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Data science platform for smart diagnosis of upper limb spasticity

 
: Yee, J.; Low, C.Y.; Koh, C.T.; Enzberg, S. von; Rabe, M.; Wegel, A.; Asmar, L.; Hanapiah, F.A.; Hashim, N.M.; Zakaria, N.A.C.

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Volltext ()

Procedia manufacturing 52 (2020), S.250-257
ISSN: 2351-9789
International Conference on System-Integrated Intelligence (SysInt) <5, 2020, Online>
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IEM ()

Abstract
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.

: http://publica.fraunhofer.de/dokumente/N-639586.html