This study aims to suggest the methodology to improve to estimate back-calculated fish growth parameters using weighted average. It is to contribute to correct errors in the calculation of back-calculated growth equation with unequal numbers of sample by age. If the numbers of sample were evenly collected by age, each back-calculated length at age was equal between arithmetic and weighted averages. However, most samples cannot be evenly collected by age in reality because of different catchability by fishing gear and limitation of environment condition. Therefore, the estimation of back-calculated length by weighted average method is essential to calculate growth parameters. There were some published growth equations from back-calculated length using a simple arithmetic average with different numbers of samples by age when searching for back-calculated growth equations from 91 relevant papers. In this study, the process of deriving growth equation was investigated and two different average calculations were applied to a fish growth equation, for example of Acheilognathus signifer. Growth parameters, such as L∞, k and t0, were estimated from two different back-calculated averages and the growth equations were compared with growth performance index. Based on the correction of back-calculated length using weighted average by age, the changes by female and male were -14.19% and -5.23% for L∞, and 59.28% and 18.91% for k, respectively. The corrected growth performance index by weighted average improved at 7.05% and 2.46% by female and male, respectively, compared to the arithmetic averages.

The electrical muscle stimulator (EMS) based human machine interface (HMI) free to mechanical constraint and muscle fatigue problems are proposed for force feedback in a virtual reality. The device was designed to provide force feedback up to 4.8 N and 2.6 N each to the thumb and forefingers. The main objective of the HMI is to make unnecessary mechanical structures to attach on the hand or fingers. It employs custom EMSs and an interface arranged in the forearm. In this work, major muscle groups such as extensor pollicis brevis (EPB), extensor indicis proprius (EIP), flexor pollicis longus (FPL) and flexor digitorum profundus (FDP) are selected for efficient force feedback and controlled individually. For this, a human muscular-skeletal analysis was performed and verified. The validity of the proposed multi-channel EMS based HMI was evaluated thorough various experiments with ten human subjects, interacting with a virtual environment.