Efficient portable wearable sweat sensors allow the long-term monitoring of changes in the status of biomarkers in sweat, which can be useful in diagnosis, medication, and nutritional assessment. In this study, we designed and tested a wireless, battery-free, flexible, self-pumping sweat-sensing system that simultaneously tracks levodopa and vitamin C levels in human sweat and detects body temperature. The system includes a microfluidic chip with a self-driven pump and anti-reflux valve, a flexible wireless circuit board, and a purpose-designed smartphone app. The microfluidic chip is used for the efficient collection of sweat and the drainage of excess sweat. The dual electrochemical sensing electrodes in the chip are modified with functional materials and appropriate enzymatic reagents, achieving excellent selectivity and stability. The sensitivities of the levodopa sensor and the vitamin C sensor are 0.0073 and 0.0018 μA·μM⁻¹, respectively, and the detection correlation coefficients of both exceed 0.99. Both sensors have a wide linear detection range of 0–100 and 0–1000 μM, respectively, and low detection limits of 0.28 and 17.9 μM, respectively. The flexible wireless circuit board is equipped with the functions of wireless charging, electrical signal capture and processing, and wireless transmission. The data recorded from each sensor are displayed on a smartphone via a self-developed app. A series of experimental results confirmed the reliability of the sweat-sensing system in noninvasively monitoring important biomarkers in the human body and its potential utility in the comprehensive assessment of biological health.

Active tuberculosis infection is a major health concern in the world. Each year, millions of people die of tuberculosis, especially in third-world countries. Though the World Health Organization has recently reported the rate of mortality by this disease is declining by 3% yearly, active tuberculosis infection is still endangering human health seriously. In addition, there are many people who have a latent tuberculosis infection, and these people do not seek treatment because they have no clinical symptoms. It is true that current specific laboratory examination approaches are capable of diagnosing active tuberculosis infection promptly and accurately. But sensitivity and specificity of current diagnostic approaches are at a low level. However, the development of new nanomaterials allows more scientists to combine diagnostic methods with nanotechnology. Recently, a novel Nanodisk mass spectrometry method has been reported. Mycobacterium tuberculosis-specific peptides are enriched using an antibody-conjugated nanodisk, allowing for rapid, quantitative detection of the serum-specific antigen for active tuberculosis infection. This method overcomes the shortcomings of poor sensitivity and long turnaround time associated with current diagnostic approaches. This review discusses the current status and progress of specific laboratory examination methods of active tuberculosis diagnosis and compares the newest diagnostic techniques.

In order to achieve fast and quantitative detection of fluorescence immunochromatographic chip, a rapid detection system based on smartphone has been developed. In this system, fluorescent signal from quantum dots (QDs) on lateral flow test strips (LFTSs) can be accurately extracted, and the system also can calculate the concentration of the analyte. The method of extraction and recognition of fluorescence signal intensity can be applied to different fluorescent chip detection systems. Based on the fluorescence tomography chip image, a specific program is used for image acquisition, processing and data handling. The Sobel operator algorithm was used in the software，which improved greatly the ability of distinguishing between the test area and the background boundary information. Extracting the components from the red format of the fluorescent strips，the high-signal intensity and sensitivity were achieved. The simulation results show that the proposed method can be applied to the detection system of fluorescence immunochromatographic chip. The experimental results show that the signal intensity has a good correlation with the concentration of immunoassay, which indicates the detection system can extract the intensity of fluorescence signal of the chip.

The key of disease diagnosis by lateral flow strip is the acquirer of color signal data. We stablished a CCD based lateral flow strip detector. The detector is designed for the low density detection, and it is suitable for point-of-care diagnostics. We established the matched software and achieve basic functions. Through the image processing, like image filtering to reduce the random noise, gray-scale transformation and binarization to get the threshold of the color signal, edge detection to identify effective information, quantitative reading to give the result of diagnosis and so on. The sensitivity of this detector is sufficient for many parameters of clinical relevance.