Surface electromyography (sEMG) has been widely used in the study of clinical medicine, rehabilitation medicine, sports, etc., and its endpoints should be detected accurately before analyzing. However, endpoint detection is vulnerable to electrocardiogram (ECG) interference when the sEMG recorders are placed near the heart. In this paper, an endpoint-detection algorithm which is insensitive to ECG interference is proposed. In the algorithm, endpoints of sEMG are detected based on the short-time energy and short-time zero-crossing rates of sEMG. The thresholds of short-time energy and short-time zero-crossing rate are set according to the statistical difference of short-time zero-crossing rate between sEMG and ECG, and the statistical difference of short-time energy between sEMG and the background noise. Experiment results on the sEMG of rectus abdominis muscle demonstrate that the algorithm detects the endpoints of the sEMG with a high accuracy rate of 95.6%.
Brain metastases are the most common intracranial malignant tumors in adults. Radiotherapy isa common treatment for brain metastases. In particular, stereotactic radiosurgery can control tumors well, and can significantly reduce the impact on cognitive function compared with whole brain radiation therapy. Immune checkpoint inhibitors have less toxic side effects in the treatment of patients with advanced tumors, and show good survival advantages. This article introduces radiotherapy, immunotherapy, stereotactic radiosurgery combined with immune checkpoint inhibitors for brain metastases, discusses the mechanism of stereotactic radiosurgery combined with immune checkpoint inhibitors, and its therapeutic value and research progress in brain metastases, aiming to provide a theoretical basis for the better application of stereotactic radiosurgery combined with immune checkpoint inhibitors to brain metastases.
In order to study the effect of light with different wavelengths on the motion behavior of carp robots, phototaxis experiment, anatomical experiment, light control experiment and speed measurement experiment were carried out in this study. Blue, green, yellow and red light with different wavelength were used to conduct phototaxis experiments on carp to observe their movement behavior. By dissecting the skull bones of the carp to determine the appropriate location to carry the light control device, we independently developed a light control carrying device which was suitable for any illumination intensity environment. The experiment of the light-controlled carp robots was carried out. The motion behavior of the carp robot was checked by using computer binocular stereo vision technology. The motion trajectory of the carp robot was tracked and obtained by applying kernel correlation filter (KCF) algorithm. The motion velocity of the carp robot at different wavelengths was calculated according to their motion trajectory. The results showed that carps’ sensitivity to different light changed from strong to weak in the order of blue, red, yellow and green, so that using light with different wavelengths to control the speed of the carp robot has certain laws to follow. A new method to avoid brain damage in carp robots control can be provided in this study.
Due to lack of the practical technique to measure the biomechanical properties of the ocular cornea in vivo, clinical ophthalmologists have some difficulties in understanding the deformation mechanism of the cornea under the action of physiological intraocular pressures. Using Young's theory analysis of the corneal deformation during applanation tonometry, the relation between the elasticity moduli of the cornea and the applanated corneal area and the measured and true intraocular pressures can be obtained. A new applanation technique has been developed for measuring the biomechanical properties of the ocular cornea tissue in vivo, which can simultaneously acquire the data of the applanation area and displacement of the corneal deformation as well as the exerted applanation force on the cornea. Experimental results on a rabbit's eyeball demonstrated that the present technique could be used to measure the elasticity moduli and creep properties of the ocular cornea nondestructively in vivo.
As one of the standard electrophysiological signals in the human body, the photoplethysmography contains detailed information about the blood microcirculation and has been commonly used in various medical scenarios, where the accurate detection of the pulse waveform and quantification of its morphological characteristics are essential steps. In this paper, a modular pulse wave preprocessing and analysis system is developed based on the principles of design patterns. The system designs each part of the preprocessing and analysis process as independent functional modules to be compatible and reusable. In addition, the detection process of the pulse waveform is improved, and a new waveform detection algorithm composed of screening-checking-deciding is proposed. It is verified that the algorithm has a practical design for each module, high accuracy of waveform recognition and high anti-interference capability. The modular pulse wave preprocessing and analysis software system developed in this paper can meet the individual preprocessing requirements for various pulse wave application studies under different platforms. The proposed novel algorithm with high accuracy also provides a new idea for the pulse wave analysis process.
Heritable aortic disease (HAD) is characterized by thoracic aortic aneurysm/dissection with strong genetic predisposition and high clinical phenotypic heterogeneity. HAD is one of the main causes of sudden death. Early diagnosis of this disease is difficult because of atypical clinical symptoms, leading to the deterioration of disease with the development of aortic aneurysm, aortic dissection or sudden death. Genetic testing plays an important role in the early diagnosis, standardized follow-up, screening of family members, genetic counseling and individualized treatment of HAD. This review focused on the application of genetic testing in the standardized diagnosis and treatment of HAD.
Epilepsy is characterized by abnormally synchronized firing of neuronal populations, which is presented as epileptiform spikes in neural electrical signal recordings. In order to investigate the epileptiform spikes quantitatively, we designed a new window-based algorithm to automatically detect population spikes (PS) in acute epilepsy models in rat hippocampus CA1 region, and to calculate characteristic parameters of PS. Results show that the algorithm could recognize PS waveforms directly in wideband recording signals in epilepsy models induced by 4-aminopyridine (4-AP), a potassium channel blocker, or by picrotoxin (PTX), an antagonist of γ-aminobutyric acid A-type receptor. The PS detection ratios of the two epilepsy models were 94.2%±1.6% (n=11) and 95.9%±1.9% (n=12), respectively. The false positive ratios were 3.5%±2.3% (n=11) and 4.8%±2.3% (n=12), which were significantly lower than those of the conventional threshold method. Comparisons of the PS patterns between the 4-AP model and the PTX model showed that the PS of the 4-AP model had wider waveforms and fired more dispersedly with intervals mainly in the range of 100–700 ms. The PS of the PTX model fired as Burst with a higher firing rate and with intervals mainly in the range of 2–20 ms, resulting in a larger sum of spike amplitudes per second than the 4-AP model. Thus, the synchronous firing of neuronal populations in the PTX model was more intense than that in the 4-AP model. In conclusion, the new algorithm of PS detection can correctly detect and analyze epileptiform population spikes. It provides a useful tool of data analysis for investigating the underlying mechanism of seizure generation and for evaluating new therapeutics of epilepsy.
Objective To evaluate the utility of collagen-gel droplet embedded-culture drug sensitivity test (CD-DST) in pancreatic carcinoma cell by compared with WST-8. Methods The chemosensitivity to 5-fluorouracil (5-FU), gemzar (GEM) and oxaliplatin (OXA) of pancreatic adenocarcinoma cells SW1990, PCT-3 and ASPC-1 were tested by WST-8 and CD-DST respectively. Results In a certain living cell number range (500-10 000), there was a linear correlation (r=0.991 1, P＜0.05) between the integral optical density in CD-DST and the cell number. The inhibition ratios of three kinds of cell growth tested by CD-DST were higher than those tested by WST-8 (P＜0.05). The results of drug chemosensitivity to 5-FU， GEM and OXA detected by two methods were uniform. Conclusion The CD-DST can be used to assay the drug chemosensitivity in vitro for pancreatic carcinoma.
Lung nodules are the main manifestation of early lung cancer. So accurate detection of lung nodules is of great significance for early diagnosis and treatment of lung cancer. However, the rapid and accurate detection of pulmonary nodules is a challenging task due to the complex background, large detection range of pulmonary computed tomography (CT) images and the different sizes and shapes of pulmonary nodules. Therefore, this paper proposes a multi-scale feature fusion algorithm for the automatic detection of pulmonary nodules to achieve accurate detection of pulmonary nodules. Firstly, a three-layer modular lung nodule detection model was designed on the deep convolutional network (VGG16) for large-scale image recognition. The first-tier module of the network is used to extract the features of pulmonary nodules in CT images and roughly estimate the location of pulmonary nodules. Then the second-tier module of the network is used to fuse multi-scale image features to further enhance the details of pulmonary nodules. The third-tier module of the network was fused to analyze the features of the first-tier and the second-tier module of the network, and the candidate box of pulmonary nodules in multi-scale was obtained. Finally, the candidate box of pulmonary nodules under multi-scale was analyzed with the method of non-maximum suppression, and the final location of pulmonary nodules was obtained. The algorithm is validated by the data of pulmonary nodules on LIDC-IDRI common data set. The average detection accuracy is 90.9%.
Objective To evaluate the possibility of detection mutations of 〖JP2〗multiple genes in stool for secondary screening for colorectal cancer. Methods Tumor specimens and stool samples from 40 patients with colorectal cancer and 40 normal persons were examined for mutations of p53, K-ras and APC gene by polymerase chain reaction single strand conformation polymorphism (PCR-SSCP) and silver nitrate staining. Results ①The mutation rate of p53, K-ras and APC gene in the tissues and stools of colorectal cancer respectively were 57.50%, 50.00%, 60.00% and 42.86%, 40.00%, 51.43%, and no mutations were found in normal mucosa and stool. ②The mutation ratioes between multiple gene and single gene had significant difference (P＜0.05). ③The sensitivities had no significant difference between faecal occult blood test (FOBT) and multiple gene mutations detection in the diagnosis of colorectal cancer, but the specificity of the latter was higher than FOBT (P＜0.05). Conclusion Detection of multiple gene mutations in stool is a vauble method in the secondary screening for colorectal cancer.