Along with changes in lifestyle, stroke is not only a disease that attacks the elderly population, but also often attacks people of productive age. Actions are proposed to the public to control risk factors, such as changing lifestyle behavior or taking medication, and variations in stroke risk are tracked by evaluating stroke risk annually. The symptom of stroke that is currently widely known by the public is paralysis, even though many stroke symptoms often appear without realizing it. So it is necessary to detect stroke using sensors and transducers to detect it. The aim of this research is to examine sensors and transducers for stroke detection. This research uses a systematic literature review using Preferred Reporting Items for Systematic Reviews (PRISMA). The results of article screening and selection found 84 potential articles that met the inclusion criteria. The research results show that the development of sensors and transducers for stroke detection is currently starting to develop through artificial intelligence based on the internet of thought which uses sensors and transducers within it. Judging from the production of tools that use sensors and transducers for stroke detection. Optimization of sensors and transducers for stroke detection must be carried out with appropriate use, detailed regulatory supervision, and continuous innovation of sensors and transducers for stroke detection which is useful in reducing the number of strokes in the world
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