A low-cost, portable, two-dimensional bioimpedance distribution estimation system based on the AD5933 impedance converter

Muñoz, Jaime Eduardo; Mosquera, Víctor Hugo; Rodas, Carlos Felipe Rengifo

doi:10.1016/j.ohx.2022.e00274

Cited by 9 publications

(6 citation statements)

References 42 publications

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“…On the other hand, the results of [34] indicate that a healthy knee exhibits an impedance between 260 and 360 Ohms at a frequency of 50 kHz, and a 5% decrease in knee impedance suggests joint injury. In-vitro tests reveal that the BIM system can measure impedances ranging from 155 to 977 Ohms [33], establishing its suitability for conducting KOA studies.…”

Section: Measurement Devicementioning

confidence: 98%

See 1 more Smart Citation

Machine learning-based bioimpedance assessment of knee osteoarthritis severity

Muñoz,

Mosquera,

Rengifo

et al. 2024

Biomed. Phys. Eng. Express

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This study proposes a multiclass model to classify the severity of knee osteoarthritis (KOA) using bioimpedance measurements. The experimental setup considered three types of measurements using eight electrodes: global impedance with adjacent pattern, global impedance with opposite pattern, and direct impedance measurement, which were taken using an electronic device proposed by authors and based on the Analog Devices AD5933 impedance converter. The study comprised 37 participants, 25 with healthy knees and 13 with three different degrees of KOA. All participants performed 20 repetitions of each of the following five tasks: (i) sitting withthe knee bent, (ii) sitting with the knee extended, (iii) sitting and performing successive extensions and flexions of the knee, (iv) standing, and (v) walking. Data from the 15 experimental setups (3 types of measurements × 5 exercises) were used to train a multiclass random forest. The training and validation cycle was repeated 100 times using random undersampling. At each of the 100 cycles, 80% of the data were used for training and the rest for testing. The results showed that the proposed approach achieved average sensitivities and specificities of 100% for the four KAO severity grades in the extensión, cyclic, and gait tasks. This suggests that the proposed method can serve as a screening tool to determine which individuals should undergo X-rays or magnetic resonance imaging for further evaluation of KOA.

show abstract

Section: Measurement Devicementioning

confidence: 98%

“…Bioimpedance measurements (BIM) were conducted using a custom-designed eight-channel electronic prototype previously developed [33] (figure 1). The BIM system incorporates an AD5933 impedance converter, which generates a 50 kHz alternating voltage signal.…”

Section: Measurement Devicementioning

confidence: 99%

Machine learning-based bioimpedance assessment of knee osteoarthritis severity

Muñoz,

Mosquera,

Rengifo

et al. 2024

Biomed. Phys. Eng. Express

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“…Two recently published articles from the university of Cauca propose a more complete open source systems, but feature, respectively, 8 electrodes [18] , and 4 rings of 8 electrodes [19] limiting the achievable in-plane imaging resolution.…”

Section: Hardware In Contextmentioning

confidence: 99%

A Wearable Open-Source electrical impedance tomography device

Creegan,

Bradfield,

Richardson

et al. 2024

HardwareX

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“…Since the value of the capacitance C affects the switching frequency of the signal V 2 but does not affect the linearity of the achieved characteristics, the results of the simulations are reported for the case C = 60 nF. Under these conditions, the resistance R 2 must comply with the constraints defined by Equations ( 5) and (10), and thus,…”

Section: Digitalmentioning

confidence: 99%

“…These systems are usually based on microcontrollers and/or Field Programmable Gate Arrays (FPGAs) and are powered by batteries [1] or scavenge energy from natural sources [2]. The sensing applications cover a wide range of fields, such as environmental monitoring [3][4][5], food screening for quality analysis and safety [6][7][8], biological measurements for human body composition determination and health monitoring [9][10][11], bacterial detection [12][13][14], chemical analysis [15][16][17], health monitoring, and data collection on civil infrastructures [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Efficient and Accurate Analog Voltage Measurement Using a Direct Sensor-to-Digital Port Interface for Microcontrollers and Field-Programmable Gate Arrays

Grossi

2024

Sensors

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Portable sensor systems are usually based on microcontrollers and/or Field-Programmable Gate Arrays (FPGAs) that are interfaced with sensors by means of an Analog-to-Digital converter (ADC), either integrated in the computing device or external. An alternative solution is based on the direct connection of the sensors to the digital input port of the microcontroller or FPGA. This solution is particularly interesting in the case of devices not integrating an internal ADC or featuring a small number of ADC channels. In this paper, a technique is presented to directly interface sensors with analog voltage output to the digital input port of a microcontroller or FPGA. The proposed method requires only a few passive components and is based on the measurements of the duty cycle of a digital square-wave signal. This technique was investigated by means of circuit simulations using LTSpice and was implemented in a commercial low-cost FPGA device (Gowin GW1NR-9). The duty cycle of the square-wave signal features a good linear correlation with the analog voltage to be measured. Thus, a look-up table to map the analog voltage values to the measured duty cycle is not required with benefits in terms of memory occupation. The experimental results on the FPGA device have shown that the analog voltage can be measured with a maximum accuracy of 1.09 mV and a sampling rate of 9.75 Hz. The sampling rate can be increased to 31.35 Hz and 128.31 Hz with an accuracy of 1.61 mV and 2.68 mV, respectively.

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A low-cost, portable, two-dimensional bioimpedance distribution estimation system based on the AD5933 impedance converter

Cited by 9 publications

References 42 publications

Machine learning-based bioimpedance assessment of knee osteoarthritis severity

Machine learning-based bioimpedance assessment of knee osteoarthritis severity

A Wearable Open-Source electrical impedance tomography device

Efficient and Accurate Analog Voltage Measurement Using a Direct Sensor-to-Digital Port Interface for Microcontrollers and Field-Programmable Gate Arrays

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