Measurement of Cholesterol Concentration Based on Bioimpedance with AD5933-EVAL

Ain, Khusnul; Wibowo, R Arif; Soelistiono, Soegianto; Muniroh, Lailatul

doi:10.1109/icici-bme.2017.8537752

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…This result indicates that distinguishing the thumb from the other four fingers is sufficiently possible with a bioimpedance measurement circuit, and the accuracy is sufficient to install it in a small mobile device. (15,16) Therefore, in this study, we inferred that the highly accurate differentiation of the thumb and other fingers would be the first step toward realizing the proposed method, and the focus of the following examination will be on the differentiation between the thumb and the index finger.…”

Section: Bioimpedance Characteristics Of Each Fingermentioning

confidence: 98%

Bioelectromagnetic-response-based Input Interface for Mobile Devices —Finger Identification Using Bioimpedance Characteristics—

Muramatsu

2024

Sensors and Materials

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In this study, we realize a next-generation extended input interface that can identify the fingers used for operating mobile devices through bioelectromagnetic response sensing. First, the impedance characteristics of the five fingers were elucidated through an experiment involving different subjects. Furthermore, we discussed the possibilities of finger identification and subsequently focused on the differentiation between the thumb and the index finger. Next, we evaluated the differences between the bioimpedance characteristics of each finger for several subjects and clarified that the bioimpedance scale relation between fingers is the same for a particular subject. Moreover, the bioimpedance of a single subject was measured by letting the subject change the manner by which they hold a case or touch an electrode, and the results demonstrated that the bioimpedance characteristics of the thumb and index finger can be clearly distinguished even in discontinuous measurements. Finally, we implemented an identification algorithm in which the bioimpedance of the index finger from previous measurements was taken as the reference and performed evaluations to verify if a highly accurate differentiation of the thumb and index finger is possible. The results demonstrated that the proposed interface can be used in practical applications. Additionally, these findings highlight the potential of various applications utilizing bioelectromagnetic response sensing.

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Section: Bioimpedance Characteristics Of Each Fingermentioning

confidence: 98%

Bioelectromagnetic-response-based Input Interface for Mobile Devices —Finger Identification Using Bioimpedance Characteristics—

Muramatsu

2024

Sensors and Materials

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Design and Implementation of a Cost‐Effective, Portable Impedance Analyzer Device with AD5941

Tran,

Ha‐Phan,

Phan

et al. 2024

IEEJ Transactions Elec Engng

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This study proposes a cost‐effective, small‐size, and portable impedance analyzer using the AD5941 Analog Front End (AFE) that makes frequency sweep measurement for various applications. The design utilizes a microcontroller and an AD5941 circuit for impedance measurement. The AD541 is a high precision impedance converter system that consists of a 16‐bit, 1.6 MSPS, analog to digital converter (ADC), an integrated waveform generator, and a digital signal processing (DSP) block. The AD5941 has many advantages over the AD5933 which was used in numerous studies in the past decade. Also, the device implements the four‐wire impedance method which is an impedance measuring technique that reduces the effect of electrodes to achieve higher accuracy. A supporting Graphic User Interface (GUI) software is employed to control the Impedance Analyzer device and to visualize the measurement. This impedance analyzer achieves a frequency resolution of 0.015 Hz and can generate sinusoid up to 200 kHz. In frequency range from 10 kHz to 150 kHz, the device can measure impedance in the range of 10 Ω–100 kΩ with less than 4.3% of error in comparison with benchtop impedance analyzer, Microtest 6632. Moreover, our impedance measurement device has undergone testing involving human calf measurements and electrochemical quantification, particularly for estimating Sodium Chlorite. The experimental outcomes demonstrate that our design not only fulfills the criteria of an impedance analyzer device but also performs effectively across diverse applications. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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Deep Learning-Based Bioimpedance Spectroscopy Using Start of Frame Delimiter in Human Body Communications

Roopnarine,

Rocke

2024

Lecture Notes in Electrical Engineering

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Measurement of Cholesterol Concentration Based on Bioimpedance with AD5933-EVAL

Cited by 4 publications

References 8 publications

Bioelectromagnetic-response-based Input Interface for Mobile Devices —Finger Identification Using Bioimpedance Characteristics—

Bioelectromagnetic-response-based Input Interface for Mobile Devices —Finger Identification Using Bioimpedance Characteristics—

Design and Implementation of a Cost‐Effective, Portable Impedance Analyzer Device with AD5941

Deep Learning-Based Bioimpedance Spectroscopy Using Start of Frame Delimiter in Human Body Communications

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