combination with a middle finger sensor of a right hand. Thus, it should be understood that the current disclosure is not limited to any particular combination of activated sensors for communicating a desired command to a system as the disclosure is not limited in this fashion. [0040] FIG. 4 is a flow diagram of one embodiment of a system. At box 200, a plurality of sensors may generate a plurality of signals. Next, at box 202, the plurality of signals may be sent to a data acquisition (DAQ) device, which may perform some degree of signal processing. Then, at box 204, the processed signals may be sent to a computing system, in which the user’s command may be determined from the processed signals by a processor. Afterwards, at box 206, the user’s command may be transmitted to a communication system. Finally, at box 208, the communication system may send the user’s command to a processor of the system to perform one or more operation based on the identified commands. [0041] FIG. 5A is a graph of finger position data used to determine a user’s commands in some embodiments of a system. This graph shows a plot of the signals recorded by sensors at a thumb, index finger, and middle finger of a user as the user completes a task. It is clear that the finger forces exerted by a user as the user executes the task may be described in a low-dimensional subspace. For example, a large percentage of the data may be able to explained with only two variables, even though the data exists in a three dimensional space. [0042] FIG. 5B is a graph that relates the principal components of a set of data to a null space of the set of data. The graph may be understood as being related to the data shown in FIG. 5A, although the graph is meant to be representative of a set of data in general. For example, the set of data graphed in FIG. 5B may be representative of signals generated by sensors disposed on the fingertips of a user. As can be seen by the large black bars in FIG. 5B, a larger percentage of the data may be able to be explained as more principal components are considered. For example, about 85% of the data may be explained using just two principal components. The small white bars indicate the marginal contribution from each additional principal component. For example, the third principal component may explain about 10% more of the data. Accordingly, if the operational range of the plurality of signals may be sufficiently understood using, for example, two principal components from the sensed