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Objective: This study aimed to conduct a bibliometric analysis of the literature on exoskeleton robot assisted walking rehabilitation for stroke patients in the Web of Science Core Collection over the past decade. Method: Retrieved literature on exoskeleton robot assisted gait training for stroke hemiplegic patients from the Web of Science Core Collection from 1 January 2014 to 31 January 2024. The search method was topic search, and the types of documents were "article, meeting abstract, review article, early access." CiteSpace was used to analyze the search results from countries, institutions, keywords, cited references and cited authors. Result: A total of 1,349 articles were retrieved, and 1,034 were ultimately included for visualization analysis. The annual publication volume showed an upward trend, with countries, institutions, and authors from Europe and America in a leading position. The core literature was also published by authors from European and American countries. The keywords were divided into 8 clusters: # 0 soft robotic exit, # 1 robot assisted gain training, # 2 multiple scales, # 3 magnetic rheological brake, # 4 test retest reliability, # 5 electromechanical assisted training, # 6 cerebra salary, and # 7 slow gain. The early research direction focused on the development of exoskeleton robots, verifying their reliability and feasibility. Later, the focus was on the combination of exoskeleton robot with machine learning and other technologies, rehabilitation costs, and patient quality of life. Conclusion: This study provides a visual display of the research status, development trends, and research hotspots, which helps researchers in this field to grasp the research hotspots and choose future research directions.
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Background: We described the prevalence of anxiety and depression related to COVID-19 pandemic among different types of population and examined their potential risk factors. Methods: A cross-sectional survey was conducted to collect demographic characteristics, exposure histories, and many other concerns about COVID-19. The Zung's self-rating anxiety scale (SAS) and self-rating depression scale (SDS), followed by a four-step multiple logistic regression analysis was performed to identify factors associated with mental health outcomes. Results: Out of 3,303 participants, the quarantined people (40.9%), community workstation staffs-policemen-volunteers (CPV) (36.4%) and general public (30.7%) reported higher percentages of depression than the general medical staff (18.4%). Moreover, the quarantined people (19.1%) also showed higher prevalence of anxiety than the general public (9.1%) and the general medical staff (7.8%). The quarantined people had the highest risk of anxiety and depression, whereas the self-rated health was negatively associated with the risks of anxiety and depression. Younger age group (18 to 30 years) showed higher risks of anxiety (OR = 6.22, 95% CI = 2.89-13.38, p < 0.001) and depression (OR = 3.69, 95% CI = 2.40-5.69, p < 0.001). People who had exposure history or contact from Hubei province after December 1, 2019 (OR = 1.57, 95% CI = 1.07-2.30, p < 0.001), had family or friends engaged in front-line health care work (OR = 1.47, 95% CI = 1.02-2.14, p < 0.001), had confirmed case nearby (OR = 2.44, 95% CI = 1.43-4.18, p < 0.001) were all more likely to suffer from anxiety. Moreover, the negligence (OR = 1.85, 95% CI = 1.37-2.51, p < 0.001) or overindulgence (OR = 1.45, 95% CI = 1.03-2.04, p < 0.001) toward the epidemic information was associated with a higher risk of depression and anxiety. Conclusions: Our findings show that the CPV and quarantined people were most at-risk population. We have identified that the young people, people with exposure histories and negligence or overindulgence toward epidemic information are in grave need of attention.
