# Early Predictability of Grasping Movements by Neurofunctional Representations: A Feasibility Study
## 4 Discussion
### Limitations  
Although the present study demonstrates the potential of neurofunctional representations as a complementary control signal to achieve fluid prosthetic movements, it is subject to some limitations. First, we obtained data from healthy subjects. While amputees do indeed perform movements such as reaching for an object with the residual upper limb and the prosthetic device, the actual physical grasping movement no longer exists given that the corresponding limb--i.e., the human end effector--is missing. However, it depends on the amputation level and whether an amputation is acquired or congenital. Neurofunctional representations of grasping movements can be assumed to be at least partly comparable for acquired amputations, since primary motor neurons were once functional and are still physically present. In the case of dysplasia, fundamentally different representationscan be expected, because these must be generated by action recognition of hand and arm movements that have never been performed [52]. Furthermore, the relatively small datasets must be mentioned. Data for the pre-training consisted of only three repetitions per subject and ADL, which resulted in approximately the same number of data as in the fine-tuning dataset. This undoubtedly had a considerable effect on the discrimination accuracy of the pre-training. Thus, this dataset should be expanded for further investigations that go beyond a feasibility investigation. Nevertheless, this limitation explains why an advantage of pre-training could not clearly be shown with the present data. As well as electrode placement with a measuring cap and electrode gel, another limitation is the cumbersome consideration of all 31 EEG channels, which would be practically impossible to transfer to a prosthetic application. Nevertheless, the present study demonstrates the initial feasibility of such a neurofunctional approach, which is certainly worth pursuing further. Since [PERSON] et al. [29] have already shown that the number and setup of electrodes have a significant effect on the performance, subsequent studies should investigate the characteristics of these representations in more detail to allow for a considerable channel reduction. Indeed, [PERSON] et al. [46] have presented very promising results in their comparative study, in which they used a dry EEG system consisting of eleven electrodes that covered only the superior orbital part of the brain. Although this system had lower accuracy for the discrimination of different reach and grasping actions from the alpha and beta frequency bands in general, the authors found a performance decrease of around 6% compared to a conventional multichannel gel-based EEG system, such as the one used in our study. A further limitation is that the distribution of ADLs to categorizations varied. A more equal distribution of ADL numbers within categories should be obtained in future work to achieve even better discrimination accuracies. Under such conditions, it would be worth investigating whether the C5 categorization identified in the present study as advantageous represents an approach that can be applied to prosthetics control. In addition, the algorithms and scenarios used in this study processed simultaneous information from multiple spectral features across multiple brain areas as a type of black box. Thus, further information about which motion parameters are encoded by the signals and how they are accurately represented cortically in time (i.e., as a function of planned or performed grasping action) and space should be a focus of future investigations.