The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.

Acupuncture is a relatively safe, commonly used "alternative" medical treatment for various symptoms. However, adverse effects can occur, including trauma, pneumothorax, and central-nervous-system injury. Our objective was to develop a reliable and practical procedure for ultrasound imaging of acupuncture points to improve safety during needling, and to acquire ultrasound images of several (44) acupuncture points, especially those in high-risk areas, according to an in-house standard operating procedure. We created the standard operating procedure for ultrasound imaging for acupuncture, and collected ultrasound images of acupuncture points in clinical trials. Ultrasound images for 44 acupuncture points considered as high-risk points were collected from 85 healthy people who were classified by body-mass index, and high-quality, clear representative images of all 44 points were obtained. These baseline images could be helpful for understanding the anatomy under the skin at acupuncture points, which would allow for an enhanced safety and more accurate needling.

Piezo-resistive pressure sensors are widely used for measuring pulse waves of the radial artery. Pulse sensors are generally fabricated with a cover layer because pressure sensors without a cover layer are fragile when they come into direct contact with the skin near the radial artery. However, no study has evaluated the dynamic pulse wave response of pulse sensors depending on the thickness and hardness of the cover layer. This study analyzed the dynamic pulse wave response according to the thickness and hardness of the cover layer and suggests an appropriate thickness and hardness for the design of pulse sensors with semiconductor device-based pressure sensors. Pulse sensors with 6 different cover layers with various thicknesses (0.8 mm, 1 mm, 2 mm) and hardnesses (Shore type A; 30, 43, 49, 71) were fabricated. Experiments for evaluating the dynamic pulse responses of the fabricated sensors were performed using a pulse simulator to transmit the same pulse wave to each of the sensors. To evaluate the dynamic responses of the fabricated pulse sensors, experiments with the pulse sensors were conducted using a simulator that artificially generated a constant pulse wave. The pulse wave simulator consisted of a motorized cam device that generated the artificial radial pulse waveform by adjusting the stroke of the cylindrical air pump and an air tube that conveyed the pulse to the artificial wrist. The amplitude of the measured pulse pressure decreased with increasing thickness and hardness of the cover layer. Normalized waveform analysis showed that the thickness rather than the hardness of the cover layer contributed more to waveform distortion. Analysis of the channel distribution of the pulse sensor with respect to the applied constant dynamic pressure showed that the material of the cover layer had a large effect. In this study, in-line array pulse sensors with various cover layers were fabricated, the dynamic pulse wave responses according to the thickness and the hardness of the cover layer were analyzed, and an appropriate thickness and hardness for the cover layer were suggested. The dynamic pulse wave responses of pulse sensors revealed in this study will contribute to the fabrication of improved pulse sensors and pulse wave analyses.

The aim of this study was to compare radial pulse characteristics between primary dysmenorrhea (PD) patients and healthy subjects throughout the menstrual cycle. A total of 48 females aged 20 to 29 years participated, and all subjects were assigned to two groups according to their visual analogue scale scores. The radial pulse of each subject was obtained using a pulse tonometric device during menstrual, follicular, and luteal phases. In addition, various pulse analysis indices were used to estimate the pulse characteristics. The pulse tension index (PTI) and pulse depth index (PDI) in the patient group were significantly lower than those in the healthy group during the menstrual phase (P < 0.01 and <0.001, respectively). According to univariate logistic regression results, the PTI, PDI and optimal applied pressure (OAP) were significantly correlated with PD, and the model based on the PTI and OAP performed best (AUC = 0.828). This study is the first to analyze pulse tension inferred from the PTI and to apply this parameter to clinical practice. The results of this study confirmed the possibility of quantitatively measuring pulse tension and suggest that the PTI and OAP can serve as potential clinical indicators for pain disorders.

The radial artery pulse is one of the major diagnostic indices used clinically in both Eastern and Western medicine. One of the prominent methods for measuring the radial artery pulse is the piezoresistive sensor array. Independence among channels and an appropriate sensor arrangement are important for effectively assessing the spatial-temporal information of the pulse. This study developed a circular-type seven-channel piezoresistive sensor array using face-down bonding (FDB) as one of the sensor combination methods. The three-layered housing structure that included independent pressure sensor units using the FDB method not only enabled elimination of the crosstalk among channels, but also allowed various array patterns to be created for effective pulse measurement. The sensors were arranged in a circular-type arrangement such that they could estimate the direction of the radial artery and precisely measure the pulse wave. The performance of the fabricated sensor array was validated by evaluating the sensor sensitivity per channel, and the possibility of estimating the blood vessel direction was demonstrated through a radial artery pulse simulator. We expect the proposed sensor to allow accurate extraction of the pulse indices for pulse diagnosis.

The aim of this study was to develop a robust algorithm to quantify pulse sharpness that can complement the limitations of radial augmentation index (rAIx) and explore the role of this quantitative sharpness index in reflecting vascular aging or arterial stiffness. The pulse sharpness index (PSI) was developed by combining the end point angle and virtual height, and 528 radial pulses were analyzed. The PSI could be uniformly applied to various waveform morphologies, even those with no or vague tidal waves, unlike the rAIx. Significant sex differences were identified in the rAIx and PSI (P < 0.01 for both), and significant age-dependent decreases in the PSI were observed (P < 0.01). In addition, the PSI and age were correlated (r = − 0.550) at least as strong as the rAIx and age (r = 0.532), and the PSI had a significant negative correlation with arterial stiffness (r = − 0.700). Furthermore, the multiple linear regression model for arterial stiffness using the PSI, age, sex and heart rate showed the excellent performance (cross-validated R² = 0.701), and the PSI was found to have the greatest influence on arterial stiffness. This study confirmed that the PSI could be a quantitative index of vascular aging and has potential for use in inferring arterial stiffness with an advantage over the rAIx.