The ability of a patient to take correct medicine at right time may be reduced when having visual or auditory impairments. Use of inappropriate drug intake can be dangerous and it is important that the patient takes right drug at schedule time. But it is difficult for the elderly persons and the patients with audio and visual impairments to carry out treatment process independently and correctly. This article presents a Convolutional Neural Network (CNN) based medication monitoring system and this system is a sub component of an intelligent pill reminder system.The goal of the intelligent pill reminder system in general, is to assist patient during treatment process at home and role of the monitoring system in particular, is to minimize medication errors. This system is demonstrated on GUI application with a satisfactory accuracy

A CNN Based Monitoring System to Minimize Medication Errors during Treatment Process at Home

Giovanni;Coronato;Antonio;De Pietro;Giuseppe
2020

Abstract

The ability of a patient to take correct medicine at right time may be reduced when having visual or auditory impairments. Use of inappropriate drug intake can be dangerous and it is important that the patient takes right drug at schedule time. But it is difficult for the elderly persons and the patients with audio and visual impairments to carry out treatment process independently and correctly. This article presents a Convolutional Neural Network (CNN) based medication monitoring system and this system is a sub component of an intelligent pill reminder system.The goal of the intelligent pill reminder system in general, is to assist patient during treatment process at home and role of the monitoring system in particular, is to minimize medication errors. This system is demonstrated on GUI application with a satisfactory accuracy
2020
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
9781450376303
CNN
Monitoring System
Medication errors
Object detection
Data-set
Deep Learning
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/374713
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? ND
social impact