Purpose: Implant therapy restores masticatory function by restoring lost tooth morphology. It has been shown that mastication contributes not only to food intake and digestion, but also to the improvement of overall h...Purpose: Implant therapy restores masticatory function by restoring lost tooth morphology. It has been shown that mastication contributes not only to food intake and digestion, but also to the improvement of overall health. However, there have been no studies on the effects of implant treatment on electroencephalography (EEG). In this study, we investigated the effects of restoration of masticatory function by implant treatment on EEG and stress. Methods: 13 subjects (6 males, 7 females, age 64.1 ± 5.8 years) who had lost masticatory function due to tooth loss and 11 healthy subjects (6 males, 5 females, age 47.6 ± 2.4 years) as a control group. EEG (θ, α, β waves, α/β ratio) and salivary cortisol were measured before immediate dental implant treatment and every month of treatment for 6 months. EEG (θ, α, β waves, α/β ratio) was measured with a simple electroencephalograph miniature DAQ terminal (Intercross-410, Intercross Co., Ltd., Japan) in a resting closed-eye condition, and salivary cortisol was measured using an ELISA kit. Results: Compared to the control group, the appearance of θ and α waves were significantly decreased and β waves were increased, and α/β ratio was significantly decreased. The cortisol level of the subject group was significantly higher compared with the control group. With the course of implant treatment, the appearance of θ and α waves of the subject group increased, while β waves decreased. However, no significant difference was observed. The α/β ratio of the subject group increased from the first month after implant treatment and increased significantly after 5 and 6 months (0 vs. 5 months: p < 0.05, 0 vs. 6 months: p < 0.01). The cortisol levels in the subject group decreased from the first month after implant treatment and significantly decreased after 3 or 4 months (0 vs. 3 months: p < 0.05, 0 vs. 4 months: p < 0.01). These results suggest that tooth loss causes mental stress, which decreases brain stimulation and affects function. Restoration of masticatory function by implants was suggested to alleviate the effects on brain function and stress.展开更多
To investigate inter- and intra-hemispheric electroencephalography (EEG) coherence at rest and during photic stimulation of patients with Alzheimer's disease (AD). Thirty-five patients (12 males, 23 females; 52～6...To investigate inter- and intra-hemispheric electroencephalography (EEG) coherence at rest and during photic stimulation of patients with Alzheimer's disease (AD). Thirty-five patients (12 males, 23 females; 52～64 y) and 33 sex- and age-matched controls (12 males, 21 females; 56～65 y) were recruited in the present study. EEG signals from C3-C4, P3-P4, T5-T6and O1-O2 electrode pairs resulted from the inter-hemispheric action, and EEG signals from C3-P3, C4-P4, P3-O1, P4-O2, C3-O1,C4-O2, T5-O 1 and T6-O2 electrode pairs resulted from the intra-hemispheric action. The influence of inter- and intra-hemispheric coherence on EEG activity with eyes closed was examined, using fast Fourier transformation from the 16 sampled channels. The frequencies of photic stimulation were fixed at 5, 10 and 15 Hz, respectively. The general decrease of AD patients in inter- and intra-hemispheric EEG coherence was more significant than that of the normal controls at the resting EEG, with most striking decrease observed in the alpha-1 (8.0-9.0 Hz) and alpha-2 (9.5-12.5 Hz) bands. During photic stimulation, inter- and intra-hemispheric EEG coherences of the AD patients having lower values in the alpha (9.5-10.5 Hz) band than those of the control group. It suggests that under stimulated and non-stimulated conditions, AD patients had impaired inter- and intra-hemispheric functional connections, indicating failure of brain activation in alpha-related frequency.展开更多
To investigate the features of electroencephalography （EEG） power and coherence at rest and during a working memory task of patients with mild cognitive impairment （MCI）. Thirty-five patients （17 males, 18 female...To investigate the features of electroencephalography （EEG） power and coherence at rest and during a working memory task of patients with mild cognitive impairment （MCI）. Thirty-five patients （17 males, 18 females; 52-71 years old） and 34 sex- and age-matched controls （17 males, 17 females; 51-63 years old） were recruited in the present study. Mini-Mental State Examination （MMSE） of 35 patients with MCI and 34 normal controls revealed that the scores of MCI patients did not differ significantly from those of normal controls （P〉0.05）. Then, EEGs at rest and during working memory task with three levels of working memory load were recorded. The EEG power was computed over 10 channels： fight and left frontal （F3, F4）, central （C3, C4）, parietal （P3, P4）, temporal （T5, T6） and occipital （O1, O2）; inter-hemispheric coherences were computed from five electrode pairs of F3-F4, C3-C4, P3-P4, T5-T6 and O1-O2 for delta （1.0-3.5 Hz）, theta （4.0-7.5 Hz）, alpha-1 （8.0-10.0 Hz）, alpha-2 （10.5-13.0 Hz）, beta-1 （13.5-18.0 Hz） and beta-2 （18.5-30.0 Hz） frequency bands. All values of the EEG power of MCI patients were found to be higher than those of normal controls at rest and during working memory tasks. Furthermore, the values of EEG power in the theta, alpha-1, alpha-2 and beta-1 bands of patients with MCI were significantly high （P〈0.05） in comparison with those of normal controls. Correlation analysis indicated a significant negative correlation between the EEG powers and MMSE scores. In addition, during working memory tasks, the EEG coherences in all bands were significantly higher in the MCI group in comparison with those in the control group （P〈0.05）. However, there was no significant difference in EEG coherences between two groups at rest. These findings comprise evidence that MCI patients have higher EEG power at rest, and higher EEG power and coherence during working conditions. It suggests that MCI may be associated with compensatory processes at rest and during working memory tasks. Moreover, failure of normal cortical connections may be exist in MCI patients.展开更多
Objective: Optimization of combining electroencephalography (EEG), short latency somatosensory evoked potentials (SLSEP) and transcranial Doppler (TCD) techniques to diagnose brain death. Methods: One hundred and elev...Objective: Optimization of combining electroencephalography (EEG), short latency somatosensory evoked potentials (SLSEP) and transcranial Doppler (TCD) techniques to diagnose brain death. Methods: One hundred and eleven patients (69 males, 42 females) from the major hospitals of Zhejiang Province were examined with portable EEG, SLSEP and TCD devices. Re-examinations occurred ≤12 h later. Results: The first examination revealed that the combination of SLSEP and EEG led to more sensitive diagnoses than the combination of SLSEP and TCD. Re-examination confirmed this and also revealed that the combination of TCD and EEG was the most sensitive. Conclusion: The results show that using multiple techniques to diagnose brain death is superior to using single method, and that the combination of SLSEP and EEG is better than other combinations.展开更多
The driver’s cognitive and physiological states affect his/her ability to control the vehicle.Thus,these driver states are essential to the safety of automobiles.The design of advanced driver assistance systems(ADAS)...The driver’s cognitive and physiological states affect his/her ability to control the vehicle.Thus,these driver states are essential to the safety of automobiles.The design of advanced driver assistance systems(ADAS)or autonomous vehicles will depend on their ability to interact effectively with the driver.A deeper understanding of the driver state is,therefore,paramount.Electroencephalography(EEG)is proven to be one of the most effective methods for driver state monitoring and human error detection.This paper discusses EEG-based driver state detection systems and their corresponding analysis algorithms over the last three decades.First,the commonly used EEG system setup for driver state studies is introduced.Then,the EEG signal preprocessing,feature extraction,and classification algorithms for driver state detection are reviewed.Finally,EEG-based driver state monitoring research is reviewed in-depth,and its future development is discussed.It is concluded that the current EEGbased driver state monitoring algorithms are promising for safety applications.However,many improvements are still required in EEG artifact reduction,real-time processing,and between-subject classification accuracy.展开更多
文摘Purpose: Implant therapy restores masticatory function by restoring lost tooth morphology. It has been shown that mastication contributes not only to food intake and digestion, but also to the improvement of overall health. However, there have been no studies on the effects of implant treatment on electroencephalography (EEG). In this study, we investigated the effects of restoration of masticatory function by implant treatment on EEG and stress. Methods: 13 subjects (6 males, 7 females, age 64.1 ± 5.8 years) who had lost masticatory function due to tooth loss and 11 healthy subjects (6 males, 5 females, age 47.6 ± 2.4 years) as a control group. EEG (θ, α, β waves, α/β ratio) and salivary cortisol were measured before immediate dental implant treatment and every month of treatment for 6 months. EEG (θ, α, β waves, α/β ratio) was measured with a simple electroencephalograph miniature DAQ terminal (Intercross-410, Intercross Co., Ltd., Japan) in a resting closed-eye condition, and salivary cortisol was measured using an ELISA kit. Results: Compared to the control group, the appearance of θ and α waves were significantly decreased and β waves were increased, and α/β ratio was significantly decreased. The cortisol level of the subject group was significantly higher compared with the control group. With the course of implant treatment, the appearance of θ and α waves of the subject group increased, while β waves decreased. However, no significant difference was observed. The α/β ratio of the subject group increased from the first month after implant treatment and increased significantly after 5 and 6 months (0 vs. 5 months: p < 0.05, 0 vs. 6 months: p < 0.01). The cortisol levels in the subject group decreased from the first month after implant treatment and significantly decreased after 3 or 4 months (0 vs. 3 months: p < 0.05, 0 vs. 4 months: p < 0.01). These results suggest that tooth loss causes mental stress, which decreases brain stimulation and affects function. Restoration of masticatory function by implants was suggested to alleviate the effects on brain function and stress.
基金Project supported by the Foundation from the Health Bureau ofZhejiang Province (2004-2005) and the Science & Technology pro-ject of Zhejiang Province (2004-2005) China
文摘To investigate inter- and intra-hemispheric electroencephalography (EEG) coherence at rest and during photic stimulation of patients with Alzheimer's disease (AD). Thirty-five patients (12 males, 23 females; 52～64 y) and 33 sex- and age-matched controls (12 males, 21 females; 56～65 y) were recruited in the present study. EEG signals from C3-C4, P3-P4, T5-T6and O1-O2 electrode pairs resulted from the inter-hemispheric action, and EEG signals from C3-P3, C4-P4, P3-O1, P4-O2, C3-O1,C4-O2, T5-O 1 and T6-O2 electrode pairs resulted from the intra-hemispheric action. The influence of inter- and intra-hemispheric coherence on EEG activity with eyes closed was examined, using fast Fourier transformation from the 16 sampled channels. The frequencies of photic stimulation were fixed at 5, 10 and 15 Hz, respectively. The general decrease of AD patients in inter- and intra-hemispheric EEG coherence was more significant than that of the normal controls at the resting EEG, with most striking decrease observed in the alpha-1 (8.0-9.0 Hz) and alpha-2 (9.5-12.5 Hz) bands. During photic stimulation, inter- and intra-hemispheric EEG coherences of the AD patients having lower values in the alpha (9.5-10.5 Hz) band than those of the control group. It suggests that under stimulated and non-stimulated conditions, AD patients had impaired inter- and intra-hemispheric functional connections, indicating failure of brain activation in alpha-related frequency.
文摘To investigate the features of electroencephalography （EEG） power and coherence at rest and during a working memory task of patients with mild cognitive impairment （MCI）. Thirty-five patients （17 males, 18 females; 52-71 years old） and 34 sex- and age-matched controls （17 males, 17 females; 51-63 years old） were recruited in the present study. Mini-Mental State Examination （MMSE） of 35 patients with MCI and 34 normal controls revealed that the scores of MCI patients did not differ significantly from those of normal controls （P〉0.05）. Then, EEGs at rest and during working memory task with three levels of working memory load were recorded. The EEG power was computed over 10 channels： fight and left frontal （F3, F4）, central （C3, C4）, parietal （P3, P4）, temporal （T5, T6） and occipital （O1, O2）; inter-hemispheric coherences were computed from five electrode pairs of F3-F4, C3-C4, P3-P4, T5-T6 and O1-O2 for delta （1.0-3.5 Hz）, theta （4.0-7.5 Hz）, alpha-1 （8.0-10.0 Hz）, alpha-2 （10.5-13.0 Hz）, beta-1 （13.5-18.0 Hz） and beta-2 （18.5-30.0 Hz） frequency bands. All values of the EEG power of MCI patients were found to be higher than those of normal controls at rest and during working memory tasks. Furthermore, the values of EEG power in the theta, alpha-1, alpha-2 and beta-1 bands of patients with MCI were significantly high （P〈0.05） in comparison with those of normal controls. Correlation analysis indicated a significant negative correlation between the EEG powers and MMSE scores. In addition, during working memory tasks, the EEG coherences in all bands were significantly higher in the MCI group in comparison with those in the control group （P〈0.05）. However, there was no significant difference in EEG coherences between two groups at rest. These findings comprise evidence that MCI patients have higher EEG power at rest, and higher EEG power and coherence during working conditions. It suggests that MCI may be associated with compensatory processes at rest and during working memory tasks. Moreover, failure of normal cortical connections may be exist in MCI patients.
文摘Objective: Optimization of combining electroencephalography (EEG), short latency somatosensory evoked potentials (SLSEP) and transcranial Doppler (TCD) techniques to diagnose brain death. Methods: One hundred and eleven patients (69 males, 42 females) from the major hospitals of Zhejiang Province were examined with portable EEG, SLSEP and TCD devices. Re-examinations occurred ≤12 h later. Results: The first examination revealed that the combination of SLSEP and EEG led to more sensitive diagnoses than the combination of SLSEP and TCD. Re-examination confirmed this and also revealed that the combination of TCD and EEG was the most sensitive. Conclusion: The results show that using multiple techniques to diagnose brain death is superior to using single method, and that the combination of SLSEP and EEG is better than other combinations.
文摘The driver’s cognitive and physiological states affect his/her ability to control the vehicle.Thus,these driver states are essential to the safety of automobiles.The design of advanced driver assistance systems(ADAS)or autonomous vehicles will depend on their ability to interact effectively with the driver.A deeper understanding of the driver state is,therefore,paramount.Electroencephalography(EEG)is proven to be one of the most effective methods for driver state monitoring and human error detection.This paper discusses EEG-based driver state detection systems and their corresponding analysis algorithms over the last three decades.First,the commonly used EEG system setup for driver state studies is introduced.Then,the EEG signal preprocessing,feature extraction,and classification algorithms for driver state detection are reviewed.Finally,EEG-based driver state monitoring research is reviewed in-depth,and its future development is discussed.It is concluded that the current EEGbased driver state monitoring algorithms are promising for safety applications.However,many improvements are still required in EEG artifact reduction,real-time processing,and between-subject classification accuracy.
