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Asthma is a chronic respiratory ailment that requires careful management due to its varying symptoms and influencing factors. It is characterized by airway inflammation, bronchial hyperresponsiveness, and reversible airflow obstruction, leading to symptoms like wheezing, shortness of breath, chest tightness, and coughing. The symptom frequency and intensity may vary considerably over time. It is also linked to immune system responses to allergens and irritants, highlighting the complex...
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Asthma is a chronic pulmonary condition involving inflammation of the airways, hyper-reactivity, and reversible obstruction of the airways. This condition can significantly impact a person's quality of life, making breathing difficult and leading to distressing symptoms.
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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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ADAPT: Approach to Develop context-Aware solutions for Personalised asthma managemenT.

Mario Quinde1, Juan Carlos Augusto2, Nawaz Khan2

  • 1Research Group on Development of Intelligent Environments, Department of Computer Science, Middlesex University London, UK; Departamento de Ingeniería Industrial y de Sistemas, Universidad de Piura, Peru.

Journal of Biomedical Informatics
|October 13, 2020
PubMed
Summary

Personalized asthma management is crucial due to varied triggers and symptoms. The Approach to Develop context-Aware solutions for Personalised asthma managemenT (ADAPT) offers tailored support, enhancing patient care.

Keywords:
Asthma managementCase-based reasoningContext-aware reasoningMobile healthPersonalisationVirtual assistant

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Area of Science:

  • Digital Health
  • Personalized Medicine
  • Respiratory Medicine

Background:

  • Asthma presents diverse triggers and symptoms, necessitating individualized management strategies.
  • Current approaches often lack the personalization required to address this heterogeneity effectively.
  • Context-aware reasoning offers a promising avenue for tailoring asthma management.

Purpose of the Study:

  • To introduce the Approach to Develop context-Aware solutions for Personalised asthma managemenT (ADAPT).
  • To facilitate the creation of customized asthma management solutions addressing individual patient needs.
  • To leverage context-aware reasoning for personalized asthma care.

Main Methods:

  • ADAPT was developed through continuous collaboration with individuals with asthma and Asthma UK.
  • The approach incorporates context dimensions for configurable preventive and reactive features.
  • Case-based reasoning and virtual assistants are integrated to support trigger identification and management.

Main Results:

  • ADAPT enables the development of personalized asthma management tools.
  • Features can be configured based on individual patient characteristics and needs.
  • The approach supports users in identifying unknown asthma triggers.

Conclusions:

  • ADAPT provides a framework for creating personalized, context-aware asthma management solutions.
  • The approach addresses the heterogeneity of asthma by offering tailored information and services.
  • Validation by patients, carers, and experts confirms the utility of ADAPT-based applications.