A Wrist Watch-type Cardiovascular Monitoring System using Concurrent ECG and APW Measurement

Lee, Kwonjoon; Song, Kiseok; Roh, Taehwan; Yoo, Hoi‐Jun

doi:10.5573/jsts.2016.16.5.702

Cited by 4 publications

(7 citation statements)

References 5 publications

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“…Two types of oscillators have been adopted in on-chip EIS systems: RC-controlled and g m -C-controlled structures. RC-controlled structures, which are based on the Wien-bridge architecture, have been adopted in on-chip EIS systems that target f SG less than 200 kHz [5], [28], [84]- [86]. Fig.…”

Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

“…An 1.8-nF off-chip capacitor is used with an 8-MΩ on-chip resistor, consuming a large area [28]. In order to avoid off-chip components, back-to-back diodes are connected in parallel to the feedback resistors in a replacement of the differential envelope detector and M 1 [86]. Diodes can be integrated inside the chip, but the THD of the oscillator is higher than -60 dBc.…”

Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

“…Furthermore, the highest f SG is limited by the gain-bandwidth product (GBW) of the amplifiers. The linearity of these oscillators is dependent on the quality (Q) factor of the band-pass filter [86], [87]. Since the Q factor is strongly dependent on the gain of amplifier [84], a large GBW is required to obtain high linearity in the high-frequency region.…”

Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

“…For example, the FDAs in [84] has 80-MHz GBW to support f SG up to 76 kHz with 2.38% THD. Similarly in [86], the amplifier has 10-MHz GBW to support f SG of 100 kHz with THD of less than 1%. As the GBW is required to be about 100 times higher than the target f SG , the maximum f SG is limited by the achievable GBW in a given power budget.…”

Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

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On-Chip Sinusoidal Signal Generators for Electrical Impedance Spectroscopy: Methodological Review

Kweon¹,

Rafi

Cheon

et al. 2022

IEEE Trans. Biomed. Circuits Syst.

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This paper reviews architectures and circuit implementations of on-chip sinusoidal signal generators (SSGs) for electrical impedance spectroscopy (EIS) applications. In recent years, there have been increasing interests in on-chip EIS systems, which measure a target material's impedance spectrum over a frequency range. The on-chip implementation allows EIS systems to have low power and small form factor, enabling various biomedical applications. One of the key building blocks of on-chip EIS systems is on-chip SSG, which determines the frequency range and the analysis precision of the whole EIS system. On-chip SSGs are generally required to have high linearity, wide frequency range, and high power and area efficiency. They are typically composed of three stages in general: waveform generation, linearity enhancement, and current injection. First, a sinusoidal waveform should be generated in SSGs. The generated waveform's frequency should be accurately adjustable over a wide range. The firstly generated waveform may not be perfectly linear, including unwanted harmonics. In the following linearity-enhancement step, these harmonics are attenuated by using filters typically. As the linearity of the waveform is improved, the precision of the EIS system gets ensured. Lastly, the filtered voltage waveform is now converted to a current by a current driver. Then, the current sinusoidal signal is injected into the target impedance. This review discusses the principles, advantages, and disadvantages of various techniques applied to each step in state-of-the-art on-chip SSGs. In addition, state-of-the-art designs are compared and summarized.

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Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

Section: Oscillator-based Sinusoidal Waveformmentioning

confidence: 99%

See 2 more Smart Citations

On-Chip Sinusoidal Signal Generators for Electrical Impedance Spectroscopy: Methodological Review

Kweon¹,

Rafi

Cheon

et al. 2022

IEEE Trans. Biomed. Circuits Syst.

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show abstract

“…16)17) Table 1 lists 9 studies about data generation and monitoring via PGHD for diagnosing, preventing, and managing cardiovascular and cerebrovascular disease. [18][19][20][21][22][23][24][25][26] Using smartphones and wearable devices to influence cardiovascular and cerebrovascular health developed from the study of the feasibility of their efficacy in the clinical environment. 27)28) Several studies have found positive influences of data obtained this way for cardiovascular and cerebrovascular health in improved everyday behaviors and self-care regarding the disease.…”

Section: Data Generation and Measurementmentioning

confidence: 99%

Recent Technology-Driven Advancements in Cardiovascular Disease Prevention in Korea

Lee

Kim

2019

Cardiovasc Prev Pharmacother

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Recent dramatic developments in information and communication technologies have been widely applied to medicine and healthcare. In particular, biometric sensors in wearable devices linked to smartphones are collecting vast amounts of personal health data. To best use these accumulated data, personalized healthcare services are emerging, and digital platforms are being developed and studied to enable data integration and analysis. The implementation of biometric sensors and smartphones for cardiovascular and cerebrovascular healthcare emerged from the research on the feasibility and efficacy of the devices in the clinical environment. It is important to understand the recent research trends in data generation, integration, and application to prevent and treat cardiovascular and cerebrovascular diseases. This paper describes these recent developments in treating cardiovascular diseases.

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Critical implementation issues of excitation signals for embedded wearable bioimpedance spectroscopy systems with limited resources

Kallel

Bouchaala

Kanoun

2021

Meas. Sci. Technol.

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Wideband excitation signals are essential in bioimpedance spectroscopy for measurements in a time ensuring a quasi-stable measurement condition. In particular, for wearable biomedical systems, due to limited system resources, several aspects regarding measurement time, crest factor, slew rate requirements, frequency distribution, amplitude spectrum, and energy efficiency need to be thoroughly investigated. In this paper, we present an investigation of excitation signals, which includes not only the theoretical aspects but also aspects of real implementation on microcontroller-based systems. At a fixed number of samples and sampling rate, we investigate the implementability of signal frequencies and the resulting spectral efficiency. We focus on sources of signal distortion due to timer and amplitude deviations. The results show that for 4096 samples and a sampling frequency of 1 MHz, wideband signals are 2.76 times faster than a stepped frequency sweep. The multisine signal provides a better energy efficiency and has a lower slew rate requirement on hardware (around 0.3 V µs−1), but has a relatively high crest factor, even after optimization. An exemplary investigation of the distortion of the time/frequency and amplitudes following implementation on a standard industrial advanced RISC machines microcontroller has shown that a sampling rate compensation is required to overcome timer inaccuracies. Furthermore, non-return-to-zero binary signals are more sensitive to distortion due to hardware-related issues and have a lower signal-to-distortion-and-noise (SINAD) ratio than 24 dB, which is lower than the multisine signal, having a SINAD of 31 dB.

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A Wrist Watch-type Cardiovascular Monitoring System using Concurrent ECG and APW Measurement

Cited by 4 publications

References 5 publications

On-Chip Sinusoidal Signal Generators for Electrical Impedance Spectroscopy: Methodological Review

On-Chip Sinusoidal Signal Generators for Electrical Impedance Spectroscopy: Methodological Review

Recent Technology-Driven Advancements in Cardiovascular Disease Prevention in Korea

Critical implementation issues of excitation signals for embedded wearable bioimpedance spectroscopy systems with limited resources

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