Fingertip force control requires fine coordination of multiple hand muscles within and across the digits. While the modulation of neural drive to hand muscles as a function of force has been extensively studied, much less is known about the effects of fatigue on the coordination of simultaneously active hand muscles. We asked eight subjects to perform a fatiguing contraction by gripping a manipulandum with thumb, index, and middle fingers while matching an isometric target force (40% maximal voluntary force) for as long as possible. The coordination of 12 hand muscles was quantified as electromyographic (EMG) muscle activation pattern (MAP) vector and EMG-EMG coherence. We hypothesized that muscle fatigue would cause uniform changes in EMG amplitude across all muscles and an increase in EMG-EMG coherence in the higher frequency bands but with an invariant heterogeneous distribution across muscles. Muscle fatigue caused a 12.5% drop in the maximum voluntary contraction force (P < 0.05) at task failure and an increase in the SD of force (P < 0.01). Although EMG amplitude of all muscles increased during the fatiguing contraction (P < 0.001), the MAP vector orientation did not change, indicating that a similar muscle coordination pattern was used throughout the fatiguing contraction. Last, EMG-EMG coherence (0-35 Hz) was significantly greater at the end than at the beginning of the fatiguing contraction (P < 0.01) but was heterogeneously distributed across hand muscles. These findings suggest that similar mechanisms are involved for modulating and sustaining digit forces in nonfatiguing and fatiguing contractions, respectively.
Fingertip forces result from activation of muscles that cross the wrist and muscles whose origins and insertions reside within the hand (extrinsic and intrinsic hand muscles, respectively). Thus, tasks that involve changes in wrist angle affect the moment arm and length, hence the force-producing capabilities, of extrinsic muscles only. If a grasping task requires the exertion of constant fingertip forces, the Central Nervous System (CNS) may respond to changes in wrist angle by modulating the neural drive to extrinsic or intrinsic muscles only or by co-activating both sets of muscles. To distinguish between these scenarios, we recorded electromyographic (EMG) activity of intrinsic and extrinsic muscles of the thumb and index finger as a function of wrist angle during a two-digit object hold task. We hypothesized that changes in wrist angle would elicit EMG amplitude modulation of the extrinsic and intrinsic hand muscles. In one experimental condition we asked subjects to exert the same digit forces at each wrist angle, whereas in a second condition subjects could choose digit forces for holding the object. EMG activity was significantly modulated in both extrinsic and intrinsic muscles as a function of wrist angle (both p < 0.05) but only for the constant force condition. Furthermore, EMG modulation resulted from uniform scaling of EMG amplitude across all muscles. We conclude that the CNS controlled both extrinsic and intrinsic muscles as a muscle synergy. These findings are discussed within the theoretical frameworks of synergies and common neural input across motor nuclei of hand muscles.
This study was designed to determine the extent to which sensations elicited by discrete electrotactile stimulation can be spatially localized, with a qualitative comparison to mechanical stimulation, in a 2 x 2 electrode array on the fingertip. Electrotactile stimulation was delivered in two modes: (1) same current to all locations (constant) or (2) current adjusted to perceptual threshold of each location (varied). For each stimulus location, subjects were asked to identify the location of the stimulus. Mechanical stimulation of the same locations on the fingerpad was delivered through von Frey hairs (0.07, 0.2 and 0.4 g). The percentage of accurate responses was computed for all stimulation modes. We found that the accuracy of discrimination of stimulus location in both the constant (46%) and varied (40%) electrotactile stimulation modes was significantly higher than chance level (25%; p < 0.01). Furthermore, subjects were significantly more accurate in discriminating electrotactile stimuli in the constant than in the varied mode (p < 0.05). We also found that the accuracy of spatial discrimination was dependent on stimulation site for mechanical, but not electrotactile stimulation. Finally, we found a significant difference in accuracy over the duration of the experiment only for mechanical modes, which may indicate that electrotactile stimuli are less biased over time. These results suggest that, although low in accuracy, human subjects are able to extract spatial information from electrotactile stimuli. Further research is needed to optimize the amount of the information that can be delivered through electrotactile stimulation.
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