The prototype of compact light-weighted hyperspectral imager based on the compact Offnerspectrometer is introduced. Two curved prisms are designed to disperse the incident light in the optical system with the benefits of low smile, keystone and lateral distortion. It has 148 spectral bands covering spectral range from 420 to 1000nm, the ground sampling distance is 50m@700km, and the swath width is 100km. But the weight is only 12.8kg, the outer dimensions are 362mm (X)* 343mm (Z)*139 mm (Y). As prisms are used for imaging spectrometer, the spectral sampling distance varies with wavelength. The width of the spectral response function varies from 1nm to 12nm. The mean bandwidth is less than 5nm. The sensor has achieved high performance levels in terms of signal to noise ratio(SNR), spectral calibration and image quality. It can be used for environmental and disaster monitoring.
A non-contact heart rate detection method based on the dual-wavelength technique is proposed and demonstrated experimentally. The heart rate is obtained based on the PhotoPlethysmoGraphy (PPG). Each detection module uses the reflection detection probe which is composed of the LED and the photodiode. It is a well-known fact that the differences in the circuits of two detection modules result in different responses of two modules for motion artifacts. It will cause a time delay between the two signals. This poses a great challenge to compensate the motion artifacts during measurements. In order to solve this problem, we have firstly used the time registration and translated the signals to ensure that the two signals are consistent in time domain. Then the adaptive filter is used to compensate the motion artifacts. Moreover, the data obtained by using this non-contact detection system is compared with those of the conventional finger blood volume pulse (BVP) sensor by simultaneously measuring the heart rate of the subject. During the experiment, the left hand remains stationary and is detected by a conventional finger BVP sensor. Meanwhile, the moving palm of right hand is detected by the proposed system. The data obtained from the proposed non-contact system are consistent and comparable with that of the BVP sensor. This method can effectively suppress the interference caused by the two circuit differences and successfully compensate the motion artifacts. This technology can be used in medical and daily heart rate measurement.
This paper proposes a method to recover the pulse signal with the theory of lock-in amplifier and calculates the oxygen saturation. The pulse signal is obtained based on the method of Photoplethysmography (PPG). We use a LED as the light source and a photoelectric diode as the receiver to get a measured pulse wave. Because the pulse wave obtained by this method is easily disturbed by motion artifact, we use an electrocardiogram (ECG) signal to aid PPG measurement. Firstly, the ECG signal is processed by the Fast Fourier Transform (FFT) and get the heart rate. Secondly, with the value of heart rate, a typical noise free pulse waveform can be constructed. Finally, we use it as a reference input to get a recovered pulse wave by the theory of lock-in amplifier. Thus, the value of oxygen saturation can be calculated accurately through two recovered pulse waveforms of red (660nm) and infrared (940nm) light. Some volunteers were tested. The correlation coefficient between the experimental data and the data provided by a reference instrument is 0.98, proving that this method has high reliability and utility in motion.
A new method of pulse signal de-noising based on wavelet transform and coherent averaging method is proposed. Pulse
signal is complex and weak, generally submerged by the interference of baseline drift, motion artifact and high
frequency noise. Consequently, it’s difficult to measure the heart rate by processing only one single-channel pulse signal,
especially when the noise frequency and the pulse signal frequency are in the same frequency range. In this paper, multichannel
pulse signal processing based on wavelet transform and coherent averaging is proposed to solve the above
problem. First, the detail coefficients and approximation coefficients of each channel signal are obtained by N layer
wavelet decomposition, then reconstructing the signal with high layers coefficients as the high frequency noises always
exist in low layers coefficients. In this way we can filter out the high frequency interference. Second, the centerline of
the upper and lower envelope curve obtained by cubic spline estimation is subtracted from each reconstructed signal so
as to eliminate the baseline drift completely. Finally, the heart rate is acquired with the coherent averaging method which
results in the noise being offset each other and the pulse signal being enhanced in the frequency range of pulse wave. The
pulse signal and three kinds of noise signals simulated with the superposition of different frequency sin signal were
analyzed, besides the experiment of six channel pulse signals measured simultaneously based on PhotoPlethysmoGraphy
(PPG) were conducted. The simulation and experiment results showed that this method was superior to the traditional
Standard instrumentation for the assessment of respiration rate is large and based on invasive method, and not suitable
for daily inspection. An optical, simple and non-contact measurement method to detect human respiration rate using lowend
imaging equipment is discussed. This technology is based on the visible light absorption of blood, which contains
many important physiological information of the cardiovascular system. The light absorption of facial area can be
indirectly reflected to gray value of the corresponding area image. In this paper, we acquire the respiration rate through
the video signal captured by low-end imaging equipment. Firstly, the color CCD captures the facial area below the eyes
and every frame of the video can be separated into three RGB channels. The blue channel is extracted as the research
object. Then, we calculate the mean gray value for each image and draw the mean gray curve along the time. Fourier
transform can get the frequency spectrogram of the graph, which is filtered through the Fourier filter. The extreme point
is the value of the respiratory rate. Finally, an available interface program is designed and we have some volunteers
tested. The correlation coefficient between the experimental data and the data provided by a reference instrument is 0.98.
The consistency of the experimental results is very well. This technology costs so low that it will be widely used in
medical and daily respiration rate measurement.
A new cardiac rate measurement method is proposed. Through the beam splitter prism, the common-path optical system
of transmitting and receiving signals is achieved. By the focusing effect of the lens, the small amplitude motion artifact is
inhibited and the signal-to-noise is improved. The cardiac rate is obtained based on the PhotoPlethysmoGraphy (PPG).
We use LED as the light source and use photoelectric diode as the receiving tube. The LED and the photoelectric diode
are on the different sides of the beam splitter prism and they form the optical system. The signal processing and display
unit is composed by the signal processing circuit, data acquisition device and computer. The light emitted by the
modulated LED is collimated by the lens and irradiates the measurement target through the beam splitter prism. The light
reflected by the target is focused on the receiving tube through the beam splitter prism and another lens. The signal
received by the photoelectric diode is processed by the analog circuit and obtained by the data acquisition device.
Through the filtering and Fast Fourier Transform, the cardiac rate is achieved. We get the real time cardiac rate by the
moving average method. We experiment with 30 volunteers, containing different genders and different ages. We compare
the signals captured by this method to a conventional PPG signal captured concurrently from a finger. The results of the
experiments are all relatively agreeable and the biggest deviation value is about 2bmp.
Compared with the traditional infrared imaging technology, the new type of optical-readout uncooled infrared imaging technology based on MEMS has many advantages, such as low cost, small size, producing simple. In addition, the theory proves that the technology’s high thermal detection sensitivity. So it has a very broad application prospects in the field of high performance infrared detection. The paper mainly focuses on an image capturing and processing system in the new type of optical-readout uncooled infrared imaging technology based on MEMS. The image capturing and processing system consists of software and hardware. We build our image processing core hardware platform based on TI’s high performance DSP chip which is the TMS320DM642, and then design our image capturing board based on the MT9P031. MT9P031 is Micron’s company high frame rate, low power consumption CMOS chip. Last we use Intel’s company network transceiver devices-LXT971A to design the network output board. The software system is built on the real-time operating system DSP/BIOS. We design our video capture driver program based on TI's class–mini driver and network output program based on the NDK kit for image capturing and processing and transmitting. The experiment shows that the system has the advantages of high capturing resolution and fast processing speed. The speed of the network transmission is up to 100Mbps.