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Data Science Platform for Smart Diagnosis of Upper Limb Spasticity

机译:数据科学平台,用于智能诊断上肢痉挛

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Providing optimal rehabilitation services to the broad public is one of the greatest challenges in the healthcare sector due to the shortage of rehabilitation physicians and facilities. Recent advances in digitalization and sophisticated data analytics offers new innovative ways in delivering rehabilitation services to enhance the quality of life of people with disabilities. Currently, the development of data-driven solutions for rehabilitation in Malaysia is limited due to multiple factors: medical and rehabilitation data is not digitally stored; the knowledge for the interpretation of clinical data is distributed; in particular, there is a lack of expertise in the field of medical data science. Thus, a data science platform is proposed so that medical expertise can be made available through digital services and is not dependent on human resource, location, time or financial ability. This platform is applied for the smart diagnosis of upper limb spasticity in compliance with clinical practice, and extensible for the other smart rehabilitation applications. By collaborating with the prestigious Fraunhofer Society, their knowhow in industrial data science can be brought to Malaysia towards improved health care in the country. The smart diagnosis system provides advice in classifying the severity level of upper limb spasticity based on the Modified Ashworth Scale and the Modified Tardieu scale. The basis is a measurement system for muscle signal, muscle tone and elbow motion. Users of the smart diagnosis application include rehabilitation physicians, doctors from other specialities, nurses, psychologists, physiotherapists and occupational therapists. The tools provided by the data science platform is deployed to store and analyze the clinical data. Further, the expertise of a rehabilitation physician is emulated in the form of an expert system to determine the severity level of upper limb spasticity. The digital clinical database helps medical researchers in secondary analysis towards knowledge discovery for the betterment of intervention and treatment of spasticity.
机译:为广义提供最佳的康复服务是由于康复医生和设施短缺,医疗保健部门的最大挑战之一。数字化和复杂数据分析的最新进展在提供康复服务方面提供了新的创新方法,以提高残疾人的生活质量。目前,由于多种因素,马来西亚康复的数据驱动解决方案的开发是有限的:医疗和康复数据未进行数字储存;分布临床数据的解释知识;特别是,医学数据科学领域缺乏专业知识。因此,提出了一种数据科学平台,以便通过数字服务提供医学专业知识,并且不依赖于人力资源,位置,时间或财务能力。该平台适用于遵守临床实践的上肢痉挛的智能诊断,并对其他智能康复应用进行伸展。通过与着名的Fraunhofer社会进行合作,他们在工业数据科学的知识可以向马来西亚带来国家改善了该国的医疗保健。智能诊断系统在分类​​基于修改的Ashworth规模和修改的Tardieu规模的基础上分类上肢痉挛的严重性水平的建议。基础是肌肉信号,肌肉音调和肘部运动的测量系统。智能诊断应用程序的用户包括康复医生,来自其他特色,护士,心理学家,物理治疗师和职业治疗师的医生。部署数据科学平台提供的工具以存储和分析临床数据。此外,康复医师的专业知识是以专家系统的形式模拟,以确定上肢痉挛的严重程度。数字临床数据库有助于医学研究人员对知识发现的次要分析,以获得痉挛的干预和治疗。

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