مجله دانشکده پزشکی اصفهان
پیاپی 498 (هفته دوم آذر ماه 1397)

The present study aimed to study the quality of relationship between personality types and temperaments (Mizaj) of Iranian Traditional Medicine, incorporation of these to fields to promote the level of personal health and prevent the diseases.

This was an analytical cross-sectional study on 293 medical students in Isfahan University of Medical Sciences, Isfahan, Iran, during the years 2015-2017. The participants were selected using simple random sampling method, after having gained their satisfaction. The data were collected using Mizaj Detecting Questionnaire and Temperament and Character Inventory-125 (TCI-125), and were analyzed using SPSS software. Findings: The mean age of the participants was 22.74 ± 0.81 years, while 54.3% were women and 45.7% were men. In study of temperaments, novelty seeking, harm avoidance, reward dependence, and persistence had the most prevalence among the persons with hot and dry Mizaj (36.60%), and the least prevalence among the persons with moderate and wet Mizaj (19.00%) (P < 0.001). Moreover, in study of personality, self-directedness, cooperativeness, and self-transcendence, had the most prevalence among the persons with hot as well as moderate dry and wet Mizaj (41.00%), and the least prevalence among the persons with hot and dry Mizaj (34.57%).

A person with a special Mizaj have a range of moral and behavioral characteristics that relates to a certain predominant quality. So, with an appropriate plan, this quality will lead to a particular behavior kept modest, and the person receives qualitative physical and mental health from the point of view of quality moderation.

Tactile sensing plays an important role in our understanding of the environment. Mechanical arms, robots, and nerve prostheses perform better, if they have the sense of touch. Microneurography studies in humans have shown that primary afferent neurons (e.g. fingertip mechanoreceptors play an important role in encoding and separability with various types of stimuli using spike train patterns.

We developed an experimental set up to simulate the responses of Merkel mechanoreceptors to force stimulation, with considering account receptor spiking behavior. Indeed, we used sensor data and spiking properties of Merkel mechanoreceptors to discriminate force. The analog tactile signals generated from sensor were fed as input to the Izhikevich neurons in order to obtain spike trains. The features of Spike trains were extracted with rate coding and timing coding. The desired features were assigned to the k-nearest neighbors (kNN), and support vector machine (SVM) to classify the types of forces. Findings: The highest classification accuracy achieved 100% with rate coding, 81.18% with inter-spike interval coefficient of variation (ISI CV), and 82% with victor-purpura distance (VPd). From the spike trains evoked during contact, we computed the information that rate and timing codes carried about applied force.

Rate coding carried more force information than spike timing for Merkel mechanoreceptors. Moreover, as the force increased, firing rate also increased