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Cardiorespiratory endurance refers to the ability of the heart and lungs to deliver oxygen to working muscles during continuous physical activity, which is an important indicator of physical health. Cardiorespiratory endurance is typically measured in the laboratory by maximum oxygen uptake (VO2max) which is not a practical method for real-life use. Given the relative difficulty in measuring oxygen consumption directly, we can estimate cardiorespiratory endurance on the basis of heart beat. In this paper, we proposed a fuzzy system based on the human heart rate to provide an effective cardiorespiratory endurance training program and the evaluation of cardiorespiratory endurance levels. Trainers can respond correctly with the help of a smart fitness app to obtain the desired training results and prevent undesirable events such as under-training or over-training. The fuzzy algorithm, which is built for the Android mobile phone operating system receives the resting heart rate (RHR) of the participants via Bluetooth before exercise to determine the suitable training speed mode of a treadmill for the individual. The computer-based fuzzy program takes RHR and heart rate recovery (HRR) after exercise as inputs to calculate the cardiorespiratory endurance level. The experimental results show that after 8 weeks of exercise training, the RHR decreased by an average of 11%, the HRR increased by 51.5%, and the cardiorespiratory endurance evaluation level was also improved. The proposed system can be combined with other methods for fitness instructors to design a training program that is more suitable for individuals.

Small molecule compounds are necessary to detect with high sensitivity since they may cause a strong effect on the human body even in small concentrations. But existing methods used to evaluate small molecules in blood are inconvenient, costly, time-consuming, and do not allow for portable usage. In response to these shortcomings, we introduce a complementary metal-oxide-semiconductor biomicroelectromechanical system (cMoS BioMeMS) based piezoresistive membrane-bridge (MB) sensor for detecting small molecule (phenytoin) concentrations as the demonstration. Phenytoin is one of anticonvulsant drugs licensed for the management of seizures, which has a narrow therapeutic window hence a level of concentration monitoring was needed. The MB sensor was designed to enhance the structural stability and increase the sensitivity, which its signal response increased 2-fold higher than that of the microcantilever-based sensor. The MB sensor was used to detect phenytoin in different concentrations from 5 to 100 μg/mL. The limit of detection of the sensor was 4.06 ± 0.15 μg/mL and the linear detection range was 5-100 μg/mL, which was within the therapeutic range of phenytoin concentration (10-20 μg/mL). Furthermore, the MB sensor was integrated with an on-chip thermal effect eliminating modus and a reaction tank on a compact chip carrier for disposable utilization. The required amount of sample solution was only 10 μL and the response time of the sensor was about 25 minutes. The nano-mechanical MB sensing method with thermal effect compensation is specific, sensitive, robust, affordable and well reproducible; it is, therefore, an appropriate candidate for detecting small molecules.

In recent years, the development of green energy sources, such as fuel cell, biomass energy, solar energy, and tidal energy, has become a popular research subject. This study aims at a flexible four-in-one microsensor, which can be embedded in the proton exchange membrane fuel cell (PEMFC) for real-time microscopic diagnosis so as to assist in developing and improving the technology of the fuel cell. Therefore, this study uses micro-electro-mechanical systems (MEMS) technology to integrate a micro humidity sensor, micro pH sensor, micro temperature sensor, and micro voltage sensor into a flexible four-in-one microsensor. This flexible four-in-one microsensor has four functions and is favorably characterized by small size, good acid resistance and temperature resistance, quick response, and real-time measurement. The goal was to be able to put the four-in-one microsensor in any place for measurement without affecting the performance of the fuel cell.

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