High-precision spectra captured by a spectral camera and suppression of their nonlinearity.

The high sensitivity of photoplethysmography (PPG) spectral signals provides conditions for extracting dynamic spectra carrying nonlinear information. By the idea of spatial conversion precision, this paper uses a spectral camera to collect highly sensitive spectral data of 24 wavelengths and proposes a method for extracting dynamic spectra of three different optical path lengths and their joint modeling. In the experiment, the models of the red blood cells and white blood cells established by the joint spectra achieved good results, with the correlation coefficients above 0.77. This study has great significance for achieving high-precision noninvasive quantitative analysis of human blood components.

A joint evaluation method of dynamic spectrum extraction methods for non-invasive blood component measurement based on stability coefficient, data point adoption rate, and smoothness of the spectrum.

BACKGROUND AND OBJECTIVE: Dynamic spectrum (DS) theory is a new non-invasive detection method of human blood components that can theoretically eliminate individual differences in static tissues and the influence of other measurement conditions to achieve blood component analysis with high precision. In order to obtain a high signal-to-noise ratio dynamic spectrum, researchers have proposed various dynamic spectrum extraction methods. METHODS: In this article, we propose three indexes: stability coefficient (SC), data point adoption rate (DAR), and smoothness of spectrum (SS). These solve the difficulty in evaluating different dynamic spectrum extraction methods without establishing mathematical models. RESULTS: In this study, DS is extracted using different dynamic spectrum extraction methods from the experimental data of 677 volunteers. Then three indexes, SC, DAR, and SS, are calculated. The trends in the scatter plot of the relationship between the three indexes and modeling results of hemoglobin, red blood cell count, and white blood cell count and the related coefficients demonstrate that SC, DAR, and SS are feasible and effective for evaluation. The results show that the root mean square extraction performs best, while the peak-to-peak value and the fast Fourier transform extraction are the worst. CONCLUSIONS: This study proposes feasible and effective indexes for evaluating dynamic spectrum extraction methods, providing a possibility for further research on high-precision dynamic spectrum extraction methods.

Non-contact cardiopulmonary signal monitoring based on magnetic eddy current induction.

The magnetic eddy current induction method has become an excellent solution for building home cardiopulmonary monitoring systems because of its non-contact and unobtrusive characteristics, but it has problems such as low precision and complex extraction of cardiopulmonary signals. Therefore, this paper designs a magnetic eddy current sensing system based on a Field Programmable Gate Array that can realize simultaneous real-time monitoring of cardiopulmonary signals. This system adopts a magnetic eddy current sensor design scheme that can improve the amount of cardiopulmonary information in the sensing signal. In addition, it uses a signal acquisition scheme that combines an inductance-to-digital converter (LDC) and oversampling technology to improve the resolution and signal-to-noise ratio of the sensing signal. Moreover, an optimized adaptive discrete wavelet transform algorithm is proposed in this system, which can realize the effective separation and extraction of cardiopulmonary signals in different respiration states. Comparing this system with the medical monitor, the cardiopulmonary signals obtained by the two have good consistency in the time-frequency domain. Under low motion, respiration rate and heart rate detected by this system are within the confidence interval of the 95% limit of agreement; the relative errors are less than 2.63% and 1.37%, respectively; and the accuracy rates are greater than 99.30% and 99.60%, respectively. In addition, an experiment with an asthmatic patient showed that the system still has good detection performance under pathological conditions and can monitor abnormal conditions such as coughing.

Non-invasive detection of total bilirubin based on multi-wavelength PPG signal.

BACKGROUND AND OBJECTIVE: Abnormal bilirubin metabolism can result in various liver function disorders. Current clinical practice for bilirubin level detection involves invasive blood collection from patients, which is time-consuming, painful, and poses infection risks. Thus, there is a pressing need for non-invasive bilirubin detection methods. This study aims to develop a non-invasive total serum bilirubin(TSB) detection method in humans based on multi-wavelength photoplethysmography (PPG) signals. METHODS: The experimental instrument includes a light source and a spectrometer. PPG signals are collected from the subjects' fingers, and the samples are selected based on the PPG deviation degree screening method. The absorption spectrum of blood is extracted from the PPG signal using dynamic spectroscopy. Finally, locally developed software calculates the total bilirubin value. The instrument is modeled and validated according to the clinical-biochemical test values. RESULTS: The results of the prediction set (correlation coefficient is 0.91, RSMEP is 2.32 umol/L, average absolute error percentage is 9.3%) show that our method has a strong correlation with the detection results of clinical-biochemical analysis instruments. The Bland-Altman test showed that the device deviated from the data detected by biochemical methods in the clinic with a mean deviation of about 0.12 umol/L and a 95% confidence interval between -2.95 umol/L and 2.7 umol/L. CONCLUSIONS: This study's non-invasive bilirubin detection method has high accuracy, which can meet the needs of continuous non-invasive total bilirubin detection in clinical practice.

Non-invasive detection of haemoglobin, platelets, and total bilirubin using hyperspectral cameras.

Hyperspectral imaging has emerged as a promising high-resolution and real-time imaging technology with potential applications in medical diagnostics and surgical guidance. In this study, we developed a high-speed hyperspectral camera by integrating a Fabry-Perot cavity filter on each CMOS pixel. We used it to non-invasively detect three blood components (haemoglobin, platelet, and total bilirubin). Specifically, we acquired transmission images of the subject's fingers, extracted spectral signals at each wavelength, and used dynamic spectroscopy to obtain non-invasive blood absorption spectra. The prediction models were established using the PLSR method and were modelled and validated based on the standard clinical-biochemical test values. The experimental results demonstrated excellent performance. The best predictions were obtained for haemoglobin, with a high related coefficient (R) of 0.85 or more in both the calibration and prediction sets and a mean absolute percentage error (MAPE) of only 5.7%. The results for total bilirubin were also ideal, with R values exceeding 0.8 in both sets and a MAPE of 10.6%. Although the prediction results for platelets were slightly less satisfactory, the error was still less than 15%, indicating that the results were also acceptable. Overall, our study highlights the potential of hyperspectral imaging technology for the development of portable and affordable devices for blood analysis, which can be used in various settings.

A modulation method that can improve the performance of LED multi-spectral imaging.

In the LED multi-spectral imaging (LEDMSI) system, modulation by using the square wave frequency division with frequency ratio of 2 can improve the image quality and acquisition speed, but it will occupy a wide frequency band. Moreover, since there is a simultaneous change in the state of multiple signals when this method is used, it will lead to serious ringing phenomenon or insufficient slew rate and affect the quality of multi-spectral images. To solve the above problems, this paper proposes a modulation method for LEDMSI system, which uses n same frequency square wave signals with different phases as the carrier signals. Comparing the multi-spectral images modulated by the proposed method with the multi-spectral images modulated by the traditional method, experimental results show that the quality of the image modulated by the proposed method is higher, which indicates that the proposed method is of great significance to improve the performance of LEDMSI system.

A method for obtaining dynamic spectrum based on the proportion of multi-wavelength PPG waveform and applying it to noninvasive detection of human platelet content.

Dynamic spectroscopy (DS) theoretically eliminates individual differences and the impact of measurement conditions on accuracy and can achieve high-precision noninvasive blood component analysis. To further improve the extraction quality of DS, this paper proposes a photoplethysmography (PPG) signal waveform proportion extraction method, which realizes the extraction of DS by calculating the proportion coefficient between PPG waveforms. To verify the effectiveness of our method, the transmission spectra of 146 volunteers' fingers and the true value of platelet content (wavelength 600-1100 nm, platelet content range 32 × 109/L-512 × 109/L) were collected. Then the DS was extracted by the single-trail method and this method, and the prediction model is established by PLS. The experimental data showed, compared with the single-trail method, that the modeling effect of the PPG waveform proportion method is significantly improved, the Rc increased 9.61%, the RMSEc decreased 31.56%, the MAPc decreased from 12 to 6%, and the Rp increased 42.92%, the RMSEP reduced 24.39%, and MAPp decreased from 13 to 11%. The results show that the PPG waveform proportion method proposed in this paper has a higher model correlation coefficient and lower prediction error, significantly improves the extraction quality of DS, further improves the accuracy of noninvasive blood component quantitative analysis, and helps to promote the application process of noninvasive detection of blood components.