The aim of this paper is to investigate control strategies for functional electrical simulation (FES) cycling, with particular focus on the generation of stimulation intensities for multiple muscles, without any predetermined stimulation pattern. The control system is developed by imitating the biological neuronal control system. Specifically, the control signal on the level of joint torque (quasi-joint torque) is generated from the feedback information of lower extremities. The quasi-joint torque is then distributed to each muscle and the muscle delay is compensated, and finally, the stimulation intensity is determined. Parameters of the control system are optimized by the genetic algorithm with cost function of energy consumption and cadence error. The proposed control system is evaluated by computer simulation. The controller generates efficient stimulation even during the muscle fatigue process and successfully continues cycling without any predetermined stimulation pattern. Moreover, the controller is robust to the parameter error in the muscle delay compensator and also to the disturbances. It is expected that the proposed method would improve the FES cycling performance and relieve patients by eliminating the experimental determination of the stimulation patterns.

Glucose concentration is closely related to the metabolic activity of cells and it is the most important substance as the energy source of a living body which plays an important role in the human body. This paper proposes an optical method that can measure the concentration of glucose. The change in glucose concentration was observed by using CIE diagram, and wavelength and purity values were detected. Also, even small changes in glucose concentration can be evaluated through mathematical modeling. This system is simple, economical, and capable of quantifying optical signals with numerical values for glucose sensing. This method can be applicable to the clinical field that examines diabetes mellitus or metabolic syndrome.

A spectrophotometer is the basic measuring equipment essential to most research activity fields requiring samples to be measured, such as physics, biotechnology and food engineering. This paper proposes a system that is able to detect sample concentration and color information by using LED and color sensor. Purity and wavelength information can be detected by CIE diagram, and the concentration can be estimated with purity information. This method is more economical and efficient than existing spectrophotometry, and can also be used by ordinary persons. This contribution is applicable to a number of fields because it can be used as a colorimeter to detect the wavelength and purity of samples.

Alcohol acts as a central nervous system depressant and falls under the category of psychoactive drugs. It has the potential to impair vital bodily functions, including cognitive alertness, muscle coordination, and induce fatigue. Taking the wheel after consuming alcohol can lead to delayed responses in emergency situations and increases the likelihood of collisions with obstacles or suddenly appearing objects. Statistically, drivers under the influence of alcohol are seven times more likely to cause accidents compared to sober individuals. Various techniques and methods for alcohol measurement have been developed. The widely used breathalyzer, which requires direct contact with the mouth, raises concerns about hygiene. Methods like chromatography require skilled examiners, while semiconductor sensors exhibit instability in sensitivity over measurement time and has a short lifespan, posing structural challenges. Non-dispersive infrared analyzers face structural limitations, and in-vehicle air detection methods are susceptible to external influences, necessitating periodic calibration. Despite existing research and technologies, there remain several limitations, including sensitivity to external factors such as temperature, humidity, hygiene consideration, and the requirement for periodic calibration. Hence, there is a demand for a novel technology that can address these shortcomings. This study delved into the near-infrared wavelength range to investigate optimal wavelengths for non-invasively measuring blood alcohol concentration. Furthermore, we conducted an analysis of the optical characteristics of biological substances, integrated these data into a mathematical model, and demonstrated that alcohol concentration can be accurately sensed using the first-order modeling equation at the optimal wavelength. The goal is to minimize user infection and hygiene issues through a non-destructive and non-invasive method, while applying a compact spectrometer sensor suitable for button-type ignition devices in vehicles. Anticipated applications of this study encompass diverse industrial sectors, including the development of non-invasive ignition button-based alcohol prevention systems, surgeon’s alcohol consumption status in the operating room, screening heavy equipment operators for alcohol use, and detecting alcohol use in close proximity to hazardous machinery within factories.