Please use this identifier to cite or link to this item: https://doi.org/10.1109/HealthCom.2012.6379413
Title: A predictive modeling engine using neural networks: Diabetes management from sensor and activity data
Authors: Chatterjee, S.
Xie, Q.
Dutta, K. 
Keywords: Diabetes
healthcare modeling
neural networks
persuasive technology
prediction
sensor networks
texting
Issue Date: 2012
Citation: Chatterjee, S.,Xie, Q.,Dutta, K. (2012). A predictive modeling engine using neural networks: Diabetes management from sensor and activity data. 2012 IEEE 14th International Conference on e-Health Networking, Applications and Services, Healthcom 2012 : 230-237. ScholarBank@NUS Repository. https://doi.org/10.1109/HealthCom.2012.6379413
Abstract: Diabetes is a common but serious chronic disease. Nearly 8% of Americans who are aged 65 and older (about 10.9 million) suffer from this deadly disease. Self-management of this disease is possible, yet the older population lack knowledge, have denial and often lack motivation to do so. Recently we have demonstrated sensor-based network architecture within the home to monitor daily activities and biological vital parameters [25]. The data is mined to find patterns and abnormal values. Through daily text messages that are sent to the subjects, we have achieved to influence behavior change using persuasive principles. In this paper, we analyze the daily data and demonstrate that a model to profile the subject's daily behavior is possible using Artificial Neural Networks (ANN). Such a profiling has the advantage of knowing the situations, when the subject's daily activity deviates from its "normal profile", which may be a possible indication of an onset of some health condition or disease. Lastly we develop an ANN based model to predict blood sugar level based on previous day's activity and diet intake. Such a model can be used to help a subject with high blood sugar to adjust daily activity to reach a target blood sugar level and also gives a care-giver advance notice to intervene in adverse situations. © 2012 IEEE.
Source Title: 2012 IEEE 14th International Conference on e-Health Networking, Applications and Services, Healthcom 2012
URI: http://scholarbank.nus.edu.sg/handle/10635/128456
ISBN: 9781457720390
DOI: 10.1109/HealthCom.2012.6379413
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

6
checked on Nov 27, 2021

Page view(s)

60
checked on Nov 18, 2021

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.