Sensors (Basel, Switzerland)
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We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). This was verified in 25 healthy subjects, aged 28 ± 5 years. The multiple linear regression (MLR) and support vector regression (SVR) models were used to examine the relationship between the SBP and the DBP ratio with ten features extracted from the oscillometric waveform envelope (OWE). ⋯ Substantial reduction in the mean and standard deviation of the blood pressure estimation errors were obtained upon artifact removal. Using the sequential forward floating selection (SFFS) approach, we were able to achieve a significant reduction in the mean and standard deviation of differences between the estimated SBP values and the reference scoring (MLR: mean ± SD = -0.3 ± 5.8 mmHg; SVR and -0.6 ± 5.4 mmHg) with only two features, i.e., Ratio2 and Area3, as compared to the conventional maximum amplitude algorithm (MAA) method (mean ± SD = -1.6 ± 8.6 mmHg). Comparing the performance of both MLR and SVR models, our results showed that the MLR model was able to achieve comparable performance to that of the SVR model despite its simplicity.
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Smartphones have been widely used recently to monitor heart rate and activity, since they have the necessary processing power, non-invasive and cost-effective sensors, and wireless communication capabilities. Consequently, healthcare applications (apps) using smartphone-based sensors have been highlighted for non-invasive physiological monitoring. In addition, several healthcare apps have received FDA clearance. ⋯ In this paper, we describe the experience of using smartphone apps with sensors in a large medical center in Korea. Among >20 apps developed in our medical center, four were extensively analyzed ("My Cancer Diary", "Point-of-Care HIV Check", "Blood Culture" and "mAMIS"), since they use smartphone-based sensors such as the camera and barcode reader to enter data into the electronic health record system. By analyzing the usage patterns of these apps for data entry with sensors, the current limitations of smartphone-based sensors in a clinical setting, hurdles against adoption in the medical center, benefits of smartphone-based sensors and potential future research directions could be evaluated.
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Cloud computing has revolutionized healthcare in today's world as it can be seamlessly integrated into a mobile application and sensor devices. The sensory data is then transferred from these devices to the public and private clouds. In this paper, a hybrid and distributed environment is built which is capable of collecting data from the mobile phone application and store it in the cloud. ⋯ Big data technology Hadoop MapReduce is employed to analyze the data and create user timeline of user's activities. These activities are visualized to find useful health analytics and trends. In this paper a big data solution is proposed to analyze the sensory data and give insights into user behavior and lifestyle trends.
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A RF powering circuit used in radio-frequency identification (RFID) tags and other batteryless embedded devices is presented in this paper. The RF powering circuit harvests energy from electromagnetic waves and converts the RF energy to a stable voltage source. Analysis of a NMOS gate-cross connected bridge rectifier is conducted to demonstrate relationship between device sizes and power conversion efficiency (PCE) of the rectifier. ⋯ The RF powering circuit is also fabricated in the HJTC 0.25 μm process. The area of the RF powering circuit is 0.23 × 0.24 mm². The RF powering circuit is successfully integrated with ISO/IEC 15693-compatible and ISO/IEC 14443-compatible RFID tag chips.
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An emerging demand for the precise manipulation of cells and particles for applications in cell biology and analytical chemistry has driven rapid development of ultrasonic manipulation technology. Compared to the other manipulation technologies, such as magnetic tweezing, dielectrophoresis and optical tweezing, ultrasonic manipulation has shown potential in a variety of applications, with its advantages of versatile, inexpensive and easy integration into microfluidic systems, maintenance of cell viability, and generation of sufficient forces to handle particles, cells and their agglomerates. This article briefly reviews current practice and reports our development of various ultrasonic standing wave manipulation devices, including simple devices integrated with high frequency (>20 MHz) ultrasonic transducers for the investigation of biological cells and complex ultrasonic transducer array systems to explore the feasibility of electronically controlled 2-D and 3-D manipulation. ⋯ The behavior and performance of the devices have been investigated and predicted with computer simulations, and verified experimentally. Issues met during development are highlighted and discussed. To assist long term practical adoption, approaches to low-cost, wafer level batch-production and commercialization potential are also addressed.