Coherent detection stochastic resonance assisted biomagnetometer for measuring magnetocardiography at room temperature

Liao, Zhiqiang; Jin, Shixu; Kuwahata, Akihiro; Sekino, Masaki; Tabata, Hitoshi

doi:10.35848/1882-0786/ac1de5

Cited by 14 publications

(2 citation statements)

References 36 publications

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“…In future work, we plan to perform experiments to collect the BP and ICP data simultaneously and study a regression model that leverages brain BIOZ to estimate BP and ICP simultaneously. Finally, recent studies have introduced the utilization of magnetic sensors, such as magnetocardiography, for the contactless monitoring of BIOZ [45] and cardiac signal [46]. BrainZ-BP monitoring system can also expand to using magnetic sensors for contactless BP estimation.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Non-invasive cuff-less blood pressure estimation using a hybrid deep learning model

et al. 2021

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Conventional blood pressure (BP) measurement methods have different drawbacks such as being invasive, cuff-based or requiring manual operations. There is significant interest in the development of non-invasive, cuff-less and continual BP measurement based on physiological measurement. However, in these methods, extracting features from signals is challenging in the presence of noise or signal distortion. When using machine learning, errors in feature extraction result in errors in BP estimation, therefore, this study explores the use of raw signals as a direct input to a deep learning model. To enable comparison with the traditional machine learning models which use features from the photoplethysmogram and electrocardiogram, a hybrid deep learning model that utilises both raw signals and physical characteristics (age, height, weight and gender) is developed. This hybrid model performs best in terms of both diastolic BP (DBP) and systolic BP (SBP) with the mean absolute error being 3.23 ± 4.75 mmHg and 4.43 ± 6.09 mmHg respectively. DBP and SBP meet the Grade A and Grade B performance requirements of the British Hypertension Society respectively.

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Section: Limitations and Future Workmentioning

confidence: 99%

Non-invasive cuff-less blood pressure estimation using a hybrid deep learning model

et al. 2021

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“…The biocompatibility and chemical inertness of diamond make it widely used in biology and medicine. 7,8) Extremely low-frequency magnetic field has great value in biological research, which can directly exert influence biological tissue, such as some researchers have confirmed that the use of extremely low-frequency magnetic fields can inhibit the growth of cancer cells without causing lymphocyte necrosis; 9,10) on the other hand, by detecting the extremely low-frequency magnetic field generation by the organism itself to identify the biological state, it has been applied in some experiments, such as in the biological magnetic field research of the human heart, [11][12][13] it is found that the cardiac magnetic field is an extremely lowfrequency magnetic field, at the same time, influenced by the changes in cardiac physiological characteristics, which is used in the diagnosis of heart disease or potential disease. In addition, diamond is also used in battery testing, 14) IC imaging, 15,16) current sensing, [17][18][19] and other fields.…”

Section: Introductionmentioning

confidence: 99%

Extremely low-frequency magnetic spectrum measurement method based on the NV center in diamond

Li,

Wang,

Gao

et al. 2023

Jpn. J. Appl. Phys.

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In this paper, we establish a set of schemes to generate, detect, and identify the multi-frequency magnetic field in the extremely low-frequency range. Based on the magnetic sensitivity of nitrogen-vacancy centers in diamond, the schemes adopt frequency closed-loop proportion-integration-differentiation locking and microwave modulation and demodulation to obtain magnetic field information. A set of multi-coil mutual inductance devices is used to generate a multi-frequency AC magnetic field. In the schemes, the DenseNet network structure is used to train and identify the magnetic field information, with a recognition rate of 99.16%. When the Net is used to identify noisy signals, it still maintains an average recognition rate of 95.18% for random frequency noisy signals. This generating, detecting, and identifying schemes of the multi-frequency magnetic field in the extremely low-frequency range based on quantum sensors in this paper provides a novel idea for the future application of quantum sensors in biomedicine.

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Quantum Analog Annealing of Gain‐Dissipative Ising Machine Driven by Colored Gaussian Noise

Liao

Sarker

et al. 2022

Advcd Theory and Sims

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Gain‐dissipative Ising machines (GIMs) are a type of quantum analog equipment that can rapidly determine the optimal solution for combinatorial optimization problems. When the noise intensity is significantly lower than the fixed point of the system, the performance of a GIM is not influenced by the fluctuation of the noise intensity. However, the noise in this study is limited to Gaussian white noise. The influence of prevalent colored noise on GIMs has not been researched. In this study, the influence of common‐colored noise on the performance of GIMs is numerically investigated. The results of a domain clustering dynamics analysis reveal that red noise can better suppress the generation of the noise‐induced irregular temporary domain. Furthermore, several prevalent MAXCUT problem topologies, including the Moebius ladder, random Moebius ladder, and 2D random lattice, are adopted as test benchmarks. The results reveal that GIMs influenced by white, blue, and violet noise perform better at low‐intensity noise condition. In contrast, pink and red noise‐injected GIMs demonstrate higher performances when applied to MAXCUT topologies with both ferromagnetic and antiferromagnetic connections under larger noise intensity conditions. This indicates that the noise dispersion can be used as an additional hyperparameter to optimize the performance of GIMs.

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Coherent detection stochastic resonance assisted biomagnetometer for measuring magnetocardiography at room temperature

Cited by 14 publications

References 36 publications

Non-invasive cuff-less blood pressure estimation using a hybrid deep learning model

Non-invasive cuff-less blood pressure estimation using a hybrid deep learning model

Extremely low-frequency magnetic spectrum measurement method based on the NV center in diamond

Quantum Analog Annealing of Gain‐Dissipative Ising Machine Driven by Colored Gaussian Noise

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