Using electroencephalogram (EEG) signal to control external devices has always been the research focus in the field of brain-computer interface (BCI). This is especially significant for those disabilities who have lost capacity of movements. In this paper, the P300-based BCI and the microcontroller-based wireless radio frequency (RF) technology are utilized to design a smart home control system, which can be used to control household appliances, lighting system, and security devices directly. Experiment results showed that the system was simple, reliable and easy to be populirised.
Brain-computer interface (BCI) system is a system that achieves communication and control among humans and computers and other electronic equipment with the electroencephalogram (EEG) signals. This paper describes the working theory of the wireless smart home system based on the BCI technology. We started to get the steady-state visual evoked potential (SSVEP) using the single chip microcomputer and the visual stimulation which composed by LED lamp to stimulate human eyes. Then, through building the power spectral transformation on the LabVIEW platform, we processed timely those EEG signals under different frequency stimulation so as to transfer them to different instructions. Those instructions could be received by the wireless transceiver equipment to control the household appliances and to achieve the intelligent control towards the specified devices. The experimental results showed that the correct rate for the 10 subjects reached 100%, and the control time of average single device was 4 seconds, thus this design could totally achieve the original purpose of smart home system.
A digital system for bioimpedance and electrical impedance tomography (EIT) measurement controlled by an ATmega16 microcontroller was constructed in our laboratory. There are eight digital electrodes using AD5933 to measure the impedance of the targets, and the data is transmitted to the computer wirelessly through nRF24L01. The structure of the system, circuit design, system testing, vitro measurements of animals' tissues and electrical impedance tomography are introduced specifically in this paper. The experimental results showed that the system relative error was 0.42%, and the signal noise ratio was 76.3 dB. The system not only can be used to measure the impedance by any two electrodes within the frequency of 1-100 kHz in a sweep scanning, but also can reconstruct the images of EIT. The animal experiments showed that the data was valid and plots were fitting with Cole-Cole theory. The testing verified the feasibility and effectiveness of the system. The images reconstructed of a salt-water tank are satisfactory and match with the actual distribution of the tank. The system improves the effectiveness of the front-end measuring signal and the stability of the system greatly.
The capsule endoscope swallowed from the mouth into the digestive system can capture the images of important gastrointestinal tract regions. It can compensate for the blind spot of traditional endoscopic techniques. It enables inspection of the digestive system without discomfort or need for sedation. However, currently available clinical capsule endoscope has some limitations such as the diagnostic information being not able to correspond to the orientation in the body, since the doctor is unable to control the capsule motion and orientation. To solve the problem, it is significant to track the position and orientation of the capsule in the human body. This study presents an AC excitation wireless tracking method in the capsule endoscope, and the sensor embedded in the capsule can measure the magnetic field generated by excitation coil. And then the position and orientation of the capsule can be obtained by solving a magnetic field inverse problem. Since the magnetic field decays with distance dramatically, the dynamic range of the received signal spans three orders of magnitude, we designed an adjustable alternating magnetic field generating device. The device can adjust the strength of the alternating magnetic field automatically through the feedback signal from the sensor. The prototype experiment showed that the adjustable magnetic field generating device was feasible. It could realize the automatic adjustment of the magnetic field strength successfully, and improve the tracking accuracy.
Quantitative assessment of the symptoms of Parkinson's disease is the key for precise diagnosis and treatment and essential for long term management over years. The challenges of quantitative assessment on Parkinson's disease are rich information, ultra-low load, long term and large range monitoring in free-moving condition. In this paper, we developed wearable devices with multiple sensors to monitor and quantify the movement symptoms of Parkinson's disease. Five wearable sensors were used to record motion signals from bilateral forearms, legs and waist. A local area network based on low power Wi-Fi technology was built for long distance wireless data transmission. A software was developed for signal recording and analyzing. The size of each sensor was 39 mm×33 mm×16 mm and the weight was 18g. The sensors were rechargeable and able to run 12 hours. The wireless transmission radius is about 45 m. The wearable devices were tested in patients and normal subjects. The devices were reliable and accurate for movement monitoring in hospital.
To achieve continuously physiological monitoring on hospital inpatients, a ubiquitous and wearable physiological monitoring system SensEcho was developed. The whole system consists of three parts: a wearable physiological monitoring unit, a wireless network and communication unit and a central monitoring system. The wearable physiological monitoring unit is an elastic shirt with respiratory inductive plethysmography sensor and textile electrocardiogram (ECG) electrodes embedded in, to collect physiological signals of ECG, respiration and posture/activity continuously and ubiquitously. The wireless network and communication unit is based on WiFi networking technology to transmit data from each physiological monitoring unit to the central monitoring system. A protocol of multiple data re-transmission and data integrity verification was implemented to reduce packet dropouts during the wireless communication. The central monitoring system displays data collected by the wearable system from each inpatient and monitors the status of each patient. An architecture of data server and algorithm server was established, supporting further data mining and analysis for big medical data. The performance of the whole system was validated. Three kinds of tests were conducted: validation of physiological monitoring algorithms, reliability of the monitoring system on volunteers, and reliability of data transmission. The results show that the whole system can achieve good performance in both physiological monitoring and wireless data transmission. The application of this system in clinical settings has the potential to establish a new model for individualized hospital inpatients monitoring, and provide more precision medicine to the patients with information derived from the continuously collected physiological parameters.
Wireless power transfer (WPT) is a new power transmission way, which can be widely used in electric vehicles and other fields. Its electromagnetic environment must be analyzed to ensure safe application. A low-power wireless power transfer system experimental platform was built, with 25 W receiving power and 47 kHz resonant frequency, which was used to carry out animal experiments. Treatment mice were exposed to environment of wireless power transfer system for 5 h a day and 6 days as one cycle. At the end of every cycle, learning memory behavior of mice were detected in T-shaped maze. The exposure experiment lasted for 12 weeks. Finally, immune parameters, sex hormones and part of organ physiological structure were detected. The results are as follows: as exposure time increased, memory behavior of mice did not change obviously with no statistical difference in sex hormone either (P > 0.05), the concentration of immune factors including tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6) and interleukin-1 beta (IL-1β) significantly increased (P < 0.05), and the structure of some organs showed some changes. The experimental results show that the environment of the wireless power transfer system has no effect on the memory behavior of mice, and has some effect on physiological properties of mice.