Improvement of the Accuracy in the Identification of Coronary Artery Disease Combining Heart Sound Features.

Most researchers use features of diastolic murmurs to identify coronary artery disease. However, the diastolic murmurs of coronary artery disease are usually very weak and are easily contaminated by noise and valvular murmurs. Therefore, the diagnostic accuracy of coronary artery disease when only using diastolic murmurs is not well. An algorithm for improving the accuracy in the identification of coronary artery disease by combining the features of the first heart sound and diastolic murmurs was proposed. Firstly, a first heart sound feature extraction algorithm was used to identify coronary artery disease from noncoronary artery disease. Secondly, the Empirical Wavelet Transform algorithm was used to decompose the diastolic heart sound into three modes, and the spectral energy of each mode was calculated to distinguish coronary artery disease from noncoronary artery disease. Then, the features of the fist heart sound, the second diastolic spectral energy, and the parameter P3, which was used to discriminate the diastolic murmurs in coronary artery disease and in valvular disease, were combined together to improve the diagnostic accuracy of coronary artery disease. The comparison experiment results show that the accuracy of the proposed algorithm is superior to some state-of-the-art methods when they are used to diagnose coronary artery disease.

A Shared-Electrode and Nested-Tube Structure Triboelectric Nanogenerator for Motion Energy Harvesting.

Triboelectric nanogenerators with the function of harvesting human motion energy have attracted wide attention. Here, we demonstrate a shared-electrode and nested-tube structure triboelectric nanogenerator (SNTN) for harvesting human motion energy. The design of the SNTN employs flexible silicone rubber as the negative friction material and Ni-coated polyester conductive textile as the positive friction material and the electrode material. The entire structure consists of an inner triboelectric unit and an outer triboelectric unit. The inner triboelectric unit is formed by a hollow inner tube and a hollow middle tube, while the hollow middle tube and a hollow outer tube constitute the outer triboelectric unit. The hollow middle tube is used as the shared tube, and the electrode in the middle tube is used as the shared electrode of the two triboelectric units. Our research demonstrates that the output performance of the SNTN was improved significantly compared with a single triboelectric unit due to the cooperation of the two triboelectric units. When the SNTN is pressed by 300 N external force, output open-circuit voltage of 180 V and output short-circuit current of 8.5 µA can be obtained. The output electrical energy can light up 31 light-emitting diodes (LEDs) connected serially (displaying "XZTC") and can drive a digital clock after rectifying storage, which shows application prospects in the field of illuminating devices and portable electronics.

Core-shell coaxially structured triboelectric nanogenerator for energy harvesting and motion sensing.

Converting sustainable human motion energy into electric energy has become an urgent task for the advancement of next-generation wearable and portable electronics. Herein, a core-shell coaxially structured triboelectric nanogenerator (CSTN) was fabricated by inserting an inner hollow circular tube into an outer hollow circular tube, and a gasbag is constructed within the space between the inner and outer tubes. Both Ni-coated polyester conductive textile and the conductive silicone rubber were used as effective electrode materials. The CSTN has excellent properties, including flexibility, light weight, sustainability and biological compatibility due to its unique structural design and materials selection. The CSTN can convert various forms of human motion energy, such as pressing, bending and twisting motion, into electric energy. A high short-circuit current of 11 µA and an open-circuit voltage of 380 V can be obtained from a CSTN with a length of 6 cm, corresponding to a high peak power of 1.638 mW at a load resistance of about 10 MΩ. When six such CSTNs are connected in parallel and placed under shoes, the electric energy output by normal walking can light up 60 LEDs connected serially and power up a competition-timer. The device can also sense different bending angles or twisting angles according to its signal outputs under different deformation angles. This study indicates the promising application prospects of the CSTN for next-generation devices, including self-powered illuminating devices, portable electronics, body motion sensing and health monitoring.