Jonathan Levin Behrens, Christian Kowalski, Anna Brinkmann, Sara Marquard, Sandra Hellmers, Maren Asmussen-Clausen, Karina Jürgensen, Stephanie Raudies, Manfred Hülsken-Giesler, Andreas Hein
{"title":"Physical relief potential through robot-assisted mobilization in nursing care: an exploratory study","authors":"Jonathan Levin Behrens, Christian Kowalski, Anna Brinkmann, Sara Marquard, Sandra Hellmers, Maren Asmussen-Clausen, Karina Jürgensen, Stephanie Raudies, Manfred Hülsken-Giesler, Andreas Hein","doi":"10.1007/s12553-023-00795-7","DOIUrl":null,"url":null,"abstract":"Abstract Purpose Physically demanding activities at the nursing bed are a key factor in the overwork of nursing staff and play a major role in the development of musculoskeletal disorders. The heavy back strain plays a significant part in this. Technical aids such as robotic assistance systems have the potential to minimize this overload during nursing activities. In the present work, we have investigated the relief potential of a supporting robotic assistance system developed in the AdaMeKoR project. An exploratory study design was developed to assess the relief potential of the robotic system for nurses during the care action of repositioning from the supine position to the sitting position at the edge of a nursing bed under kinaesthetic principles. Methods The study was conducted in March 2022 with a total of 21 nursing professionals participating. Safety precautions at this stage of the robot’s development made it necessary to use a 40 kg patient simulator instead of having a human act as the patient. Each participant performed the repositioning three times in the conventional manner and three times with the robotic-assistance. The conventional and the robotic-assisted task execution was compared using different perspectives of analysis. From a sensory perspective, ground reaction forces and electromyography data were collected and analyzed. A kinaesthetic perspective was added using 3D-video data which was analyzed by professional kinaesthetics trainers. A third perspective was added by collecting the subjective workload experiences of the participants. Results While participants’ self-assessment based on a NASA-TLX questionnaire suggests more of a physical and psychological strain from using the robot, electromyography shows a 24.41% reduction in muscle activity for left back extensors and 7.99% for right back extensors. The kinaesthetic visual inspection of the study participants also allows conclusions to be made that the robot assistance system has a relieving effect when performing the nursing task. Conclusions The conducted study suggests that overall the robotic-assistance has the potential of relieving nurses of partial physical exertion during mobilization. However, the different focuses of analysis show varying results in regard to external, i.e. sensor data and expert analysis, compared to internal, i.e. the nurses, perspectives. Going forward, these results have to be further expanded to get more robust analyses and insights on the interdependencies of subjective factors contributing to the experience of workload. In view of the fact that robotics for nursing is still a relatively new field and there are various lessons to be learned regarding the conceptualization of studies and corresponding evaluations, our approach of combining perspectives of analysis allows for a more differentiated view of the subject at hand.","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12553-023-00795-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Purpose Physically demanding activities at the nursing bed are a key factor in the overwork of nursing staff and play a major role in the development of musculoskeletal disorders. The heavy back strain plays a significant part in this. Technical aids such as robotic assistance systems have the potential to minimize this overload during nursing activities. In the present work, we have investigated the relief potential of a supporting robotic assistance system developed in the AdaMeKoR project. An exploratory study design was developed to assess the relief potential of the robotic system for nurses during the care action of repositioning from the supine position to the sitting position at the edge of a nursing bed under kinaesthetic principles. Methods The study was conducted in March 2022 with a total of 21 nursing professionals participating. Safety precautions at this stage of the robot’s development made it necessary to use a 40 kg patient simulator instead of having a human act as the patient. Each participant performed the repositioning three times in the conventional manner and three times with the robotic-assistance. The conventional and the robotic-assisted task execution was compared using different perspectives of analysis. From a sensory perspective, ground reaction forces and electromyography data were collected and analyzed. A kinaesthetic perspective was added using 3D-video data which was analyzed by professional kinaesthetics trainers. A third perspective was added by collecting the subjective workload experiences of the participants. Results While participants’ self-assessment based on a NASA-TLX questionnaire suggests more of a physical and psychological strain from using the robot, electromyography shows a 24.41% reduction in muscle activity for left back extensors and 7.99% for right back extensors. The kinaesthetic visual inspection of the study participants also allows conclusions to be made that the robot assistance system has a relieving effect when performing the nursing task. Conclusions The conducted study suggests that overall the robotic-assistance has the potential of relieving nurses of partial physical exertion during mobilization. However, the different focuses of analysis show varying results in regard to external, i.e. sensor data and expert analysis, compared to internal, i.e. the nurses, perspectives. Going forward, these results have to be further expanded to get more robust analyses and insights on the interdependencies of subjective factors contributing to the experience of workload. In view of the fact that robotics for nursing is still a relatively new field and there are various lessons to be learned regarding the conceptualization of studies and corresponding evaluations, our approach of combining perspectives of analysis allows for a more differentiated view of the subject at hand.
期刊介绍:
Health and Technology is the first truly cross-disciplinary journal on issues related to health technologies addressing all professions relating to health, care and health technology.The journal constitutes an information platform connecting medical technology and informatics with the needs of care, health care professionals and patients. Thus, medical physicists and biomedical/clinical engineers are encouraged to write articles not only for their colleagues, but directed to all other groups of readers as well, and vice versa.By its nature, the journal presents and discusses hot subjects including but not limited to patient safety, patient empowerment, disease surveillance and management, e-health and issues concerning data security, privacy, reliability and management, data mining and knowledge exchange as well as health prevention. The journal also addresses the medical, financial, social, educational and safety aspects of health technologies as well as health technology assessment and management, including issues such security, efficacy, cost in comparison to the benefit, as well as social, legal and ethical implications.This journal is a communicative source for the health work force (physicians, nurses, medical physicists, clinical engineers, biomedical engineers, hospital engineers, etc.), the ministries of health, hospital management, self-employed doctors, health care providers and regulatory agencies, the medical technology industry, patients'' associations, universities (biomedical and clinical engineering, medical physics, medical informatics, biology, medicine and public health as well as health economics programs), research institutes and professional, scientific and technical organizations.Health and Technology is jointly published by Springer and the IUPESM (International Union for Physical and Engineering Sciences in Medicine) in cooperation with the World Health Organization.