A healthcare edition of sporting equipment for middle-aged and elderly.

The aging phenomenon results in body organ system debilitating, which causes the balance weakening and makes a fall, fracture rate, and further medical cost to increase. The lack of exercise has been linked to increasing the incidence of hypertension, coronary artery disease, osteoporosis, degenerative arthritis, and diabetes. Chronic disease affects patients both in psychological and physiological functions which limit their daily activity. In the past, many researches pointed out that these patients can improve their balance sensation by exercise. Because of the above reasons, this research implementation forms a wireless platform of information connection system and medical data analysis. First of all, the target population in the society focuses on those elderly with the common chronic diseases, such as skeletal muscle diseases and degenerative arthritis. Using the hydraulic resist practicing equipment as the mainstay intervention can help examinee collecting the practice value and further analysis. The platform of information accords not only the data prior and after the exercise but also graphic data presentation and analysis from the medical staff members providing services in the society. It can also provide the medical unit to create data mold and a body health counselor when services in the society.

Design of a 32-channel EEG system for brain control interface applications.

This study integrates the hardware circuit design and the development support of the software interface to achieve a 32-channel EEG system for BCI applications. Since the EEG signals of human bodies are generally very weak, in addition to preventing noise interference, it also requires avoiding the waveform distortion as well as waveform offset and so on; therefore, the design of a preamplifier with high common-mode rejection ratio and high signal-to-noise ratio is very important. Moreover, the friction between the electrode pads and the skin as well as the design of dual power supply will generate DC bias which affects the measurement signals. For this reason, this study specially designs an improved single-power AC-coupled circuit, which effectively reduces the DC bias and improves the error caused by the effects of part errors. At the same time, the digital way is applied to design the adjustable amplification and filter function, which can design for different EEG frequency bands. For the analog circuit, a frequency band will be taken out through the filtering circuit and then the digital filtering design will be used to adjust the extracted frequency band for the target frequency band, combining with MATLAB to design man-machine interface for displaying brain wave. Finally the measured signals are compared to the traditional 32-channel EEG signals. In addition to meeting the IFCN standards, the system design also conducted measurement verification in the standard EEG isolation room in order to demonstrate the accuracy and reliability of this system design.