Review of sensors for remote patient monitoring

Remote patient monitoring (RPM) of physiological measurements can provide an efficient method and high quality care to patients. The physiological signals measurement is the initial and the most important factor in RPM. This paper discusses the characteristics of the most popular sensors, which are used to obtain vital clinical signals in prevalent RPM systems. The sensors discussed in this paper are used to measure ECG, heart sound, pulse rate, oxygen saturation, blood pressure and respiration rate, which are treated as the most important vital data in patient monitoring and medical examination

Development of a PC interfaced blood pressure meter (E-BPMS)

Blood pressure is one of the fundamental vital signs, and its measurement is of great importance to medical professionals and the general public alike. Nowadays, there are several types of blood pressure meter available manufactured from various companies. In order to meet the demand on telemedicine and technology advancement, a new form of blood pressure meter is desirable. This prototype of blood pressure meter is interfaced with a personal computer (PC) which able to simulate the measurement process in real time. The proposed system was named e-BPMS (Electronic Blood Pressure Measurement System) suggests the usage of both hardware and software in determining blood pressure reading. Hardware elements operate on oscillometric principle which gives the results in terms of systolic, diastolic and MAP (Mean Arterial Pressure). Furthermore, these results will be presented and simulated on the software. The e-BPMS interface was developed by using Visual Basic 6.0 language which highlights the user friendly attributes. Moreover, the simulated waveform will evaluate the blood pressure and gives the blood pressure value. This application shows significant improvement on the overall performance and gives reliable results. The framework used to design e-BPMS is easy to understand and it can be extended further to endorse new application area

Signal processing methodologies for an acoustic fetal heart rate monitor

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use

Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

Prevention of drowsy driving by means of warning sound

Traffic accidents occur due to inattentive driving such as drowsy driving. A variety of support systems that make an attempt to prevent inattentive driving are under development. The development of a system to prevent drowsy driving using auditory or tactile alarm system is undertaken. It is essential to detect the low arousal state and warn drivers of such a state so that drowsy can be prevented. EEG (Electroencephalography) was used to evaluate how an arousal level degraded with time for eight participants under a low arousal level. Mean power frequency (MPF) was calculated to evaluate an arousal level. The value of MPF was compared between high and low arousal levels. The difference of arousal effect among four warning sounds was examined. As a result, there was no significant difference of arousal effect among four alarm sounds. The alarm sound was found to temporarily heighten participants' arousal level