ULTRA WIDE-BAND RADAR FOR THE REAL-TIME MONITORING OF HEART RATE USING CONVOLUTIONAL NEURAL NETWORK=ỨNG DỤNG MẠNG NƠ RON TÍCH CHẬP CHO HỆ THỐNG THEO DÕI NHỊP TIM THEO THỜI GIAN THỰC SỬ DỤNG RA ĐA BĂNG THÔNG SIÊU RỘNG

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Tác giả: Đăng Khánh Lê

Ngôn ngữ: eng

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Thông tin xuất bản: Tạp chí Khoa học Công nghệ Hàng hải, 2024

Mô tả vật lý: tr.47

Bộ sưu tập: Metadata

ID: 481649

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Các radar băng thông siêu rộng (UWB) đang nhận được nhiều sự quan tâm đối với các ứng dụng hàng hải trên các tàu thông minh và tàu hạng sang, trong đó radar UWB có thể được tích hợp vào Hệ thống cảnh báo và giám sát cầu dẫn đường - BNWAS. Một trong những ứng dụng thú vị của radar UWB là đo các tín hiệu sống, đây là phương pháp không tiếp xúc. Radar UWB đo nhịp thở và nhịp tim bằng chuyển động của lồng ngực để phát hiện và kiểm tra trạng thái của người trong ca trực. Tuy nhiên, chuyển động của lồng ngực do nhịp tim gây ra thường có cường độ thấp và dễ bị nhiễu và nhiễu loạn bởi tín hiệu không cố định. Do đó, một thuật toán được phát triển dựa trên mạng nơ ron tích chập để theo dõi nhịp tim không tiếp xúc bằng radar băng thông siêu rộng (UWB). Phần tiền xử lý bao gồm nhiều bước cần thiết để xử lý tín hiệu thô từ radar UWB. Trong nghiên cứu này, các số liệu đánh giá bao gồm sai số bình phương trung bình gốc là 11,34, sai số tuyệt đối trung bình là 8,98, độ lệch chuẩn của tín hiệu ước tính là 4,05 và sai số phần trăm của HR trung bình là 5,77%. Mô hình đề xuất có thể đo được nhịp tim và phục vụ cho công tác theo dõi tình trạng sức khoẻ, tâm lý của người được theo dõi.Ultra-wideband (UWB) radars are getting much attention for maritime applications of smart and luxury ships in which UWB radar could be integrated into Bridge Navigational Watch & Alarm System - BNWAS. One of the interesting applications of UWB radar is vital signs measurement, which is a contactless method. UWB radar measures respiration and heartbeat rate by the motion of thorax for detecting and checking the state of people on the bridge. However, the motion of the thorax caused by the heartbeat is usually low intensity and easily gets noisy and perturbed by a non-stationary signal. Due to this, an architecture built by a convolutional neural network is developed and modified to monitor heart rate using a contactless ultra wide-band (UWB) radar. The preprocessing part including many steps is necessary to clean raw signals from UWB radar. In this study, the evaluation metrics included a root mean square error of 11.34, a mean absolute error of 8.98, a standard deviation of the estimated signal of 4.05, and a percentage error of average HR at 5.77%. The proposed model could capture HR and is expected to be used for monitoring health and psychological status.

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