The nervous system subconsciously estimates the state of the body as a weighted average of the information from various sensory sources, where the weights reflect the perceived reliability of each source. Loss of motor functions can be partially compensated using assistive systems (e.g. prostheses), which may also restore somatosensory feedback through tactile stimulation. Whether such artificial feedback is integrated in the neural state estimation process is not known. In this study, able-bodied subjects performed a grasp force matching task with supplementary non-invasive electrotactile stimulation with a frequency proportional to grasp force magnitude. Before the task, a brief training session taught the subjects to associate the sensation of electrotactile stimulation with the generated grasp force. In some trials, the force-frequency mapping was biased to introduce an unnoticeable mismatch between natural and electrotactile force feedback, thereby provoking the subject to subconsciously estimate the force as a compromise between the two sources of information.The outcome of this compromise revealed the weights assigned to each feedback type. The grasp forces were significantly affected by the biased mappings, as indicated by the average estimated relative weights (electrotactile: 0.69 ± 0.29; natural: 0.31±0.29). Across subjects, this weight was correlated (𝑟 2 = 0.75) with the improvement in force matching precision when adding the unbiased electrotactile feedback to the natural force feedback, as predicted by maximum likelihood estimation. This shows that even after minimal training the nervous system adopts electrotactile stimulation as a highly reliable source of information that can improve the precision in the estimation of the grip force. This result has important implications for the restoration of sensory feedback in upper limb prostheses as it indicates that even non-invasive stimulation can be integrated naturally (i.e., subconsciously and effectively) in the motor control loop.

Just-noticeable difference (JND), indicating the ability to accurately identify small differences in stimulation parameters, can be used to choose more sensitive stimulation methods as well as to calibrate tactile feedback in closed-loop human-machine interfacing. The JND is typically estimated using a forced-choice-discrimination task, in which two stimuli with different intensities are delivered separated by a brief pause. In the applications of tactile feedback, however, the stimulation parameters are typically modulated continuously. It is unclear if the discriminability of stimuli separated in time characterizes the ability to distinguish continuous changes in stimulation intensity. The present study compared the JND when pairs of frequency-modulated electrotactile stimuli were separated in time and presented continuously at two different baseline frequencies (20 and 60 Hz). The results showed that the JND was significantly smaller with time-separation between stimuli, but that the JND obtained with different types of transitions were in most cases linearly associated. In conclusion, the discriminability of time-separated stimuli is systematically better compared to that of the stimuli presented continuously. This can have an impact when calibrating the tactile feedback where the conventional method of the JND assessment might lead to an overly optimistic estimate of detectable changes.

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