A Belief Rule Based Expert System to Assess Meditation

Meditation is a practice, by regularly applying one can develop calm and quite mind. It is essential not only for developing pure mind but also for sound health. Therefore, the assessment of meditation is very important in every day of our life. It can be measured by using various human sensing factors such as sleep pattern, Galvanic Skin Response (GSR), Heart rate Variability (HRV), pulse difference etc. However, assessing meditation level is complex due to the presence of various types of uncertainties such as vagueness, ignorance, imprecision, incompleteness associated with these human sensing factors. This paper presents the design, development and application of an expert system to assess meditation under uncertainty. The belief rule-based inference methodology using evidential reasoning approach (RIMER), which can handle various types of uncertainties, employed to develop this expert system. The knowledge-base has been constructed by taking account of meditation practitioner's real data and expert's opinion. The practitioner's case studies have been used to validate the expert system. It has been observed that the system generated results are more reliable than from the expert assessment.