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- Abdelakram, Hafid, et al.
(author)
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Estimating Physiological Parameters in Various Age Groups : Windkessel 4 Element Model and PPG Waveform Analysis Approach
- 2023
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In: IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023. - : IEEE. - 9798350313826 ; , s. 194-197
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Conference paper (peer-reviewed)abstract
- Non-invasive monitoring of cardiovascular health through photoplethysmography (PPG) waveforms has emerged as a crucial area of research. The Windkessel 4-Element (WK4) model is a mathematical approach used to estimate key physiological parameters related to cardiovascular health, including arterial compliance, peripheral resistance, inertance, and total arterial resistance. This study aimed to evaluate key physiological parameters associated with cardiovascular health using the WK4 model, leveraging real-life PPG waveform data obtained from volunteers across three distinct age groups. To achieve this, an algorithm was developed to automatically determine optimal parameter values for each volunteer. The results revealed a mean correlation coefficient of 0.96 between the automatically generated waveforms by the algorithm and the actual real-life PPG waveforms, indicating robust agreement. Notably, only the total arterial resistance parameter exhibited significant differences among the age groups, suggesting that the algorithm holds promise for detecting agerelated changes in cardiovascular health. These findings emphasize the potential for the development of a non-invasive tool to assess cardiovascular health status and enhance healthcare outcomes. Furthermore, they underscore the capability of the developed algorithm as a non-invasive means to evaluate various aspects of cardiovascular physiology. Additionally, the versatility of this algorithm opens doors for its application in educational settings, promoting knowledge advancement, empowering research endeavors, and facilitating advancements in the field.
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| 2. |
- Abdullah, Saad, et al.
(author)
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Comparing the Effectiveness of EMG and Electrical Impedance myography Measurements for Controlling Prosthetics
- 2023
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In: IEEE Int. Multidiscip. Conf. Eng. Technol., IMCET. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350313826 ; , s. 189-193
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Conference paper (peer-reviewed)abstract
- In recent years, the field of prosthetics has made significant progress towards creating prosthetic devices that are more functional, comfortable, and user-friendly. However, achieving intuitive control over prosthetic hand movements remains a significant challenge, especially for individuals with limb loss who rely on prosthetics for independent daily activities. To address this challenge, researchers have explored the potential of non-invasive techniques as electromyography (EMG) for prosthetic control. This paper aims to investigate the potential of using EMG and the electrical impedance myography (EIMG) techniques jointly for the measurement of hand movements. The study involved recording and comparing EMG and EIMG signals from a cohort of healthy individuals. These signals were captured during four distinct hand gestures: opening and closing the hand, as well as extending and flexing it, under varying time conditions, allowing for categorization into low and high-intensity movements. Data collection employed the Open BCI and ZRPI devices. The analysis of these signal waveforms revealed compelling results. Brachioradialis activity in EMG 2 exhibited an increase during open hand (0.015mV) and extension hand (0.009mV in low and 0.013mV in high intensity) gestures, accompanied by increased EIMG activity (56mV and 52mV respectively). Additionally, close hand (0.0018mV in low and 0.05mV in high intensity) and flexion hand (0.0075 in low intensity and 0.002 in high intensity) gestures exhibited heightened flexor carpi ulnaris activity with raised EIMG activity (57mV and 45mV respectively). These results proved to be consistent, acceptable, and aligned with existing literature. The findings of this paper indicate that both EMG and EIMG techniques could be used together to control custom-made hand prosthetics, demonstrating a significant development that could lead to more intuitive and easier-to-control prosthetics. Also, the results obtained could be valuable to researchers and engineers working in the prosthetics field, as it provides insights into the potential of non-invasive techniques for prosthetic control.
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