtle motions to make this research state-of-the-art in terms of managing acute suicidal and self-harm behaviour in a mental health ward.

Leadless and Wireless Cardiac Devices: The Next Frontier in Remote Patient Monitoring

2021 ◽  
Vol 46 (5) ◽  
pp. 100800
Author(s):  
Abdulaziz Joury ◽  
Tamunoinemi Bob-Manuel ◽  
Alexandra Sanchez ◽  
Fnu Srinithya ◽  
Amber Sleem ◽  
...  
Keyword(s):  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Cardiac Devices ◽  
Remote Patient

scholarly journals Emerging Role of Remote Patient Monitoring in Pulmonary Care

CHEST Journal ◽  
2021 ◽  
Vol 159 (2) ◽  
pp. 477-478
Author(s):  
Neeraj R. Desai ◽  
Edward J. Diamond
Keyword(s):  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Remote Patient
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