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dc.contributor.authorAmarasekara, YR
dc.contributor.authorGoonatilleke, MAST
dc.date.accessioned2025-02-11T07:30:40Z
dc.date.available2025-02-11T07:30:40Z
dc.date.issued2023-02-06
dc.identifier.urihttp://ir.kdu.ac.lk/handle/345/8249
dc.description.abstractPain in the feet, circulatory problems, and tension are some of the less noticed yet very basic parts of everyday health concerns. Traditional Marma therapy offers an effective treatment to alleviate these conditions through stimulation at specific pressure points. However, access to this therapy is highly restricted due to dependency on trained and qualified human practitioners. This study reviews how modern technology integrated into smart footwear products can facilitate personalized Marma foot therapy. This development combines the therapeutic benefits of traditional practices with the convenience of wearable devices, using pressure sensors to identify key Marma points, vibratory motors for targeted stimulation, and IoT technology for wireless control and real-time feedback via mobile applications. The study critically analyzes the IoT architecture, and the communication frameworks used in those systems, pointing out their functions in monitoring foot pressure distribution, adapting therapy to individual needs, and cost-effectiveness with components such as FSR sensors, DC vibration motors, and ESP32 microcontrollers. This covers challenges like the exact detection of Marma points, user acceptance, and feasibility for large-scale production, together with possible solutions. This review identifies IoT-based smart footwear technology as a game-changing tool in the advancement of foot health management and general well-being, thus paving the way for wider adoption of personalized therapeutic intervention
dc.language.isoenen_US
dc.subjectIoTen_US
dc.subjectLow-cost smart footwearen_US
dc.subjectMarma pointsen_US
dc.subjectVibratory motorsen_US
dc.subjectFoot healthen_US
dc.titleComprehensive Review for Development of a Smart IoT Based Marma Foot Therapy Shoeen_US
dc.typeArticle Abstracten_US
dc.identifier.facultyFaculty of Computingen_US
dc.identifier.journal5th Student Symposium Faculty of Computing-SSFOC-2025en_US
dc.identifier.pgnos4en_US


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