PENGEMBANGAN SISTEM REKOGNISI AKTIVITAS DAN PREDIKSI JATUH PADA LANSIA MENGGUNAKAN SENSOR IMU
DOI:
https://doi.org/10.25124/jett.v11i1.7299Keywords:
Fall prediction, HAR, IMU, elderly, machine learningAbstract
Urgensi pengembangan suatu sistem pengenalan aktivitas lansia serta memprediksi kemungkinan terjadinya jatuh menjadi prioritas dalam menghadapi total populasi lansia yang telah mencapai 11,34% di tahun 2020 dan diproyeksikan meningkat menjadi seperlima populasi Indonesia pada tahun 2045. Keluarga yang hidup bersama dengan lansia memiliki keterbatasan dalam memantau dan menjaga lansia, ditambah lagi dengan kekhawatiran akan kemungkinan terjadinya jatuh. Bertujuan untuk membantu keluarga lansia dalam memonitor aktivitas lansia maka dikembangkanlah suatu sistem pemantauan aktivitas lansia. Sedangkan untuk mengurangi risiko jatuh, sebuah alat yang dapat dikenakan pada lansia dilengkapi dengan mode peringatan berupa getaran yang akan aktif sesaat diprediksi lansia akan terjatuh. Sistem pemantauan aktivitas lansia menggunakan metode human activity recognition (HAR) dengan model XGBoost dan 6 fitur sedangkan prediksi jatuh diambil dari deteksi sensor IMU menggunakan threshold dari nilai mutlak terbesar pada akselerometer di sumbu . Performa yang didapat dari metode tersebut adalah akurasi sebesar 90% untuk HAR, 95% untuk prediksi jatuh, dan 83,3% untuk hasil integrasi keduanya.
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