A Case‐based Decision Support System for Individual Stress Diagnosis Using Fuzzy Similarity Matching

Abstract

Stress diagnosis based on finger temperature (FT) signals is receiving increasing interest in the psychophysiological domain. However, in practice, it is difficult and tedious for a clinician and particularly less experienced clinicians to understand, interpret, and analyze complex, lengthy sequential measurements to make a diagnosis and treatment plan. The paper presents a case-based decision support system to assist clinicians in performing such tasks. Case-based reasoning (CBR) is applied as the main methodology to facilitate experience reuse and decision explanation by retrieving previous similar temperature profiles. Further fuzzy techniques are also employed and incorporated into the CBR system to handle vagueness, uncertainty inherently existing in clinicians reasoning as well as imprecision of feature values. Thirty-nine time series from 24 patients have been used to evaluate the approach (matching algorithms) and an expert has ranked and estimated similarity. On average goodness-of-fit for the fuzzy matching algorithm is 90% in ranking and 81% in similarity estimation that shows a level of performance close to an experienced expert. Therefore, we have suggested that a fuzzy matching algorithm in combination with CBR is a valuable approach in domains, where the fuzzy matching model similarity and case preference is consistent with the views of domain expert. This combination is also valuable, where domain experts are aware that the crisp values they use have a possibility distribution that can be estimated by the expert and is used when experienced experts reason about similarity. This is the case in the psycho-physiological domain and experienced experts can estimate this distribution of feature values and use them in their reasoning and explanation process.

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis

“…Moreover, Lee and Wang's study used the Pima Indians Dataset, but we use real cases from Mansura University Hospitals in Egypt. [96] Diagnosis of liver disorder 85 Begum et al [97] Diagnosis of stress 80 Petrovic et al [88] Radiotherapy planning 84.72 Non-medical Li et al [98] Financial application 92.36 Arias-Aranda et al [99] Knowing the relationship between flexibility and operations strategy…”

Clustering to Enhance Case-Based Reasoning

“…These methods and particularly the decision trees and the neural networks have been used in many studies in medicine [17,20]. We give a non-exhaustive list of some research works which uses data mining methods in a medical field.…”

“…Begum et al presented a decision support system to help physicians to diagnose the state of stress [17]. De Paz et al presented a decision support system for the diagnosis of different types of cancer [18].…”

ECG sensor signal analysis to represent cases in a case-based stress diagnosis system

“…For example, a procedure using CBR for diagnosing stress-related disorder was put forwarded by Nilsson et al [14] where stress-related disorders were diagnosed by classifYing the heart rate patterns. A CBR system was outlined in [15], [17], [7] where cases are formulated using finger temperature sensor signal for diagnosing stress in the psycho-physiological domain, however it is not sufficient to depend only on finger temperature for classifYing individual sensitivity to stress. Therefore, in this proposed system we have introduced another physiological parameter i.e.…”