Literature DB >> 28269622

Toward personalized and context-aware prompting for smartphone-based intervention.

Ramin Fallahzadeh, Samaneh Aminikhanghahi, Ashley Nichole Gibson, Diane J Cook.   

Abstract

Intervention strategies can help individuals with cognitive impairment to increase adherence to instructions, independence, and activity engagement and reduce errors on everyday instrumental activities of daily living (IADLs) and caregiver burden. However, to be effective, intervention prompts should be given at a time that does not interrupt other important user activities and is more convenient. In this paper, we propose an intelligent personalized intervention system for smartphones. In our approach, we use context and activity awareness to time prompts when they will most likely be viewed and used. Our result based on real data collected using smartphone motion sensors demonstrate that the proposed approach can detect the time-frame of a user response with an average accuracy of 65% and reduce the inefficiency by 39%, on average, compared to different static time interventions which shows the possibilities and advantages of the proposed system to increase user satisfaction and response rate.

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Year:  2016        PMID: 28269622     DOI: 10.1109/EMBC.2016.7592098

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Real-Time Change Point Detection with application to Smart Home Time Series Data.

Authors:  Samaneh Aminikhanghahi; Tinghui Wang; Diane J Cook
Journal:  IEEE Trans Knowl Data Eng       Date:  2018-06-25       Impact factor: 9.235

2.  A Survey of Challenges and Opportunities in Sensing and Analytics for Risk Factors of Cardiovascular Disorders.

Authors:  Nathan C Hurley; Erica S Spatz; Harlan M Krumholz; Roozbeh Jafari; Bobak J Mortazavi
Journal:  ACM Trans Comput Healthc       Date:  2020-12-30
  2 in total

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