KBot

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kBot
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Knowledge enabled personalized chat-bot system for self-management of asthma in padiatric population (age 8-15).

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Dipesh Kadariya

Motivation

Asthma is a lung inflammatory disease that has prevailed more than 26 million people in the United States, out of which 6.1 million are children [ref]. It is the most chronic condition among the pediatric population[ref] accounting for 13.8 million missed school days each year [ref]. Though incurable, asthma can be controlled and managed by strict adherence to a medication care plan and by avoiding the triggers [ref]. However, due to a lack of consistent adherence to the asthma care plan, and inadequate information about the patient’s environment, asthma management can be challenging [ref]. These issues are further compounded by its multi-factorial nature, where every patient is sensitive to different triggers, and react differently even when exposed to the same trigger [ref]. This demands personalized care beyond the regular hospital setup to which the clinical professionals are limited. The advent of digital health monitoring technologies such as smart wearables and increasing adoption of mobile devices and low-cost sensors translate to an unprecedented amount of data being generated and collected on a continuous basis. It is now possible to monitor long-term medication adherence, exposure to environmental triggers, and asthma control level in real-time.

Challenges

  1. Continuous monitoring of the patient’s asthmatic condition requires their active involvement in the process. However, due to the static user interface of current monitoring systems, poor patients compliance badly affects the quality and quantity of data collection.
  2. In asthma care, the effectiveness of treatment is affected not only by patient compliance but also by the inhalers usage techniques. If asthma inhalers are not used in a proper way, it has no effect on patients asthmatic condition which may lead to worsening of asthma. For the effectiveness of asthma treatment, patients need to be educated on proper inhaler techniques and encouraged towards medical compliance.
  3. Asthma is a multi-factorial disease; each patient reacts to both triggers and treatment differently. A general treatment approach such as a generic asthma care plan proves to be ineffective in such a scenario. A more personalized approach to monitor patients and their environmental factors are required.

Evaluation

Architecture

Contextualization

Personalization

Video

Team Members

Dipesh Kadariya, Revathy Venkataramanan, and Kirill Kultinov

Related Publications

  1. Dipesh Kadariya, Revathy Venkataramanan, Hong Yung Yip, Maninder Kalra, Thirunarayan Krishnaprasad, Amit Sheth. "kBot: Knowledge-enabled Personalized Chatbot for Asthma Self-Management". In Proceedings of the IEEE SMARTSYS Workshop on Smart Service Systems (SMARTCOMP 2019). IEEE, 2019.

Funding

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  • This research has been partially supported by:
  • Grant Number: 1 R01 HD087132-01
  • Principal Investigators: Amit P. Sheth (Kno.e.sis, Wright State University)
  • Project Title: KHealth: Semantic Multisensory Mobile Approach to Personalized Asthma Care