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| 1 | Application of EEG multipole model in the diagnosis of Alzheimer's disease显示文摘In order to find the electroencephalogram (EEG) characteristic parameters typical of Alzheimer’s disease (AD) and explore an effec- tive diagnostic method, a new mobile current multipole model was proposed to simulate the AD patient’s cortical dipole source activities. The indicators of goodness of fit (GOF) and DtononD (DD) were calculated from EEG samples to evaluate the performance of this model. Relevant results showed that this multipole model with higher GOF values and larger DD change well fitted the pathological elec- trical activities of cortical neurons aroused by AD’s extended sulcus and gyrus in the cerebral cortex. Meanwhile, the products of DD mean & standard variance were found in a clear linear correlation with the diagnostic data of mini-mental state examination (MMSE) used in AD clinics. Furthermore, by tracing this multipole model’s indicators in typical patients and contrasting with the functional mag- netic resonance image (fMRI) as AD progressed, we suggested that the DD index may be suitable for monitoring the AD developments as a new diagnostic parameter. | Baikun Wan Longlong Cheng Xia Hu Dong Ming | 2008 | Progress in Natural Science:Materials International2008，18，1： | 0 |
| 2 | Rapid fatty acids detection of vegetable oils by Raman spectroscopy based on competitive adaptive reweighted sampling coupled with support vector regression显示文摘Objectives:The composition and content of fatty acids are critical indicators of vegetable oil quality.To overcome the drawbacks of traditional detection methods,Raman spectroscopy was investigated for the fast determination of the fatty acids composition of oil.Materials and Methods:Rapeseed and soybean oil at different depths of the oil tank at different storage times were collected and an eighth-degree polynomial function was used to fit the Raman spectrum.Then,the multivariate scattering correction,standard normal variable transformation(SNV),and Savitzky–Golay convolution smoothing methods were compared.Results:Polynomial fitting combined with SNV was found to be the optimal pretreatment method.Characteristic wavelengths were selected by competitive adaptive reweighted sampling.For monounsaturated fatty acids(MUFAs),polyunsaturated fatty acids(PUFAs),and saturated fatty acids(SFAs),44,75,and 92 characteristic wavelengths of rapeseed oil,and 60,114,and 60 characteristic wavelengths of soybean oil were extracted.Support vector regression was used to establish the prediction model.The R^(2)values of the prediction results of MUFAs,PUFAs,and SFAs for rapeseed oil were 0.9670,0.9568,and 0.9553,and the root mean square error(RMSE)values were 0.0273,0.0326,and 0.0340,respectively.The R^(2)values of the prediction results of fatty acids for soybean oil were respectively 0.9414,0.9562,and 0.9422,and RMSE values were 0.0460,0.0378,and 0.0548,respectively.A good correlation coefficient and small RMSE value were obtained,indicating the results to be highly accurate and reliable.Conclusions:Raman spectroscopy,based on competitive adaptive reweighted sampling coupled with support vector regression,can rapidly and accurately analyze the fatty acid composition of vegetable oil. | Linjiang Pang Hui Chen Liqing Yin Jiyu Cheng Jiande Jin Honghui Zhao Zhihao Liu Longlong Dong Huichun Yu Xinghua Lu | 2022 | Food Quality and Safety2022，6，4： | 0 |
| 3 | A 124 dB dynamic range sigma-delta modulator applied to non-invasive EEG acquisition using chopper-modulated input-scaling-down technique显示文摘With the advancement of brain science in recent years,the non-invasive brain-computer interfaces(BCIs)based on electroencephalogram(EEG)acquisition have been widely adopted in various brain-inspired applications.The acquisition of multi-channel microvolts EEG signals corrupted by the motion artifacts(MAs)of up to several volts poses enormous challenges to the design of analog front-end(AFE),especially the analog-to-digital converter(ADC),which is necessary to achieve low noise,wide dynamic range(DR),high accuracy as well as low power.In this paper,a wide DRΣ∆modulator with chopper-modulated inputscaling-down(CM-ISD)technique has been proposed to deal with large input offset while extending dynamic range.Fabricated in 180 nm CMOS technology,the prototype occupies a core area of 0.32 mm^(2).With a 40 Hz input signal and 125 Hz Nyquist bandwidth,the measured signal-to-noise ratio(SNR)and signalto-noise and distortion ratio(SNDR)are 117 and 110 dB,respectively.Thanks to the proposed CM-ISD technique,the modulator is capable of withstanding a full-scale(4.5 V_(pp))input whereas the measured DR has been extended from 99 to 124 dB.The power consumption is 2.75 mW under 5 V supply voltage,corresponding to 170.6 dB Schreier figure-of-merit(FoMS).The multi-channel EEG acquisition has been demonstrated based on the proposed modulator,showing its potential in advanced non-invasive BCI systems. | Kaiquan CHEN Mingyi CHEN Longlong CHENG Liang QI Guoxing WANG Yong LIAN | 2022 | Science China(Information Sciences)2022，65，4： | 0 |
| 4 | Electric modulation of conduction in MAPbBr_(3) single crystals显示文摘The resistive switching(RS)mechanism of hybrid organic–inorganic perovskites has not been clearly understood until now.A switchable diode-like RS behavior in MAPbBr3 single crystals using Au(or Pt)symmetric electrodes is reported.Both the high resistance state(HRS)and low resistance state(LRS)are electrode-area dependent and light responsive.We propose an electric-fielddriven inner p–n junction accompanied by a trap-controlled space-charge-limited conduction(SCLC)conduction mechanism to explain this switchable diode-like RS behavior in MAPbBr_(3) single crystals. | Shanming Ke Shangyu Luo Jinhui Gong Liwen Qiu Renhong Liang Yangbo Zhou Bingcheng Luo Baochang Cheng Li Wang Longlong Shu | 2021 | Journal of Advanced Ceramics2021，10，2： | 0 |
| 5 | A 70%-power transmission efficiency, 3.39 Mbps power and data telemetry over a single 13.56 MHz inductive link for biomedical implants显示文摘The application of wireless power and data telemetry to implantable medical devices(IMDs)has grown dramatically in recent decades. Achieving a high data rate and high-power transmission efficiency(PTE) over the same inductive link remains challenging. This paper presents a power and data telemetry circuit over a single 13.56 MHz inductive link. On the transmitter(TX) side, a binary-phase-shift keying(BPSK) modulation based on a Class-E amplifier that features a high modulation rate and a high quality(Q)-factor is proposed. A digital-assisted phase-locked-loop(PLL) is proposed on the receiver(RX) side as a BPSK demodulator to handle the long settling process. The maximum data rate can be extended to 1/4 of the carrier frequency. The prototype has been fabricated with a 180 nm BCD(Bipolar-CMOS-DMOS)process. The measurement shows that up to 31.25 mW of power can be delivered simultaneously with 3.39-Mbps of data transmission, while a 2×10^(-7)bit-error-rate(BER) can be ensured over a transmission distance of 5 mm. The peak PTE is 70%, whereas the RX energy efficiency is 183 p J/bit. The results demonstrate the potential of the proposed techniques in applications to various biomedical implants with intensive bandwidth and energy efficiency requirements. | Mingyi CHEN Luominghao PAN Qiuyang LIN Longlong CHENG Dong MING | 2023 | Science China(Information Sciences)2023，66，2： | 0 |
| 6 | Research on EEG emotion recognition based on CNN+BiLSTM+self-attention model显示文摘To address the problems of insufficient dimensionality of electroencephalogram(EEG) feature extraction,the tendency to ignore the importance of different sequential data segments,and the poor generalization ability of the model in EEG based emotion recognition,the model of convolutional neural network and bi-directional long short-term memory and self-attention(CNN+Bi LSTM+self-attention) is proposed.This model uses convolutional neural network(CNN) to extract more distinctive features from both spatial and temporal dimensions.The bi-directional long short-term memory(Bi LSTM) is used to further preserve the long-term dependencies between the temporal phases of sequential data.The self-attention mechanism can change the weights of different channels to extract and highlight important information and address the often-ignored importance of different channels and samples when extracting EEG features.The subject-dependent experiment and subject-independent experiment are performed on the database for emotion analysis using physiological signals(DEAP) and collected datasets to verify the recognition performance.The experimental results show that the model proposed in this paper has excellent recognition performance and generalization ability. | LI Xueqing LI Penghai FANG Zhendong CHENG Longlong WANG Zhiyong WANG Weijie | 2023 | Optoelectronics Letters2023，19，8： | 0 |
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