them into grey scale pixel signals forming specific potential images 421 which potential images 421 are graphs presented in black and white this is done by normalizing the irregularly or regularly shaped electric voltage signals into 256 categories and then re arranging them in gray level dot matrix images pre processing the images 43 characteristics of these potential images 421 are highlighted u2014 for example the gray level signals are u201c discretized u201d so that iso potential lines and iso potential points can be identified grouping the images 44 after the characteristics were highlighted the potential images can be grouped according to their characteristics and tallied with those in the muscle template database 15 the user can for example use fuzzy neural network analysis to do the necessary characteristics grouping and tallying generating movement commands 45 after image grouping 44 and tallying with the muscle template database 15 movement commands 152 are given to the control bus 20 to conduct various controls of the care taking machine and obtaining the next step 46 after the above control cycle is completed the next step goes back to the potential image construction step 42 starting the next control cycle the above method of potential image construction and processing 40 not only can be used to process signals detected by the strain gauges 113 but can be used to process analyze and identify massive electrical potential signals which are detected by other detectors and highly complicated such as the signals of multi channel eegs and emgs compared with the prior art the multi functional control interface for care taking machines developed by the present invention makes.