Rehabilitation Assessment System for Stroke Patients Based on Fusion-Type Optoelectronic Plethysmography Device and Multi-Modality Fusion Model: Design and Validation.

This study aimed to propose a portable and intelligent rehabilitation evaluation system for digital stroke-patient rehabilitation assessment. Specifically, the study designed and developed a fusion device capable of emitting red, green, and infrared lights simultaneously for photoplethysmography (PPG) acquisition. Leveraging the different penetration depths and tissue reflection characteristics of these light wavelengths, the device can provide richer and more comprehensive physiological information. Furthermore, a Multi-Channel Convolutional Neural Network-Long Short-Term Memory-Attention (MCNN-LSTM-Attention) evaluation model was developed. This model, constructed based on multiple convolutional channels, facilitates the feature extraction and fusion of collected multi-modality data. Additionally, it incorporated an attention mechanism module capable of dynamically adjusting the importance weights of input information, thereby enhancing the accuracy of rehabilitation assessment. To validate the effectiveness of the proposed system, sixteen volunteers were recruited for clinical data collection and validation, comprising eight stroke patients and eight healthy subjects. Experimental results demonstrated the system's promising performance metrics (accuracy: 0.9125, precision: 0.8980, recall: 0.8970, F1 score: 0.8949, and loss function: 0.1261). This rehabilitation evaluation system holds the potential for stroke diagnosis and identification, laying a solid foundation for wearable-based stroke risk assessment and stroke rehabilitation assistance.

[Traditional Chinese medicine used as anti-aging agent by targeting nuclear factor erythroid 2-related factor 2 signaling pathway].

The imbalance of redox homeostasis is a major characteristic of aging and contributes to the pathogenesis of various aging-related diseases. As a regulatory hub of redox homeostasis, nuclear factor erythroid 2-related factor 2 (NRF2) can attenuate oxidative stress by activating the transcription of many antioxidant enzymes. China is the birthplace of traditional Chinese medicine (TCM) which has been wildly used as medicine for thousands of years. Recently, TCM as anti-aging medicine has attracted enormous attention. Focusing on the NRF2 signaling pathway, this paper summarizes the correlation between various anti-aging TCM and the NRF2 signaling, and discusses the common key mechanisms by which TCM slows the aging process by targeting the NRF2 signaling network.

Photoplethysmography Driven Hypertension Identification: A Pilot Study.

To prevent and diagnose hypertension early, there has been a growing demand to identify its states that align with patients. This pilot study aims to research how a non-invasive method using photoplethysmographic (PPG) signals works together with deep learning algorithms. A portable PPG acquisition device (Max30101 photonic sensor) was utilized to (1) capture PPG signals and (2) wirelessly transmit data sets. In contrast to traditional feature engineering machine learning classification schemes, this study preprocessed raw data and applied a deep learning algorithm (LSTM-Attention) directly to extract deeper correlations between these raw datasets. The Long Short-Term Memory (LSTM) model underlying a gate mechanism and memory unit enables it to handle long sequence data more effectively, avoiding gradient disappearance and possessing the ability to solve long-term dependencies. To enhance the correlation between distant sampling points, an attention mechanism was introduced to capture more data change features than a separate LSTM model. A protocol with 15 healthy volunteers and 15 hypertension patients was implemented to obtain these datasets. The processed result demonstrates that the proposed model could present satisfactory performance (accuracy: 0.991; precision: 0.989; recall: 0.993; F1-score: 0.991). The model we proposed also demonstrated superior performance compared to related studies. The outcome indicates the proposed method could effectively diagnose and identify hypertension; thus, a paradigm to cost-effectively screen hypertension could rapidly be established using wearable smart devices.

Illumination Adaptation in a Multi-Wavelength Opto-Electronic Patch Sensor.

In capturing high-quality photoplethysmographic signals, it is crucial to ensure that appropriate illumination intensities are used. The purpose of the study was to deliver controlled illumination intensities for a multi-wavelength opto-electronic patch sensor that has four separate arrays each consisting of four light-emitting diodes (LEDs), the wavelength of the light generated by each array being different. The study achieved the following: (1) a linear constant current source LED driver incorporating series negative feedback using an integrated operational amplifier circuit; (2) the fitting of a linear regression equation to provide rapid determination of the LEDs driver voltage; and (3) an algorithm for the automatic adjustment of the output voltage to ensure suitable LED illumination. The data from a single centrally-located photo detector, which is capable of capturing all four channels of back-light in a time-multiplexed manner, were used to monitor heart rate and blood oxygen saturation. This paper provides circuitry for driving the LEDs and describes an adaptive algorithm implemented on a microcontroller unit that monitors the quality of the photo detector signals received in order to control each of the individual currents being supplied to the LED arrays. The study demonstrated that the operation of the new circuitry in its ability to adapt LED illumination to the strength of the signal received and the performance of the adaptive system was compared with that of a non-adaptive approach.

Oxygen Saturation Measurements from Green and Orange Illuminations of Multi-Wavelength Optoelectronic Patch Sensors.

Photoplethysmography (PPG) based pulse oximetry devices normally use red and infrared illuminations to obtain oxygen saturation (SpO2) readings. In addition, the presence of motion artefacts severely restricts the utility of pulse oximetry physiological measurements. In the current study, a combination of green and orange illuminations from a multi-wavelength optoelectronic patch sensor (mOEPS) was investigated in order to improve robustness to subjects' movements in the extraction of SpO2 measurement. The experimental protocol with 31 healthy subjects was divided into two sub-protocols, and was designed to determine SpO2 measurement. The datasets for the first sub-protocol were collected from 15 subjects at rest, with the subjects free to move their hands. The datasets for the second sub-protocol with 16 subjects were collected during cycling and walking exercises. The results showed good agreement with SpO2 measurements (r = 0.98) in both sub-protocols. The outcomes promise a robust and cost-effective approach of physiological monitoring with the prospect of providing health monitoring that does not restrict user physical movements.

A Multi-Wavelength Opto-Electronic Patch Sensor to Effectively Detect Physiological Changes against Human Skin Types.

Different skin pigments among various ethnic group people have an impact on spectrometric illumination on skin surface. To effectively capture photoplethysmographic (PPG) signals, a multi-wavelength opto-electronic patch sensor (OEPS) together with a schematic architecture of electronics were developed to overcome the drawback of present PPG sensor. To perform a better in vivo physiological measurement against skin pigments, optimal illuminations in OEPS, whose wavelength is compatible with a specific skin type, were optimized to capture a reliable physiological sign of heart rate (HR). A protocol was designed to investigate an impact of five skin types in compliance with Von Luschan's chromatic scale. Thirty-three healthy male subjects between the ages of 18 and 41 were involved in the protocol implemented by means of the OEPS system. The results show that there is no significant difference (p: 0.09, F = 3.0) in five group tests with the skin types across various activities throughout a series of consistent measurements. The outcome of the present study demonstrates that the OEPS, with its multi-wavelength illumination characteristics, could open a path in multiple applications of different ethnic groups with cost-effective health monitoring.