Table 3 Study characteristics. The table gives an overview of the targeted application type, the research type, the frequency of data collection, what control was used, and a summary of the aim of the study. ‘–’ indicates that this does not apply to the respective study

Diagnostic

Basic

Cross-sectional

None

Identification of submovement signatures in EEG during a double-step target displacement task

[54]

Investigation of the effects of cognitive and motor dual tasking on gait performance and brain activities after stroke

[56]

Investigate the participation of midfrontal theta dynamics in a behavioral monitoring system for reactive balance responses

[57]

Healthy

Identification of particular impairments by pre- and post-movement changes in EEG after stroke

[39]

Translational

Cross-sectional

None

Feasibility of recording kinematic and EEG data during visuomotor coordination task

[53]

Feasibility of the combined detection of EEG and gait events during treadmill walking for rehabilitation

[55]

Longitudinal

Healthy

Development of a multivariate analysis method to couple clinical evaluations with multimodal instrumental evaluations

[52]

Therapy

Basic

Cross-sectional

None

Evaluation of changes in cortical involvement during treadmill walking with and without BCI control of an avatar

[48]

Healthy

Investigation of the inter-limb coordination based on brain activity and kinematic features

[42]

Translational

Cross-sectional

None

Comparison of non-adaptive and adaptive approaches in MRCP detection for motor rehabilitation

[47]

Investigation of a transfer learning framework for personalized decoding of TES-assisted 3D reaching task

[49]

Development of a real-time EEG-signal processing and classification pipeline of movement intention for clinical motor rehabilitation

[51]

Healthy

Evaluation of an active robotic upper limb exoskeleton based on gaze tracking and BCI to assist with upper limb movements

[43]

Evaluation of movement task with visuomotor feedback based on related changes in the motor cortex

[50]

–

–

Presentation of an exergame based on EEG and Kinect for lower-limb rehabilitation

[45]

Clinical

Longitudinal

None

Feasibility of decoding gait kinematics during robot-assisted gait training from stroke patients using a powered exoskeleton

[44]

Evaluation of a BCI system to assist with upper-limb functional movement rehabilitation

[40]

Healthy

Evaluation of an assessment system for functional upper limb assessment, based on EEG and kinematic, dynamic data during planar reaching movements

[41]

Non-Healthy

Evaluation of a novel multimodal upper-limb stroke rehabilitation exergame

[46]