Background: Caregiver burden significantly affects both patients and caregivers but is often overlooked in clinical practice. Physical and emotional strain on caregivers can compromise the quality of care. Care robots are emerging as solutions to alleviate these burdens by assisting with routine tasks, thereby reducing caregivers' physical strain and stress. Therefore, a prospective, non-randomized, interventional clinical trial was designed to identify changes in caregivers' physical activities due to care robot use and explore the associated benefits.
Methods: Twenty-two caregivers (1 male and 21 female; mean age, 62.05 years) were participated. We analyzed the impact of care robots on reducing physical burden and assessed caregivers' satisfaction with these robots by examining care activity history, pain levels, muscle activities, and data for each physical care activity (e.g., transfer, reposition, feeding, and toileting), categorizing them based on whether a care robot was used. Care robots that assist in transfer, repositioning, feeding, and toileting activities were used in a clinical trial. Muscle activity was measured during maximum voluntary isometric contraction using electromyography sensors placed on the upper trapezius, biceps brachii, and erector spinae muscles.
Results: During care robot use, we observed a statistically significant decrease in the distance and number of steps required for assisting with repositioning. However, the caregiving activity time increased when the robots assisted with transfer, feeding, and toileting (P < .001). Pain was significantly reduced during transfer and toileting activities using the care robot (P < .001) as well as during feeding activity (P = .040). Maximum voluntary isometric contraction showed a significant reduction in the upper trapezius, biceps brachii, and erector spinae muscles during the 4 care activities when using the robot, and these findings were consistent across the 3 sessions (P < .001). In the survey, caregivers indicated that "transfer-assisting" care robots were the most needed (15 respondents, 68.2%).
Conclusion: In this study, we demonstrated that employing care robots can aid in mitigating muscle overuse among caregivers, potentially alleviating pain due to musculoskeletal conditions.
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http://dx.doi.org/10.1097/MD.0000000000040877 | DOI Listing |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651516 | PMC |
Imaging Sci Dent
December 2024
Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara, Medan, Indonesia.
Purpose: This review aimed to explore the scientific literature concerning the methodologies and applications of artificial intelligence (AI) in the field of endodontics. The findings may equip dentists with the necessary technical knowledge to understand the opportunities presented by AI.
Materials And Methods: Articles published between 1992 and 2023 were retrieved through an electronic search of Medline via the PubMed, Scopus, and Google Scholar databases.
Ann Agric Environ Med
December 2024
Department of Rehabilitation, Medical University of Warsaw, Warsaw, Poland.
Introduction And Objective: Surface electromyography (sEMG) measurements are a valid method for sublesional muscle activity following spinal cord injury (SCI). In the literature there are few reports evaluating the effect of robotic assisted gait training (RAGT) on the sEMG properties change in SCI patients. The aim of this study was to evaluate the influence of RAGT on observed change of sEMG, and in 64 incomplete SCI patients in the sub-acute stage in relation to functional scales.
View Article and Find Full Text PDFZhonghua Kou Qiang Yi Xue Za Zhi
January 2025
Department of Stomatology, The second affiliated hospital of Nanchang University,Nanchang330006, China.
Artificial intelligence (AI) technology is a scientific and technological field that focuses on the research and development of systems that simulate, extend, and expand human intelligence activities. This field encompasses various applications such as image recognition, language processing, expert systems, and robotics. The advancement of AI has greatly improved the quality and efficiency of medical work, particularly in areas like medical imaging, clinical decision support, precision medicine, and healthcare management.
View Article and Find Full Text PDFFront Robot AI
December 2024
Chair of Systematic Theology (Ethics), Seminar of Systematic Theology, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
Health is a multidimensional phenomenon encompassing physical, mental, social, and spiritual aspects. Therefore, it is only logical that good care should be holistic and include all these dimensions. However, when examining the current field of health and care robotics, the spiritual aspect is notably neglected.
View Article and Find Full Text PDFBiom J
February 2025
Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA.
Despite the extensive use of network autocorrelation models in social network analysis, network autocorrelation models for binary dependent variables have received surprisingly scant attention. In this paper, we develop four network autocorrelation models for a binary random variable defined by whether the peer effect (also termed social influence or contagion) acts on latent continuous outcomes leading to an indirect effect under a normal or a logistic distribution or on the probability of the observed outcome itself under a probit or a logit link function defining a direct effect to account for interdependence between outcomes. For all models, we use a Bayesian approach for model estimation under a uniform prior on a transformed peer effect parameter ( ) designed to enhance model computation and compare results to those under the uniform prior for .
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