Key result
Explainable fuzzy logic for HR classification is deemed useful by ~70% of surveyed clinicians.
Why the study?
People lack a clear method to determine whether their heart rate is normal or indicative of a serious condition, and designing fuzzy logic systems for this purpose is challenging.
The development of an explainable fuzzy logic system may assist individuals in self-monitoring their heart rate levels and health status.
May aid heart rate staging in aging adults; leaves open prospective validation before clinical use.
As people, we have no way of knowing whether our heart rate is considered normal or not. The strength and quality of our pulses will deteriorate as we get older. As a result, this may indicate a heart attack or another illness that requires immediate attention. The main goal of this paper is to define the heart rate stage using fuzzy logic systems (FLSs). In practice, however, designing or developing fuzzy logic systems is extremely difficult. To achieve this aim, we suggested a solution that involves: i) classifying the medical expert's criterion for signs of heart rate; ii) developing an explainable fuzzy logic system for heart rate measurement; and iii) evaluating the proposed system with human experts. In addition, the aim of this research was to provide an explainable fuzzy system that people could use to self-monitor heart rate levels and determine their health status. As a result, it is hoped that this research would provide insight into how to improve the development of fuzzy logic systems, especially in the field of medical applications.
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Dahalan et al. (2021) studied Heart rate events (bradycardia, tachycardia) (n=10). Explainable fuzzy logic system for heart rate classification was evaluated on User understanding and usefulness of the proposed system. An explainable fuzzy logic system developed for heart rate classification was perceived as easy to understand by 50% and useful for self-diagnosis by 70% of surveyed medical practitioners.
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