Analysis of Wrist Pulse Signals Using Spatial Features in Time Domain

Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for health care applications.

Statistical Analysis of Wrist Pulse Signals Obtained Under Different Food Intake Conditions

It is well known that wrist pulse signals contain information about the status of health of a person and hence diagnosis based on pulse signals has assumed great importance since long time. In this paper the efficacy of signal processing techniques in extracting useful information from wrist pulse signals has been demonstrated by using signals recorded under two different experimental conditions viz. before lunch condition and after lunch condition. We have used Pearson's product-moment correlation coefficient, which is an effective measure of phase synchronization, in making a statistical analysis of wrist pulse signals. Contour plots and box plots are used to illustrate various differences. Two-sample t-tests show that the correlations show statistically significant differences between the groups. Results show that the correlation coefficient is effective in distinguishing the changes taking place after having lunch. This paper demonstrates the ability of the wrist pulse signals in detecting changes occurring under two different conditions. The study assumes importance in view of limited literature available on the analysis of wrist pulse signals in the case of food intake and also in view of its potential health care applications.

Study of Wrist Pulse Signals Using a Bi-Modal Gaussian Model

Wrist pulse signals contain important information about the health of a person and hence diagnosis based on pulse signals has assumed great importance. In this paper we demonstrate the efficacy of a two term Gaussian model to extract information from pulse signals. Results have been obtained by conducting experiments on several subjects to record wrist pulse signals for the cases of before exercise and after exercise. Parameters have been extracted from the recorded signals using the model and a paired t-test is performed, which shows that the parameters are significantly different between the two groups. Further, a recursive cluster elimination based support vector machine is used to perform classification between the groups. An average classification accuracy of 99.46% is obtained, along with top classifiers. It is thus shown that the parameters of the Gaussian model show changes across groups and hence the model is effective in distinguishing the changes taking place due to the two different recording conditions. The study has potential applications in healthcare.

Study of wrist pulse signals using time domain spatial features

Blood travels throughout the body and thus its flow is modulated by changes in body condition. As a consequence, the wrist pulse signal contains important information about the status of the human body. In this work we have employed signal processing techniques to extract important information from these signals. Radial artery pulse pressure signals are acquired at wrist position noninvasively for several subjects for two cases of interest, viz. before and after exercise, and before and after lunch. Further analysis is performed by fitting a bi-modal Gaussian model to the data and extracting spatial features from the fit. The spatial features show statistically significant (p < 0.001) changes between the groups for both the cases, which indicates that they are effective in distinguishing the changes taking place due to exercise or food intake. Recursive cluster elimination based support vector machine classifier is used to classify between the groups. A high classification accuracy of 99.71% is achieved for the exercise case and 99.94% is achieved for the lunch case. This paper demonstrates the utility of certain spatial features in studying wrist pulse signals obtained under various experimental conditions. The ability of the spatial features in distinguishing changing body conditions can be potentially used for various healthcare applications. (C) 2015 Elsevier Ltd. All rights reserved.

A low-power, low-cost soil-moisture sensor using dual-probe heat-pulse technique

This paper presents the development and testing of an integrated low-power and low-cost dual-probe heat-pulse (DPHP) soil-moisture sensor in view of the electrical power consumed and affordability in developing countries. A DPHP sensor has two probes: a heater and a temperature sensor probe spaced 3 mm apart from the heater probe. Supply voltage of 3.3V is given to the heater-coil having resistance of 33 Omega power consumption of 330 mW, which is among the lowest in this category of sensors. The heater probe is 40 mm long with 2 mm diameter and hence is stiff enough to be inserted into the soil. The parametric finite element simulation study was performed to ensure that the maximum temperature rise is between 1 degrees C and 5 degrees C for wet and dry soils, respectively. The discrepancy between the simulation and experiment is less than 3.2%. The sensor was validated with white clay and tested with red soil samples to detect volumetric water-content ranging from 0% to 30%. The sensor element is integrated with low-power electronics for amplifying the output from thermocouple sensor and TelosB mote for wireless communication. A 3.7V lithium ion battery with capacity of 1150 mAh is used to power the system. The battery is charged by a 6V and 300 mA solar cell array. Readings were taken in 30 min intervals. The life-time of DPHP sensor node is around 3.6 days. The sensor, encased in 30 mm x 20 mm x 10 mm sized box, and integrated with electronics was tested independently in two separate laboratories for validating as well as investigating the dependence of the measurement of soil-moisture on the density of the soil. The difference in the readings while repeating the experiments was found out to be less than 0.01%. Furthermore, the effect of ambient temperature on the measurement of soil-moisture is studied experimentally and computationally. (C) 2015 Elsevier B.V. All rights reserved.

Multiphase technique improves mud-pulse velocity calculations

Measurement while drilling (MWD) has become a popular survey technology to monitor directional data, drilling data, formation evaluation data and safety data in the world. And closed loop drilling shows promise in recent years. Obviously, the method of tr

Detection and Characterization of Long-Pulse Low-Velocity Impact Damage in Plastic Bonded Explosives

Damage not only degrades the mechanical properties of explosives, but also influences the shock sensitivity, combustion and even detonation behavior of explosives. The study of impact damage is crucial in the vulnerability evaluation of explosives. A long-pulse low-velocity gas gun with a gas buffer was developed and used to induce impact damage in a hot pressed plastic bonded explosive. Various methods were used to detect and characterize the impact damage of the explosive. The microstructure was examined by use of polarized light microscopy. Fractal analysis of the micrographs was conducted by use of box counting method. The correlation between the fractal dimensions and microstructures was analyzed. Ultrasonic testing was conducted using a pulse through-transmission method to obtain the ultrasonic velocity and ultrasonic attenuation. Spectra analyses were carried out for recorded ultrasonic signals using fast Fourier transform. The correlations between the impact damage and ultrasonic parameters including ultrasonic velocities and attenuation coefficients were also analyzed. To quantitatively assess the impact induced explosive crystal fractures, particle size distribution analyses of explosive crystals were conducted by using a thorough etching technique, in which the explosives samples were soaked in a solution for enough time that the binder was totally removed. Impact induces a large extent of explosive crystal fractures and a large number of microcracks. The ultrasonic velocity decreases and attenuation coefficients increase with the presence of impact damage. Both ultrasonic parameters and fractal dimension can be used to quantitatively assess the impact damage of plastic bonded explosives.

Colliding-pulse modelocked quantum dot lasers

Colliding pulse modelocking is demonstrated for the first time in quantum dot lasers. Using 3.9 mm-long devices with a 245 pm-long central absorber, 7 ps pulses at a repetition rate of 20 GHz is obtained. For Gaussian pulses a time-bandwidth product close to the Fourier transform limit is determined. These results confirm the potential of quantum dot lasers for high repetition rate harmonic modelocking.

Effects of superimposed pulse bias on TiN coating in cathodic arc deposition

Orthogonal designs are used to investigate the main factors when doing experiments in which pulse bias is superimposed on d.c. bias during cathodic are deposition of TiN. Pulse peak, duty cycle, frequency, direct voltage, are current and pressure all are investigated when coating TiN on HSS substrates. Roughness, surface micrograph, microhardness and thickness are tested. By analysis of variance, it is shown that pressure and frequency are the main factors. R-a and droplet density of the film with (d.c. + pulse) bias decrease. A simple explanation for the result is suggested.

Thermal Decomposition of 1,2-Dichloroethane in a Single-Pulse Shock Tube

在单脉冲激波管上,研究了1,2-二氯乙烷的热裂解.实验的激波条件为:温度区间1020 K＜T＜1190 K, 压力: P=0.12 MPa,实验时间τ=0.5 ms;实验气体为1,2-二氯乙烷稀释于Ar气中(3.95 mmol/L).以4-甲基-1-环己烯作为对比速率法实验的内标物,用4-甲基-1-环己烯开环反应的速率常数k=1015.3exp(-33400/T) s-1,以及从其产物的浓度推定出实验温度.经激波加热后的实验气体的终产物用气相色谱分析出主要成分为C2H3Cl,指示出主要反应通道为β消去反应.如把所有产物C2H3Cl都归于β消去反应,则可推定出表观之反应速率常数k1a=5.0×1013exp(-30000/T) s-1.对于由C-Cl键断键反应引发的链反应的可能影响做了分析研究.用了一种简便分析可推知在实验的温度范围内的低端(1020 K)链反应的影响可以忽略,而在其高端(1190 K)链反应将给出10%的终产物C2H3Cl的附加浓度,获得真实的β消去反应速率常数则必须把这部分予以扣除.经过这样的校正之后,最后得到CH2ClCH2Clβ消去反应速率常数为k1c=2.3×1013exp(-29200/T) s-1.

Numerical Investigation on Laser Transformation Hardening with Different Temporal Pulse Shapes

A 3-D numerical model for pulsed laser transformation hardening (LTH) is developed using the finite element method. In this model, laser spatial and temporal intensity distribution, temperature-dependent thermophysical properties of material, and multi-phase transformations are considered. The influence of laser temporal pulse shape on connectivity of hardened zone, maximum surface temperature of material and hardening depth is numerically investigated at different pulse energy levels. Results indicate that these hardening parameters are strongly dependent on the temporal pulse shape. For the rectangular temporal pulse shape, the temperature field obtained from this model is in excellent agreement with analytical solution, and the predicted hardening depth is favorably compared with experimental one. It should be pointed out that appropriate temporal pulse shape should be selected according to pulse energy level in order to achieve desirable hardening quality under certain laser spatial intensity distribution.