Classification accuracy of pain intensity induced by leg blood flow restriction during walking using machine learning based on electroencephalography.

Pain assessment in clinical practice largely relies on patient-reported subjectivity. Although previous studies using fMRI and EEG have attempted objective pain evaluation, their focus has been limited to resting conditions. This study aimed to classify pain levels during movement using a wearable device with three forehead electrodes and advanced machine learning.

Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device.

Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, emphasizing the need for accessible, cost-effective, and noninvasive diagnostic tools. Electroencephalography (EEG) is a promising biomarker, but traditional systems are limited by size, cost, and the need for skilled technicians. This study proposes a deep-learning-based approach using data from a portable EEG device to distinguish healthy volunteers (HVs) from patients with dementia-related conditions.

Analyses of Menopause and Its Related Symptoms on Sleep Quality Using a Novel Wearable Sheet-Type Frontal Electroencephalography Sensor, Haru-1.

Objectives: Menopause affects sleep quality and contributes to depressive symptoms, but its precise impact on sleep remains unclear. To address this gap, we conducted detailed measurements of brain activity during sleep in pre- and postmenopausal women using a novel wearable sheet-type frontal electroencephalography (EEG) patch, Haru-1 (PGV Inc., Tokyo, Japan).

Estimation of the Stages of Labor Using a Multichannel Electrohysterogram Sensor and Conditional Variational Autoencoder.

The electrohysterogram (EHG) is a type of electromyogram that measures potential changes produced by the smooth muscle of the uterus. Similar to the electrical activity of cardiac and skeletal muscle, EHG manifests as alterations in body surface potentials. It offers a less invasive alternative and is expected to identify preterm labor and abnormal deliveries.

Masseter and digastric muscle activity evaluation using a novel electromyogram that utilizes elastic sheet electrodes.

Purpose: To evaluate the reproducibility and reliability of a novel electromyogram (EMG) device with a flexible sheet sensor for measuring muscle activity related to mastication and swallowing.

Methods: We developed a new EMG device made of elastic sheet electrodes to measure the masseter and digastric muscle activities for evaluating mastication and swallowing. To examine the measurement reproducibility of the new EMG device, masseter muscle activity was analyzed using the intraclass correlation coefficient (ICC).

Predictive Diagnostic Approach to Dementia and Dementia Subtypes Using Wireless and Mobile Electroencephalography: A Pilot Study.

Background: Developing a screening method for mild cognitive impairment in the aging population and intervening early in the progression of dementia based on such a method, remains challenging. Electroencephalography (EEG) is a noninvasive and sensitive tool to assess the functional activity of the brain, and wireless and mobile EEG (wmEEG) could serve as an alternative screening technique that is widely tolerable in patients with dementia from the preclinical to severe stage.

Materials And Methods: Using wmEEG, we recorded bioelectrical activity (BA) from the forehead in 101 individuals with dementia and nondementia controls (NCs) during 4 tasks and investigated which task could differentiate dementia from NC.

Wireless Monitoring Using a Stretchable and Transparent Sensor Sheet Containing Metal Nanowires.

Mechanically and visually imperceptible sensor sheets integrated with lightweight wireless loggers are employed in ultimate flexible hybrid electronics (FHE) to reduce vital stress/nervousness and monitor natural biosignal responses. The key technologies and applications for conceptual sensor system fabrication are reported, as exemplified by the use of a stretchable sensor sheet completely conforming to an individual's body surface to realize a low-noise wireless monitoring system (<1 µV) that can be attached to the human forehead for recording electroencephalograms. The above system can discriminate between Alzheimer's disease and the healthy state, thus offering a rapid in-home brain diagnosis possibility.

Highly-ordered Triptycene Modifier Layer Based on Blade Coating for Ultraflexible Organic Transistors.

We present a highly ordered surface modification layer for polymers based on ambient solution-processed triptycene (Trip) derivatives for high-mobility organic thin-film transistors (OTFTs). The nested packing of Trip molecules results in the formation of 2D hexagonal arrays, which stack one-dimensionally on the surface of polymer dielectrics without anchoring groups. The Trip surface was previously shown to be preferable for the growth of organic semiconductors (OSCs), and hence for enhancing the mobility of OTFTs.

Fine printing method of silver nanowire electrodes with alignment and accumulation.

One-dimensional metal nanowires offer great potential in printing transparent electrodes for next-generation optoelectronic devices such as flexible displays and flexible solar cells. Printing fine patterns of metal nanowires with widths <100 μm is critical for their practical use in the devices. However, the fine printing of metal nanowires onto polymer substrates remains a major challenge owing to their unintended alignment.

Potential Clinical Applications and Future Prospect of Wireless and Mobile Electroencephalography on the Assessment of Cognitive Impairment.

Electroencephalography (EEG) systems have been used for assessing cognitive function in dementia for several decades. Studies have demonstrated that EEG in Alzheimer's disease (AD) patients is generally characterized by significant and specific increases in delta and theta power, a decrease in alpha power, and a decrease in the coherence of the fast bands between different brain areas linked by long corticocortical fibers. Posterior EEG characteristics in dementia with Lewy bodies (DLB) allowed discrimination of DLB from AD and controls with high accuracy.

Long-Term Implantable, Flexible, and Transparent Neural Interface Based on Ag/Au Core-Shell Nanowires.

Neural interfaces enabling light transmittance rely on optogenetics to control and monitor specific neural activity, thereby facilitating deeper understanding of intractable diseases. This study reports the material strategy underlying an optogenetic neural interface comprising stretchable and transparent conductive tracks and capable of demonstrating high biocompatibility after long-term (5-month) implantation. Ag/Au core-shell nanowires contribute toward improving track performance in terms of stretchability (<60% strain), transparency (<83%), and electrical resistance (15 Ω sq ).

Flexible organic TFT bio-signal amplifier using reliable chip component assembly process with conductive adhesive.

This paper presents a flexible organic thin-film transistor (OTFT) amplifier for bio-signal monitoring and presents the chip component assembly process. Using a conductive adhesive and a chip mounter, the chip components are mounted on a flexible film substrate, which has OTFT circuits. This study first investigates the assembly technique reliability for chip components on the flexible substrate.

Flexible sensor sheet for real-time pressure monitoring in artificial knee joint during total knee arthroplasty.

As described in this paper, we propose a sheet-type pressure sensor to support assistive technology for artificial knee joint replacement. The proposed pressure sensor consists of two sheets: an electrode sheet with metal wiring and a flexible polymer-based insulating layer on 80 μm polyimide film, as well as a pressure-sensitive conductive sheet that can function as a pressure-to-resistance sensor. We developed a 5 cm × 7 cm pressure sensor sheet with 116 sensing points.

Normally Off ECG SoC With Non-Volatile MCU and Noise Tolerant Heartbeat Detector.

This paper describes an electrocardiograph (ECG) monitoring SoC using a non-volatile MCU (NVMCU) and a noise-tolerant instantaneous heartbeat detector. The novelty of this work is the combination of the non-volatile MCU for normally off computing and a noise-tolerant-QRS (heartbeat) detector to achieve both low-power and noise tolerance. To minimize the stand-by current of MCU, a non-volatile flip-flop and a 6T-4C NVRAM are used.