AUTHOR=Nguyen Hoai Son , Luu Trieu Phat
TITLE=Tremor-Suppression Orthoses for the Upper Limb: Current Developments and Future Challenges
JOURNAL=Frontiers in Human Neuroscience
VOLUME=15
YEAR=2021
URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2021.622535
DOI=10.3389/fnhum.2021.622535
ISSN=1662-5161
ABSTRACT=Introduction: Pathological tremor is the most common motor disorder in adults and characterized by involuntary, rhythmic muscular contraction leading to shaking movements in one or more parts of the body. Functional Electrical Stimulation (FES) and biomechanical loading using wearable orthoses have emerged as effective and non-invasive methods for tremor suppression. A variety of upper-limb orthoses for tremor suppression have been introduced; however, a systematic review of the mechanical design, algorithms for tremor extraction, and the experimental design is still missing.
Methods: To address this gap, we applied a standard systematic review methodology to conduct a literature search in the PubMed and PMC databases. Inclusion criteria and full-text access eligibility were used to filter the studies from the search results. Subsequently, we extracted relevant information, such as suppression mechanism, system weights, degrees of freedom (DOF), algorithms for tremor estimation, experimental settings, and the efficacy.
Results: The results show that the majority of tremor-suppression orthoses are active with 47% prevalence. Active orthoses are also the heaviest with an average weight of 561 ± 467 g, followed by semi-active 486 ± 395 g, and passive orthoses 191 ± 137 g. Most of the orthoses only support one DOF (54.5%). Two-DOF and three-DOF orthoses account for 33 and 18%, respectively. The average efficacy of tremor suppression using wearable orthoses is 83 ± 13%. Active orthoses are the most efficient with an average efficacy of 83 ± 8%, following by the semi-active 77 ± 19%, and passive orthoses 75 ± 12%. Among different experimental setups, bench testing shows the highest efficacy at 95 ± 5%, this value dropped to 86 ± 8% when evaluating with tremor-affected subjects. The majority of the orthoses (92%) measured voluntary and/or tremorous motions using biomechanical sensors (e.g., IMU, force sensor). Only one system was found to utilize EMG for tremor extraction.
Conclusions: Our review showed an improvement in efficacy of using robotic orthoses in tremor suppression. However, significant challenges for the translations of these systems into clinical or home use remain unsolved. Future challenges include improving the wearability of the orthoses (e.g., lightweight, aesthetic, and soft structure), and user control interfaces (i.e., neural machine interface). We also suggest addressing non-technical challenges (e.g., regulatory compliance, insurance reimbursement) to make the technology more accessible.