Stroke is one of the main causes of long-term disability worldwide, placing a large burden on individuals and society. Rehabilitation after stroke consists of an iterative process involving assessments and specialized training, aspects often constrained by limited resources of healthcare centers. Wearable technology has the potential to objectively assess and monitor patients inside and outside clinical environments, enabling a more detailed evaluation of the impairment and allowing the individualization of rehabilitation therapies. The present review aims to provide an overview of wearable sensors used in stroke rehabilitation research, with a particular focus on the upper extremity. We summarize results obtained by current research using a variety of wearable sensors and use them to critically discuss challenges and opportunities in the ongoing effort towards reliable and accessible tools for stroke rehabilitation. Finally, suggestions concerning data acquisition and processing to guide future studies performed by clinicians and engineers alike are provided.

The development of novel strategies to augment motor training success is of great interest for healthy persons and neurological patients. A promising approach is the combination of training with transcranial electric stimulation. However, limited reproducibility and varying effect sizes make further protocol optimization necessary. We tested the effects of a novel cerebellar transcranial alternating current stimulation protocol (tACS) on motor skill learning. Furthermore, we studied underlying mechanisms by means of transcranial magnetic stimulation and analysis of fMRI-based resting-state connectivity. N = 15 young, healthy participants were recruited. 50 Hz tACS was applied to the left cerebellum in a double-blind, sham-controlled, cross-over design concurrently to the acquisition of a novel motor skill. Potential underlying mechanisms were assessed by studying short intracortical inhibition at rest (SICIrest) and in the premovement phase (SICImove), intracortical facilitation at rest (ICFrest), and seed-based resting-state fMRI-based functional connectivity (FC) in a hypothesis-driven motor learning network. Active stimulation did not enhance skill acquisition or retention. Minor effects on striato-parietal FC were present. Linear mixed effects modelling identified SICImove modulation and baseline task performance as the most influential determining factors for predicting training success. Accounting for the identified factors may allow to stratify participants for future training-based interventions.

Practicing a previously unknown motor sequence often leads to the consolidation of motor chunks, which enable its accurate execution at increasing speeds. Recent imaging studies suggest the function of these structures to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We found that optimal motor skill acquisition prioritizes the storage of the spatial features of the sequence in memory over its rapid execution early in training, as proposed by Hikosaka in 1999. This process, seemingly diminished in older adults, was partially restored by anodal transcranial direct current stimulation over the motor cortex, as shown by a sharp improvement in accuracy and an earlier yet gradual emergence of motor chunks. These results suggest that the emergence of motor chunks is preceded by the storage of the sequence in memory but is not its direct consequence; rather, these structures depend on, and result from, motor practice.