Rule extraction for detection and prevention of asthma attacks

Design Of Asthma Detection Devices Through Heart Rate and Oxygen Saturation

Abstract: Respiratory problems can cause asthma, acute asthma attacks are very difficult to predict because they often occur suddenly and asthma can also cause death in sufferers because the breath can suddenly stop. The purpose of this research is to design an asthma detection device through indicators of heart rate and oxygen saturation. The contribution of this study is to categorize the patient's condition by looking at the value of the heartbeat and oxygen saturation so that when asthma occurs the message of a location will be sent. To measure heart rate and oxygen saturation, a Nellcor finger sensor is placed on the patient's index finger. The finger sensor enters the signal conditioning circuit, then sent to the microcontroller to be processed to produce a heart rate value and the percentage of oxygen saturation. The testing of this tool is done by comparing the module with a standard measuring instrument that produces the highest value of oxygen saturation error which is 1.715% and the largest value of heart rate error is 3.548%. The results showed that the device was appropriate to use, because in the Medical Devices Testing and Calibration Guidelines of the Ministry of Health of the Republic of Indonesia in 2001, the maximum limit in oxygen saturation error tolerance was 2%, and heart rate was 5%. The results of this study can be implemented in patients who have been diagnosed with asthma so that it can facilitate the family in monitoring the patient's condition.

An Analytical Approach for Asthma Attack Prevention

Abstract: Asthma patients sometimes immediately need medical attention due to sudden breath loss or asthma attack. An analytical approach is proposed in this paper to prevent a patient from asthma attack. Weather, air quality and pollen data are used to predict the probability of asthma attack for taking preemptive action using logistic regression. The proposed solution implemented on environmental datasets and it achieves 84.2% accuracy.

Mbreath: Asthma monitoring system on the go

Abstract: Prevalence of asthma, especially in air polluted areas, has dramatically increased. As a result, the demand for a system that is able to predict asthma attacks and monitor a patient's condition is becoming increasingly important. This paper presents a prototype system that allow asthma's patients to self-monitor their symptoms condition and manage their conditions accurately, as well as informing the medics in the case of emergency.

Application of fuzzy ontological reasoning in an implementation of medical guidelines

Abstract: In this paper we address two problems. The first pertains to implementation of medical guidelines in an e-health system supporting self-management of chronic diseases. The system allows patients to enter observed symptoms and measured parameters, then makes assessment of disease state and informs about necessary actions. We propose to formalize guidelines as sets of fuzzy rules. Fuzziness is introduced to cope with uncertainty resulting from self-observations bias, low quality of sensors and limited patients skills. The second problem is more general. It concerns the reuse of knowledge gathered in ontologies and an application of Semantic Web technologies to perform fuzzy inference. We show that, despite the fact that commonly used ontology languages and supporting tools are not intended to handle vagueness and uncertainty, they can be successfully integrated to represent and execute a set of fuzzy rules. The proposed method consists in refactoring a domain ontology, then introducing additional relations expressing fuzzy properties, encoding Mamdani fuzzy rules in SWRL language and executing them with use of Pellet OWL reasoner. We describe a fuzzy reasoning engine applying this approach and discuss translation of fuzzy rules to SWRL constructs taking as example a complete set of rules formalizing a medical guideline for asthma control assessment.

The development of a rule-based asthma system

Abstract: Asthma is a very common disease that may become lethal if remained untreated. An asthma patient must always be alert with their body condition, especially their respiratory and the surroundings they are in. This paper proposes a development of a rule-based asthma system. This system provides advice for patients who would like to know the chances of getting an asthma attack are based on the patient's current asthma condition and surrounding environment. To do so, the patients will answer questions to enable the system to understand their current health condition and the environment they are living in. It will then provide suggestions to avoid the attack, or to hasten asthma recovery, which includes environmental factors. Data regarding asthma was gathered through an interview with doctors and online medical resources. A rule-based algorithm was developed based on the data gathered. With this program, it allows patient's self-management to lead a healthy, asthma-free lifestyle.