Abstract
Pain in a baby is difficult to detect is because the method for detecting pain is self-reporting even though babies themselves still cannot describe the pain verbally, then by observing changes in behavior in the form of facial expressions. Statistically, it is also recorded that about 80% of the world's population pays less attention to pain assessment, especially for children, even though this pain gives children a bad experience so that it can interfere with pain responses in the future or psychological trauma. Based on these problems, a prototype system was made using the NVIDIA Jetson Nano Developer kit to help detect pain, especially in infants 0-12 months by using the Convolutional Neural Network (CNN) model with the PyTorch framework and the You Only Look Once (YOLO) algorithm with three detection classification is sad, neutral and sick. From the results of the study, it was found that the YOLO algorithm was able to detect the three classifications with a sad mAP value of 77.8%, neutral 76.7%, in pain 68.9%. With a precision value of 71.4%, recall 62.5% and f1-score 66.6%. The average value of Confidence is 53.57%.
Highlights
Dengan semakin pesatnya kemajuan teknologi computer vision, salah satunya dengan memanfaatkan data citra wajah
From the results of the study, it was found that the You Only Look Once (YOLO) algorithm was able to detect the three classifications with mean Average Precision (mAP)@0.5 value of sad 97,9%, neutral 99,2%, pain 96,9%, model accuracy 70%
Activity (EDA) Skin Conductance Responses (SCRs) for “Infants’ pain recognition based on facial expression: Dynamic
Summary
Dengan semakin pesatnya kemajuan teknologi computer vision, salah satunya dengan memanfaatkan data citra wajah. Untuk verbal pain scale revised (NVPSR) yang memiliki menunjang penilaian tersebut terdapat beberapa cara korelasi yang kuat dengan WBPS dalam menilai nyeri salah satunya yaitu melihat perubahan perilaku yang pada anak. Beberapa metode yang sering digunakan untuk mengukur tingkat rasa nyeri pada anak adalah metode Visual Analog Scale (VAS), Verbal Rating Scale (VRS), pula dengan cara mengklasifikasikan respon wajah pada bayi menggunakan CNN ketika mengalami suatu rasa nyeri [21]. Hasil monitoring tersebut digunakan untuk menginterpretasikan nyeri secara keseluruhan, melakukan jenis tindakan pemulihan nyeri dan sedangkan nonverbal pain scale (NVPS) memiliki ketidaknyamanan lebih awal agar tidak menciptakan korelasi yang lebih kuat dalam mendeteksi rasa nyeri rasa trauma berkepanjangan terhadap bayi. Blok Diagram Sistem dalam grid berukuran s x s dari setia grid akan Untuk membangun sistem pendeteksi rasa nyeri ini memprediksi bounding box serta peta kelas masing- dimulai dengan membuat dataset, training dan testing masing grid. 12 bulan, pada the child affective facial expression set (CAFÉ)[22] juga menyediakan dataset utuk anak-anak tetapi rentang umur yang tersedia mulai dari 2 tahun sampai 8 tahun
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