Yuko Mizuno-Matsumoto

The purpose of this study is to verify whether machine learning using electroencephalogram (EEG) and electrocardiogram (ECG) as inputs improves accuracy. The participants, 16 healthy adults, were given two stimulations: resting and unpleasant stimuli. Their EEG was measured 180 s immediately after the stimuli. The beta band of EEG and LF, HF, and LF/HF of ECG were calculated. The accuracy of the neural network was then compared using an EEG-only, ECG-only, and combined EEG and ECG dataset. The accuracy of the neural network using the combined EEG and ECG dataset was 79.51%, which was higher than that of the other datasets. The results suggest that emotional responses to resting and unpleasant stimuli may differ in brain and autonomic nervous system activity, and that combining both EEG and ECG indices may allow for more accurate discrimination.

The usefulness of stretching to improve cold sensitivity in healthy adults was investigated using skin surface temperature and finger plethysmography. Thirty-one healthy adults in the age group of 20‒25 years were divided into two groups: high upper-limb muscle mass group and low upper-limb muscle mass group. In experiment one, two rounds of hand bath were performed. In experiment two, one round of hand bath and one round of stretching followed by hand bath were performed. In both experiments, pulse wave amplitude and skin surface temperature were measured for ten minutes after hand bath and the temperatures of both the groups were compared. For the high group, the pulse wave amplitude and skin surface temperature did not change in both the experiments compared to the resting state. In experiment two, the pulse wave amplitude at rest, after the hand bath and after stretching and hand bath, were significantly higher for the low group than that of the high group. Moreover, the skin surface temperature in experiment two was significantly higher than in experiment one after zero, two, four, and six minutes. Therefore, stretching has improved the cold sensitivity for the low muscle mass group.

In this study, nursing students were classified into two groups and the effects of mindfulness were investigated from a physiological perspective. The subjects (20 people) were randomly divided into two groups, and EEG was measured during the task in the group that applied mindfulness and the group that did not apply mindfulness during 5 days. The analysis points were theta, alpha, and beta waves during the task in both groups, and the power spectrum values of each frequency band were compared. The results suggested that mindfulness had a relaxation effect during the task and maintained attention after the task was completed. All the subjects in the mindfulness group practiced mindfulness continuously for five days during the experimental period, and the relaxation effect was sustained even when they did not practice mindfulness in a situation of reduced tension. These results suggest that mindfulness is useful for task performance and relaxation.

In this study, a brain network was created using graph theoretical analysis based on electroencephalography (EEG) data. The purpose of the study was to investigate the functional connectivity of the brain in different states of anxiety. Seventeen adults with anxiety (A-G), and 13 adults without anxiety (AF-G) were examined. They were given three different stimulations: resting, pleasant, and unpleasant. EEG was measured immediately after the stimulation. The EEG was analyzed by Fast Fourier Transform (FFT), coherence analysis, and graph theory. The results of FFT and coherence analysis showed that the anxiety group (A-G) had higher power spectra and coherence values than those for the anxiety-free group (AF-G) in all sessions. The results of graph theory analysis showed that the clustering coefficient and small-worldness in A-G were lower than those in AF-G, although the characteristic path length in A-G was higher than that in AF-G. This study shows that the brain of A-G has smaller clusters and longer paths to compare with those of AF-G. These events suggest that the brain of A-G would have an inefficient network structure to transmit emotional information.

[Objective] The purpose of this study was to investigate the information processing process in the brain by cross-correlation analysis of brain waves after emotional stimulation with a smartphone. [Methods] The subjects were 23 healthy adults that were divided into two groups, namely stress and non-stress groups, via psychological examination. In the experiment, stimuli of relaxation, pleasant, unpleasant, pleasant sentence, and unpleasant sentence were displayed on a smartphone for the subject, and the brain waves were measured concurrently. To record the EEG data, the electrodes (19 channels) were placed according to the international 10/20 system. Coherence analysis was performed on the EEG, and the coherence values and time lag in 171 combinations among all channels in the alpha 1 band (8–10 Hz) were calculated. [Results] The time-lag between unpleasant, pleasant, and unpleasant sentences in the non-stress group was higher than that for the rest and pleasant stimuli. The stress group showed higher time-lag than the non-stress group at all stimulation times. [Discussion] The results imply that the stress group has slower information propagation compared to the non-stress group. Additionally, it can be suggested that text stimulation received from a smartphone has slow information propagation, regardless of its content.

This study aimed to evaluate the effects of psychological support utilizing mindful breathing on emotional load and task execution in college students using pulse waves. The subjects (20 students) were randomly divided into two groups (10 students each in the mindfulness and nonmindfulness groups). The number of answers and number of correct answers on a mental arithmetic task were compared between the mindfulness group and non-mindfulness group on day 1, day 5, and day 10. We also analyzed the results of fingertip plethysmography during the experiment. There was a significant difference between the number of answers and number of correct answers on the mental arithmetic task. The results for pulse wavelength suggested that mindful breathing was effective in suppressing sympathetic nerves. With regard to autonomic nervous system activity, the sympathetic nervous system was dominant before mindfulness practice and the sympathetic nervous system was suppressed after mindfulness practice. These results suggest that mindfulness may be useful for task execution and relaxation.

The objective of this study is to extract the features of the network in the brain of schizophrenia patients using network analysis of EEG. The EEGs of 10 healthy adults and 10 patients with schizophrenia were measured. The EEG was analyzed using wavelet-crosscorrelation analysis and graph theory. Our results showed that the schizophrenia patients had a lower small world index than the healthy subjects. This suggests that schizophrenia patients have a different brain network compared to healthy individuals, with poor connections and inefficient communication pathways between brain sites.

Cortical stimulation has been used for brain mapping for over a century, and a standard assumption is that stimulation interferes with task execution due to local effects at the stimulation site. Stimulation can however produce afterdischarges which interfere with functional localization and can lead to unwanted seizures. We previously showed that (a) cognitive effort can terminate these afterdischarges, (b) when termination thus occurs, there are electrocorticography changes throughout the cortex, not just at sites with afterdischarges or sites thought functionally important for the cognitive task used, and (c) thresholds for afterdischarges and functional responses can change among stimulation trials. We here show that afterdischarge termination can occur prior to overt performance of the cognitive tasks used to terminate them. These findings, taken together, demonstrate that task-related brain changes are not limited to one or a group of functional regions or a specific network, and not limited to the time directly surrounding overt task execution. Discrete locations, networks and times importantly underpin clinical behaviors. However, brain activity that is diffuse in location and extended in time also affect task execution and can affect brain mapping. This may in part reflect fluctuating levels of attention, engagement, or motivation during testing.

We evaluated the impact of different mood states on electroencephalogram (EEG) activity and surface sensation electrical current values using surface sensory nerve electrical stimulation in a virtual reality (VR) environment. The participants were 22 adults. The Profile of Mood States (POMS) was used as a psychological test to calculate the Total Mood Disturbance (TMD) score to divide participants into a high TMD group and a low TMD group. Three videos were selected for each of three different conditions (resting, unpleasant, pleasant) for a total of nine videos. Pain Vision was used to calculate the pain ratio (PR) to evaluate surface sensory nerve electrical stimulation. A subjective pain questionnaire was used to calculate the pain subjective score (PS) to assess participants’ subjective evaluations of pain. The θ wave rate (θ%), α wave rate (α%), and β wave rate (β%) were calculated for the EEG. Analysis results demonstrated that when mood was positive, PS was lower for all VR videos, but when mood was negative, PR, PS, and α% were lower and β% was higher for unpleasant and pleasant videos. Our study findings suggest that pain may be mitigated subjectively when mood is positive, and when mood is negative, it may be mitigated both subjectively and objectively as demonstrated by electrical stimulation.

Graph theoretical analysis has recently been used to study brain function. This study aims to compare the functional brain networks derived from electroencephalography (EEG) of 10 patients suffering from epilepsy with 10 healthy subjects based on graph theory. Five epochs per healthy subject, and ten epochs (during epileptiform discharge and non-discharge) per patient were selected and analyzed using wavelet-crosscorrelation analysis. The clustering coefficient, characteristic path length, small-worldness, and nodal betweenness centrality were calculated using graph analysis. The results showed that in the patients, Wavelet-crosscorrelation Coefficients (WCC) were significantly higher, and clustering and path length were significantly lower during discharge compared with the healthy subjects, along with alterations in the hub regions. These results suggest a loss of small-world topology in the functional brain network of epilepsy patients. A loss of small-world topology was found even during non-discharge, therefore network indices might aid to distinguish epilepsy patients from healthy individuals.

<p>The aim of this study was to assess Virtual Reality (VR) based visual auditory stimulation can relieve pain. To achieve this, the impact that body surface electrical stimulation has on the body surface potentials and activity in the central nervous system in VR environments were extracted. Twenty-two adults participated in this study. The body surface potentials and Electroencephalogram frequencies were measured under various conditions: non-viewing, viewing neutral clips, viewing unpleasant clips, and viewing pleasant clips. The pain index was calculated from the body surface potentials. Participants were asked to complete subjective pain measurement scales. Results showed that the pain index and the relative subjective pain score decreased when presented with unpleasant and pleasant video clips. The incidence of alpha waves declined when presented with unpleasant clips, while the incidence of beta waves increased when presented with unpleasant and pleasant video clips. Inattentiveness to pain due to VR immersion and descending pain inhibition due to awareness of emotional stress after viewing VR clips were considered to have contributed to the decline in the pain index and in relative subjective pain score. This study suggests that it is possible to relieve pain by VR viewing related to unpleasant or pleasant.</p>

The objective of this study was to develop a home care support system using a smartphone to solve problems of patients with psychiatric disorders such as schizophrenia. We have created a system by which patients can input their symptoms, drug administrations, doctor’s appointments, and so on from the comfort of their homes to support their own treatment and recovery. We got healthcare professionals including nurses and psychiatric patients to evaluate the system. The results showed that the input items for the physical and mental symptoms were inevitable. In particular, it was suggested that support for prodromal symptoms, thought disorders, and lack of motivation would be effective in the system. These findings suggest that a home care support system via a smartphone could be helpful for psychiatric patients’ self-care.

クエン酸第二鉄(FCH)服用中の血液透析患者を対象として、貧血関連指標の特徴を後方視的に検討した。FCH服用によりヘモグロビン(Hb)overshootを起こした61例、ならびにHb overshootを起こしていない血液透析患者で赤血球数(RBC)>350万/μLの34例とRBC≦350万/μLの46例について血液検査評価項目、血液透析処方項目を比較した結果、RBC>350万/μLがHb overshootの必要条件であると考えられた。また、血清フェリチンの変動はFCHの服用量に依存するのではなく、赤血球造血刺激因子(ESA)製剤投与量の変動により鉄が多く分布しているRBCの増減に依存していると考えられた。RBCと平均赤血球ヘモグロビン量を指標にESA製剤投与量を設定することで、FCH服用に伴うHb overshootをコントロールできると考えられた。

【緒言】現在、痛みの治療には主に鎮痛薬が用いられるが、副作用やコストが問題となる。また、体表面に惹起される体性痛は、医療現場において、検査を含む治療行為等の様々な場面で発生するため、痛みに対する新たな治療や対策が必要である。近年、VR環境における生体への影響に関する研究が多くなされているが、体性痛感度との関係性については明らかになっていない。そこで、本研究ではVR環境において、体性痛を模擬した低周波電流刺激による体表面感知電流閾値の影響を評価した。【方法】被験者は健常成人22名とした。VR映像は、「安静」「不快」「快」に分類し、各3種類ずつを用いた。低周波電流刺激にはPain Vision（NIPRO社製）を用い、刺激部位は左上腕部とした。各種VR映像視聴時における最小感知電流値と痛み対応電流値を測定し、痛み度を算出した。また、実験終了後に主観的評価質問紙に回答し、痛み得点を算出した。【結果】VR映像視聴時の痛み度及び痛み得点は、VR映像非視聴時と比較して有意に低値を示した。【考察】VR映像視聴時の情動負荷及び没入感覚により、意識的に注意が痛みから逸れ、前部帯状回の活動が抑制されることで、鎮痛効果が生じたと考えられる。

In some individuals, alpha waves appear in many regions of the brain, and this is considered abnormal electroencephalography (EEG). This phenomenon is known as diffuse alpha pattern. This study aims to extract and compare the features of the connectivity between the parts of the brain. The EEGs of healthy individuals and mental disorder patients with the diffuse alpha pattern were analyzed using wavelet-crosscorrelation analysis. Five epochs of 2 seconds were analyzed for each subject. Wavelet-crosscorrelation coefficients were calculated for frequencies in the alpha band for all epochs in each subject. The results showed that the WCC values were higher in the patients with diffuse alpha. The highest wavelet power spectra in the alpha band of the patients occurred at a lower frequency. Our results suggest that the connectivity strength along the sagittal and occipital orientations in the brain of the patients could be stronger than healthy individuals.

<p>The authors carried out a physiological evaluation involving plethysmographic analysis and subjective evaluation to identify differences in the usability of personal computer peripherals. As workload items, the speed of the mouse pointer was changed in three stages, and the plethysmography was measured while the users performed a Trail Making Test. Sympathetic nerve activity in the peripheral region and the central trunk region increases when the movement speed of the mouse pointer is slow. However, there was no significant difference in subjective evaluation and activity of autonomic nervous function. Competitive factors of mental workloads suggested that subjects experienced differences in load recognition of psychological stress and that this may affect the activity of autonomic nerve function.</p>