Weninggalih, Natasya Adinda (2023) Pengembangan Sistem Pemantauan Spastisitas Otot pada Rehabilitasi Pasca Stroke dengan Terapi Functional Electrical Stimulation Menggunakan Fuzzy Clinical Decision Support System. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Stroke adalah penyebab utama kematian dan kecacatan yang signifikan. Spastisitas, yaitu peningkatan tonus otot yang dapat menghambat pemulihan dan rehabilitasi pasca stroke, terjadi pada 30%-80% kasus. Terapi Functional Electrical Stimulation (FES) telah terbukti efektif dalam mengurangi tingkat spastisitas dan meningkatkan fungsi motorik. Namun, pemantauan spastisitas yang objektif diperlukan untuk mengevaluasi kemajuan rehabilitasi. Penelitian ini mengembangkan sistem pemantauan spastisitas menggunakan Modified Ashwoth Scale (MAS) yang dikombinasikan dengan pendekatan biomekanis menggunakan data sudut sendi dan torsi. Sebuah sistem komputasi Fuzzy Clinical Decision Support System(FCDSS) diimplementasikan untuk menghasilkan nilai MAS berdasarkan data kuantitatif spastisitas. Hasil penelitian menunjukkan bahwa semua subjek dengan FCDSS memiliki nilai MMAS 0 dan severity bernilai zero. Selain itu, pengujian pada kondisi spastisitas yang berbeda menunjukkan hasil yang sesuai dengan tingkat keparahan yang diharapkan. Validasi sistem dengan membandingkan hasil keluaran sistem FCDSS dengan sistem konvensional menunjukkan hasil yang selaras dengan ketepatan 100%. Dalam rehabilitasi pasca stroke dengan FES, sistem ini membantu memantau perkembangan spastisitas sebagai indikator keberhasilan rehabilitasi. Dengan adopsi tata cara pengukuran konvensional, sistem ini memberikan penilaian yang objektif dan mengurangi ketergantungan pada penilaian subjektif. Data yang dihasilkan oleh sistem ini dapat diandalkan dan konsisten, memberikan dasar yang kuat untuk pengambilan keputusan dalam penyesuaian program rehabilitasi. Adaptasi machine learning dapat menjadi pengembangan berikutnya guna meningkatkan kecakapan sistem dalam menilai spastisitas.
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Stroke is a leading cause of mortality and significant disability. Spasticity, characterized by increased muscle tone that can impede recovery and post-stroke rehabilitation, occurs in 30%-80% of cases. Functional Electrical Stimulation (FES) therapy has proven effective in reducing spasticity levels and improving motor function. However, objective monitoring of spasticity is necessary to evaluate rehabilitation progress. This study aimed to develop an objective and reliable spasticity monitoring system using the Modified Ashworth Scale (MAS) combined with a biomechanical approach utilizing joint angle and torque data. A Fuzzy Clinical Decision Support System(FCDSS) computational system was implemented to generate MAS scores based on quantitative spasticity data. The findings revealed that all subjects using FCDSS had MMAS scores of 0, indicating no spasticity severity. Furthermore, testing under different spasticity conditions yielded results consistent with the expected severity levels. System validation by comparing the output of the FCDSS system with conventional systems shows consistent results with 100% accuracy. In post-stroke rehabilitation with FES, this system assists in monitoring spasticity progression as an indicator of rehabilitation success. By adopting conventional measurement techniques, the system provides an objective assessment, reducing reliance on subjective evaluations. The data generated by this system is reliable and consistent, providing a solid foundation for decision-making in rehabilitation program adjustments. The adaptation of machine learning can be considered as the next development aimed at enhancing the system's capability in assessing spasticity
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Stroke, Spastisitas, Rehabilitasi pasca stroke, Functional Electrical Stimulation (FES), Fuzzy Clinical Decision Support System(FCDSS), Stroke, Spasticity, Post Stroke rehabilitation, Functional Electrical Stimulation (FES), Fuzzy Clinical Decision Support System(FCDSS) |
| Subjects: | R Medicine > RM Therapeutics. Pharmacology > RM871 Electric stimulation. R Medicine > RM Therapeutics. Pharmacology > RM950 Rehabilitation technology. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Biomedical Engineering > 11410-(S1) Undergraduate Thesis |
| Depositing User: | Natasya Adinda Weninggalih |
| Date Deposited: | 07 Aug 2023 07:32 |
| Last Modified: | 07 Aug 2023 07:32 |
| URI: | http://repository.its.ac.id/id/eprint/103783 |
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