Literature DB >> 20703552

Monitoring of medication intake using a camera system.

Guillaume-Alexandre Bilodeau1, Soufiane Ammouri.   

Abstract

This paper presents a computer vision system for monitoring medication intake in the context of home care services. We use a method based on color and shape to detect the body parts and the medication bottles. Color is used for skin detection, and the shape is used to distinguish the face from the hands and to differentiate bottles of medicine. To track these objects, we use a method based on color histograms, Hu moments, and edges. For the recognition of medication intake, we use a Petri network and event recognition. Our method has an accuracy of more than 75% and allows the detection of the medication intake in various scenarios where the user is cooperative.

Mesh:

Year:  2009        PMID: 20703552     DOI: 10.1007/s10916-009-9374-6

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  3 in total

1.  Approximate Bayesian multibody tracking.

Authors:  Oswald Lanz
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2006-09       Impact factor: 6.226

2.  Video surveillance of medication intake.

Authors:  Myriam Valin; Jean Meunier; Alain St-Arnaud; Jacqueline Rousseau
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2006

3.  A computational approach to edge detection.

Authors:  J Canny
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  1986-06       Impact factor: 6.226

  3 in total
  2 in total

Review 1.  Medication management needs information and communications technology-based approaches, including telehealth and artificial intelligence.

Authors:  Alphons Eggerth; Dieter Hayn; Günter Schreier
Journal:  Br J Clin Pharmacol       Date:  2019-07-25       Impact factor: 4.335

Review 2.  Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review.

Authors:  Madilyn Mason; Youmin Cho; Jessica Rayo; Yang Gong; Marcelline Harris; Yun Jiang
Journal:  JMIR Mhealth Uhealth       Date:  2022-03-10       Impact factor: 4.947

  2 in total

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