“…The search strategy was performed regarding the following four categories: body segment (hand, elbow, wrist, shoulder, arm, fingers, upper extremity, upper limb), orthosis (orthosis, orthoses, exoskeleton, orthotic device, orthosis device, orthoses device, robotic device, robotic, wearable robot, exosuit, wearable orthoses, wearable orthosis, wearable assistive robots, wearable exosuit), physical rehabilitation (physical rehabilitation, motor rehabilitation, physical medicine, telerehabilitation), and ML algorithms (ML, supervised ML, unsupervised ML, semi-supervised ML, reinforcement learning, artificial intelligence, adaptive algorithms, neural network (NN), artificial NN, k-nearest neighbors (KNN), linear regression, logistic regression, support vector machines (SVM), decision trees, random forests (RF), extreme gradient boosting, k-means, hierarchical cluster analysis, expectation maximization, principal component analysis, kernel principal component analysis, locally-linear embedding, T-distributed stochastic neighbor embedding, Q-learning, state-action-reward-stateaction, deep Q network, deep deterministic policy gradient, computational intelligence, machine intelligence, computer reasoning, computer vision systems, knowledge acquisition, knowledge representation, logic fuzzy, fuzzy control, deep learning) for both databases and patents, according to our previous study [21]. All database searches were done without restriction to the language and year of publication.…”