Mobile Information Systems

Wearable Technology and Mobile Applications for Healthcare


Publishing date
01 Apr 2019
Status
Published
Submission deadline
16 Nov 2018

1University of Zaragoza, Teruel, Spain

2University of Miami, Miami, USA

3University of Reims Champagne-Ardenne, Reims, France


Wearable Technology and Mobile Applications for Healthcare

Description

Wearable devices, such as smartbands and smartwatches, are available for real-time monitoring of its wearer’s activities and vital signs. Most of these wearable devices connect to smartphones or mobile devices that collect data and process it to extract information such as daily physical activities and health conditions. This information motivates the wearer to develop healthy habits and exercise. Additionally, the data can be shared with healthcare providers and caregivers, who can monitor health conditions of the weatet for providing better advice and services. For example, the condition of people with Alzheimer’s disease, Parkinson’s disease, dementia, and cerebral palsy may be monitored in real time by caregivers and doctors. Moreover, such data can be utilized to determine accurate dosage for medication of patients with hypertension and diabetes.

While millions of people are using wearable devices for tracking fitness activities, very few people are using them for healthcare. This is because of two major problems: (1) extraction of information from sensor-data is a relatively challenging task for consumer, medical professionals, and healthcare personnel and (2) typical wearable devices may not be equipped with sensors for measuring vital health signs. A solution to the second problem would be to embed appropriate sensors for the desired applications into these devices. However, it is more challenging to solve the first problem, because these sensors would require algorithms for mining useful information in the data collected.

This special issue seeks novel state-of-the-art contributions in the area of wearable sensing devices and mobile applications for healthcare, addressing these challenges. This includes contributions about communications between wearable technology and mobile devices, data-mining software for mobile applications, methodological contributions about how to develop mobile applications for applying wearable technology to healthcare, and novel mobile applications for healthcare by means of wearable technology.

Potential topics include but are not limited to the following:

  • Integration of novel wearable devices in healthcare mobile information systems
  • Integration of green or self-powered wearable sensing devices in mobile information systems
  • Methods for mining information from datasets collected from wearable technology
  • Development of user interface for reporting health information
  • Frameworks for developing mobile applications for mobile devices
  • Novel mobile applications for alerting and advising patients with neurological diseases
  • Methodologies for developing wearable technology applications
  • Security measures for communication between wearable technology and mobile applications
  • Privacy of health data communication between wearable technology and mobile devices
  • Interactive multiagent system applications for patients or caregivers based on the information derived from wearable technology
  • Privacy of sharing health data between clients, health professionals, and caregivers
  • Responsibility of health professionals when using big personal tracking data
  • Development of physical sensors for data collection in mobile information systems
  • Deep learning techniques for processing data in mobile information systems

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 6247094
  • - Editorial

Wearable Technology and Mobile Applications for Healthcare

Iván García-Magariño | Dilip Sarkar | Raquel Lacuesta
  • Special Issue
  • - Volume 2019
  • - Article ID 8269695
  • - Research Article

Depression Episodes Detection in Unipolar and Bipolar Patients: A Methodology with Feature Extraction and Feature Selection with Genetic Algorithms Using Activity Motion Signal as Information Source

Carlos E. Galván-Tejada | Laura A. Zanella-Calzada | ... | José M. Celaya-Padilla
  • Special Issue
  • - Volume 2019
  • - Article ID 4731048
  • - Research Article

Empirical Study Based on the Perceptions of Patients and Relatives about the Acceptance of Wearable Devices to Improve Their Health and Prevent Possible Diseases

Francisco D. Guillén-Gámez | María J. Mayorga-Fernández
  • Special Issue
  • - Volume 2019
  • - Article ID 8026042
  • - Research Article

An Integrated SEM-Neural Network Approach for Predicting Determinants of Adoption of Wearable Healthcare Devices

Shahla Asadi | Rusli Abdullah | ... | Shah Nazir
  • Special Issue
  • - Volume 2019
  • - Article ID 1093514
  • - Research Article

Gait Assessment of Younger and Older Adults with Portable Motion-Sensing Methods: A User Study

Runting Zhong | Pei-Luen Patrick Rau | Xinghui Yan
  • Special Issue
  • - Volume 2018
  • - Article ID 4878014
  • - Research Article

An Empirical Evaluation on Vibrotactile Feedback for Wristband System

Feng Wang | Wanna Zhang | Wei Luo
  • Special Issue
  • - Volume 2018
  • - Article ID 3860146
  • - Research Article

A Hybrid Intelligent System Framework for the Prediction of Heart Disease Using Machine Learning Algorithms

Amin Ul Haq | Jian Ping Li | ... | Ruinan Sun
Mobile Information Systems
 Journal metrics
Acceptance rate32%
Submission to final decision103 days
Acceptance to publication41 days
CiteScore1.590
Impact Factor1.635
 Submit