Mathematical models of cardiac cells have been established to broaden understanding of cardiac function. In the process of developing electrophysiological models for cardiac myocytes, precise parameter tuning is a crucial step. The membrane resistance (Rm) is an essential feature obtained from cardiac myocytes. This feature reflects intercellular coupling and affects important phenomena, such as conduction velocity, and early after-depolarizations, but it is often overlooked during the phase of parameter fitting. Thus, the traditional parameter fitting that only includes action potential (AP) waveform may yield incorrect values for Rm. In this paper, a novel multi-objective parameter fitting formulation is proposed and tested that includes different regions of the Rm profile as additional objective functions for optimization. As Rm depends on the transmembrane voltage (Vm) and exhibits singularities for some specific values of Vm, analyses are conducted to carefully select the regions of interest for the proper characterization of Rm. Non-dominated sorting genetic algorithm II is utilized to solve the proposed multi-objective optimization problem. To verify the efficacy of the proposed problem formulation, case studies and comparisons are carried out using multiple models of human cardiac ventricular cells. Results demonstrate Rm is correctly reproduced by the tuned cell models after considering the curve of Rm obtained from the late phase of repolarization and Rm value calculated in the rest phase as additional objectives. However, relative deterioration of the AP fit is observed, demonstrating trade-off among the objectives. This framework can be useful for a wide range of applications, including the parameters fitting phase of the cardiac cell model development and investigation of normal and pathological scenarios in which reproducing both cellular and intercellular properties are of great importance.

Background: Neck and back pain are the most common reported musculoskeletal disorders. Applying surface electromyography to determine muscular activity has been used for a long time for clinical diagnosis. OBJECTIVE: The aim of this study was to assess the effect of two sleeping postures (recommended and preferred postures) on neck muscles activities and fatigue by measuring cervical muscles activities using electromyography. In the recommended posture (Model 1), the cervical and lumbar spine are horizontally aligned, while in the preferred posture (Model 2), the cervical spine is not aligned with lumbar spine. Methods: A total of nine healthy male subjects were asked to side rest with a pillow with adjustable height. The electromyography examinations were performed for upper trapezius (UT) and sternocleidomastoid (SCM) muscles of participants. After acquiring the anthropometric data, participants laid on mattress with medium hardness at the two postures for 30 minutes. Results: Comparison between the two models showed a significant difference ( ) in the level of electrical activity of neck muscles. In addition, a remarkable difference ( ) was observed in terms of neck muscle fatigue between the two tested models. Conclusions: The results indicate that the recommended posture developed and tested in this study would reduce the level of fatigue and activity of neck muscles during resting.

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