Fauzan, Muhammad (2018) Integrasi Leap Motion pada MedCap untuk Rehabilitasi Pasca Stroke Gerakan Jari Tangan Secara Online - Leap Motion Integration On Medcap For Post-Stroke Rehabilitation Of Finger Movements Online. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Rehabilitasi pasca stroke merupakan salah satu cara yang dapat membantu panderita stroke untuk mendapatkan kembali fungsi motorik, wicara, kognitif dan fungsi lainnya. Rehabilitasi pasca stroke memiliki beragam macam gerakan, salah satunya adalah gerakan jari tangan. MedCap muncul sebagai salah satu alat bantu yang dapat membantu fisioterapis dan pasien untuk melakukan rehabilitasi pasca stroke gerakan jari-jari tangan dengan memberikan feedback berupa nilai kesesuaian gerakan. Medcap menggunakan sensor gerakan tangan Leap Motion dapat merekam gerakan referensi yang telah ditentukan dengan rasio kesuksesan sebesar 62,35%. MedCap juga dapat menghitung kesesuaian gerakan referensi dan gerakan realtime dari pasien menggunakan metode Euclidean Distance sebagai bentuk feedback kepada fisioterapis dan pasien. Metode yang digunakan MedCap mampu menghitung kesesuaian gerakan referensi dengan gerakan realtime dengan rata-rata nilai sebesar 43,2495%. Selain itu MedCap juga terkoneksi dengan database online yang menghimpun gerakan referensi rehabilitasi pasca stroke gerakan jari tangan. Hasil pengujian database menunjukkan tingkat kecepatan rata-rata unggah sebesar 2,076 detik per frame dan kecepatan rata-rata unduh sebesar 0,676 detik. ========================================================================================================== An effort to help stroke patients to improve their motoric function, speech, cognition, and other impaired functions is by doing a series of post-stroke rehabilitation. Post-stroke rehabilitation has a variety of movements, one of which is the finger movement. MedCap emerged as one of the tools that can help physiotherapists and patients to do post-stroke rehabilitation of finger movements. Medcap uses Leap Motion sensor which can record a predetermined reference movement with a success rate around 62.35%. MedCap can also calculate the suitability of the reference movement and the realtime movement of the patient using the Euclidean Distance method as a form of feedback to the physiotherapist and patient. This method enables MedCap to calculate the suitability beetween reference movement and realtime movement with an average value around 43.2495%. In addition, MedCap is also connected with an online database that stores the reference movement of post-stroke rehabilitation of finger movements. The database test result shows an average upload speed of 2.076 seconds per frame and average download speed of 0.676 seconds.
| Item Type: | Thesis (Undergraduate) |
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| Additional Information: | RSKom 005.74 Ach v-1 3100018076387 |
| Uncontrolled Keywords: | Rehabilitasi Pasca Stroke; Self-Physical Rehabilitation ; Leap Motion ; Euclidean Distance |
| Subjects: | R Medicine > RM Therapeutics. Pharmacology |
| Divisions: | Faculty of Electrical Technology > Computer Engineering > 90243-(S1) Undergraduate Thesis |
| Depositing User: | Muhammad Fauzan |
| Date Deposited: | 08 Jan 2019 07:14 |
| Last Modified: | 15 Feb 2021 05:41 |
| URI: | https://repository.its.ac.id/id/eprint/58714 |
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