Classify and Diagnose Individual Stress Using Calibration and Fuzzy Case-Based Reasoning

Begum, ShahinaMälardalens högskola,Institutionen för datavetenskap och elektronik (author)

Increased exposure to stress may cause health problems. An experi-enced clinician is able to diagnose a person's stress level based on sensor read-ings. Large individual variations and absence of general rules make it difficult to diagnose stress and the risk of stress-related health problems. A decision sup-port system providing clinicians with a second opinion would be valuable. We propose a novel solution combining case-based reasoning and fuzzy logic along with a calibration phase to diagnose individual stress. During calibration a num-ber of individual parameters are established. The system also considers the feedback from the patient on how well the test was performed. The system uses fuzzy logic to incorporating the imprecise characteristics of the domain. The cases are also used for the individual treatment process and transfer experience between clinicians. The validation of the approach is based on close collabora-tion with experts and measurements from 24 persons used as reference.

Ahmed, Mobyen UddinMälardalens högskola,Institutionen för datavetenskap och elektronik(Swepub:mdh)mad02 (author)
Funk, PeterMälardalens högskola,Institutionen för datavetenskap och elektronik(Swepub:mdh)pfk01 (author)
Xiong, NingMälardalens högskola,Institutionen för datavetenskap och elektronik(Swepub:mdh)nxg01 (author)
von Schéele, BoMälardalens högskola,Institutionen för datavetenskap och elektronik (author)
Mälardalens högskolaInstitutionen för datavetenskap och elektronik (creator_code:org_t)

In:Case-Based Reasoning Research and DevelopmentBerlin, Heidelberg : Springer, s. 478-4919783540741381

By the author/editor: Begum, Shahina; Ahmed, Mobyen Ud ...; Funk, Peter; Xiong, Ning; von Schéele, Bo

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