Adaptive filtering methods based on least-mean-square (LMS) error criterion have been commonly used in auscultation to reduce ambient noise. For non-Gaussian signals containing pulse components, such methods are prone to weights misalignment. Unlike the commonly used variable step-size methods, this paper introduced linear preprocessing to address this issue. The role of linear preprocessing in improving the denoising performance of the normalized least-mean-square (NLMS) adaptive filtering algorithm was analyzed. It was shown that, the steady-state mean square weight deviation of the NLMS adaptive filter was proportional to the variance of the body sounds and inversely proportional to the variance of the ambient noise signals in the secondary channel. Preprocessing with properly set parameters could suppress the spikes of body sounds, and decrease the variance and the power spectral density of the body sounds, without significantly reducing or even with increasing the variance and the power spectral density of the ambient noise signals in the secondary channel. As a result, the preprocessing could reduce weights misalignment, and correspondingly, significantly improve the performance of ambient-noise reduction. Finally, a case of heart-sound auscultation was given to demonstrate how to design the preprocessing and how the preprocessing improved the ambient-noise reduction performance. The results can guide the design of adaptive denoising algorithms for body sound auscultation.
We conducted this study to explore the influence of the ocular residual aberrations changes on contrast sensitivity (CS) function in eyes undergoing orthokeratology using adaptive optics technique. Nineteen subjects' nineteen eyes were included in this study. The subjects were between 12 and 20 years (14.27±2.23 years) of age. An adaptive optics (AO) system was adopted to measure and compensate the residual aberrations through a 4-mm artificial pupil, and at the same time the contrast sensitivities were measured at five spatial frequencies (2,4,8,16, and 32 cycles per degree).The CS measurements with and without AO correction were completed. The sequence of the measurements with and without AO correction was randomly arranged without informing the observers. A two-interval forced-choice procedure was used for the CS measurements. The paired t-test was used to compare the contrast sensitivity with and without AO correction at each spatial frequency. The results revealed that the AO system decreased the mean total root mean square (RMS) from 0.356 μm to 0.160 μm(t=10.517, P＜0.001), and the mean total higher-order RMS from 0.246 μm to 0.095 μm(t=10.113, P＜0.001). The difference in log contrast sensitivity with and without AO correction was significant only at 8 cpd (t=-2.51, P=0.02). Thereby we concluded that correcting the ocular residual aberrations using adaptive optics technique could improve the contrast sensitivity function at intermediate spatial frequency in patients undergoing orthokeratology.
The paper introduces a training system for foot ulcer patients based on three axis accelerometer, which uses three axis accelerometer and Apple mobile phone platform to guide foot ulcer patients to carry out a variety of lower limb muscle tissues training. The acceleration values of three directions for the foot training is obtained by analog-to-digital conversion and transmitted to the Apple mobile phone via its Bluetooth low energy. The Apple mobile phone accomplishes acceleration data preprocessing, numerical filtering and adaptive dual-threshold processing by our developed application program, so as to achieve the purpose of foot gesture recognition. The experimental result shows that the design can effectively present the training situation and effect of patients, encourage patients to adhere to the training, and provide some reference data for doctors and patients.
The mechanical behavior modeling of human soft biological tissues is a key issue for a large number of medical applications, such as surgery simulation, surgery planning, diagnosis, etc. To develop a biomechanical model of human soft tissues under large deformation for surgery simulation, the adaptive quasi-linear viscoelastic (AQLV) model was proposed and applied in human forearm soft tissues by indentation tests. An incremental ramp-and-hold test was carried out to calibrate the model parameters. To verify the predictive ability of the AQLV model, the incremental ramp-and-hold test, a single large amplitude ramp-and-hold test and a sinusoidal cyclic test at large strain amplitude were adopted in this study. Results showed that the AQLV model could predict the test results under the three kinds of load conditions. It is concluded that the AQLV model is feasible to describe the nonlinear viscoelastic properties of in vivo soft tissues under large deformation. It is promising that this model can be selected as one of the soft tissues models in the software design for surgery simulation or diagnosis.
Diabetic retinopathy is a common blinding complication in diabetic patients. Compared with conventional fundus color photography, fundus fluorescein angiography can dynamically display retinal vessel permeability changes, offering unique advantages in detecting early small lesions such as microaneurysms. However, existing intelligent diagnostic research on diabetic retinopathy images primarily focuses on fundus color photography, with relatively insufficient research on complex lesion recognition in fluorescein angiography images. This study proposed an adaptive multi-label classification model (D-LAM) to improve the recognition accuracy of small lesions by constructing a category-adaptive mapping module, a label-specific decoding module, and an innovative loss function. Experimental results on a self-built dataset demonstrated that the model achieved a mean average precision of 96.27%, a category F1-score of 91.21%, and an overall F1-score of 94.58%, with particularly outstanding performance in recognizing small lesions such as microaneurysms (AP = 1.00), significantly outperforming existing methods. The research provides reliable technical support for clinical diagnosis of diabetic retinopathy based on fluorescein angiography.
In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.
The Wireless Body Area Network (WBAN) is a key part of the wearable monitoring technologies, which has many communication technologies to choose from, like Bluetooth, ZigBee, Ultra Wideband, and Wireless Human Body Communication (WHBC). As for the WHBC developed in recent years, it is worthy to be further studied. The WHBC has a strong momentum of growth and a natural advantage in the formation of WBAN. In this paper, we first briefly describe the technical background of WHBC, then introduce theoretical model of human-channel communication and digital transmission machine based on human channel. And finally we analyze various of the interference of the WHBC and show the AFH (Adaptive Frequency Hopping) technology which can effectively deal with the interference.
Objective To investigate the predictive value of mechanical power (MP) in the weaning outcome of adaptive mechanical ventilation plus intelligent trigger (AMV+IntelliCycle, simply called AMV) mode for acute respiratory distress syndrome (ARDS) patients. Methods From November 2019 to March 2021, patients with mild to moderate ARDS who were treated with invasive mechanical ventilation in the intensive care unit of the First Affiliated Hospital of Jinzhou Medical University were divided into successful weaning group and failed weaning group according to the outcome of weaning. All patients were treated with AMV mode during the trial. The MP, oral closure pressure (P0.1), respiratory rate (RR) and tidal volume (VT) of the two groups were compared 30 min and 2 h after spontaneous breathing trial (SBT). The correlation between 30 min and 2 h MP and shallow rapid respiratory index (RSBI) was analyzed by Pearson correlation. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of 30 min MP in ARDS patients with AMV mode weaning failure. Results Sixty-eight patients were included in the study, 49 of them were successfully removed and 19 of them failed. There was no statistical significance in age, gender, body mass index, oxygenation index, acute physiology and chronic health evaluation Ⅱ score, reasons for mechanical ventilation (respiratory failure, sepsis, intracranial lesions, and others) between the two groups (all P>0.05). The MP, P0.1 and RR at SBT 30 min and 2 h of the successful weaning group was lower than those of the failed weaning group (all P<0.05), but the VT of the successful weaning group was higher than the failed weaning group (all P<0.05). There was a significant relation between the MP at SBT 30 min and 2 h and RSBI (r value was 0.640 and 0.702 respectively, both P<0.05). The area under ROC curve of MP was 0.674, 95% confidence interval was 0.531 - 0.817, P value was 0.027, sensitivity was 71.73%, specificity was 91.49%, positive predictive value was 0.789, negative predictive value was 0.878, optimal cutoff value was 16.500. The results showed that 30 min MP had a good predictive value for the failure of weaning in AMV mode in ARDS patients. Conclusion MP can be used as an accurate index to predict the outcome of weaning in ARDS patients with AMV mode.
Image-guided radiation therapy using magnetic resonance imaging (MRI) is a new technology that has been widely studied and developed in recent years. The technology combines the advantages of MRI imaging, and can offer online real-time tracking of tumor and adjacent organs at risk, as well as real-time optimization of radiotherapy plan. In order to provide a comprehensive understanding of this technology, and to grasp the international development and trends in this field, this paper reviews and summarizes related researches, so as to make the researchers and clinical personnel in this field to understand recent status of this technology, and carry out corresponding researches. This paper summarizes the advantages of MRI and the research progress of MRI linear accelerator (MR-Linac), online guidance, adaptive optimization, and dosimetry-related research. Possible development direction of these technologies in the future is also discussed. It is expected that this review can provide a certain reference value for clinician and related researchers to understand the research progress in the field.
In order to get the adaptive bandwidth of mean shift to make the tumor segmentation of brain magnetic resonance imaging (MRI) to be more accurate, we in this paper present an advanced mean shift method. Firstly, we made use of the space characteristics of brain image to eliminate the impact on segmentation of skull; and then, based on the characteristics of spatial agglomeration of different tissues of brain (includes tumor), we applied edge points to get the optimal initial mean value and the respectively adaptive bandwidth, in order to improve the accuracy of tumor segmentation. The results of experiment showed that, contrast to the fixed bandwidth mean shift method, the method in this paper could segment the tumor more accurately.