Bearbmagovva

Development of a Low-Cost Multi-Physiological Signal Simulation System for Multimodal Wearable Device Calibration

Furkejuvvon:
Publikašuvnnas:Technologies vol. 13, no. 6 (2025), p. 239-253
Váldodahkki: Tumenkhuslen, Delgerkhaan
Eará dahkkit: Wei, Qun, Jung Jiwoo, Lee, Sangwon, Gangoh, Na, Kim Bongjo, Kim, In-Cheol, Park, Heejoon
Almmustuhtton:
MDPI AG
Fáttát:
Receivers & amplifiers
Physiology
Simulation
Integrated circuits
Accuracy
Low cost
Performance evaluation
Mortality
Pulse oximetry
Calibration
Multitasking
Light emitting diodes
Cardiovascular disease
Wearable technology
Wearable computers
Medical equipment
Medical devices
Transit time
Professionals
Heart
Blood
Digital to analog converters
Sound
Correlation analysis
Liŋkkat:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Fáddágilkorat: Lasit fáddágilkoriid
Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!
Abstrákta:Using multimodal wearable devices to diagnose cardiovascular diseases early is essential for providing timely medical assistance, particularly in remote areas. This approach helps prevent risks and reduce mortality rates. However, prolonged use of medical devices can lead to measurement inaccuracies, necessitating calibration to maintain precision. Unfortunately, wearable devices often lack affordable calibrators that are suitable for personal use. This study introduces a low-cost simulation system for phonocardiography (PCG) and photoplethysmography (PPG) signals designed for a multimodal smart stethoscope calibration. The proposed system was developed using a multicore microprocessor (MCU), two digital-to-analog converters (DACs), an LED light, and a speaker. It synchronizes dual signals by assigning tasks based on a multitasking function. A designed time adjustment algorithm controls the pulse transit time (PTT) to simulate various cardiovascular conditions. The simulation signals are generated from preprocessed PCG and PPG signals collected during in vivo experiments. A prototype device was manufactured to evaluate performance by measuring the generated signal using an oscilloscope and a multimodal smart stethoscope. The preprocessed signals, generated signals, and measurements by the smart stethoscope were compared and evaluated through correlation analysis. The experimental results confirm that the proposed system accurately generates the features of the physiological signals and remains in phase with the original signals.
ISSN:2227-7080
DOI:10.3390/technologies13060239
Gáldu:Materials Science Database