Xiaying Wang
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View article: Patient demographics, medical factors, treatment modalities and satisfaction at five traditional Chinese medicine practices in Switzerland: A cross-sectional study
Patient demographics, medical factors, treatment modalities and satisfaction at five traditional Chinese medicine practices in Switzerland: A cross-sectional study Open
Background Traditional Chinese Medicine (TCM) is increasingly integrated into healthcare and insurance systems, therefore, it is essential to understand its current status and patients’ perspectives. Methods This cross-sectional study was …
View article: RAS-RH up-regulates the level of miR-126 and inhibits the opening of mPTP in a rat model of coronary microvascular disease
RAS-RH up-regulates the level of miR-126 and inhibits the opening of mPTP in a rat model of coronary microvascular disease Open
RAS-RH effectively ameliorates X-ray radiation-induced CMVD by modulating miR-126 expression to inhibit pathological opening of the mPTP in endothelial cells. This finding provides novel mechanistic evidence supporting RAS-RH as a therapeu…
View article: Development of a core outcome set for the trials of complementary therapies in people with multiple sclerosis: international survey and consensus meetings
Development of a core outcome set for the trials of complementary therapies in people with multiple sclerosis: international survey and consensus meetings Open
Objectives This study aimed to develop a core outcome set (COS) for trials evaluating the effects of complementary therapies in people with multiple sclerosis (pwMS). We sought to identify the outcomes most relevant to pwMS, their relative…
View article: Daith Piercing, a Social Media Hype on Youtube for the Treatment of Migraine? A Systematic Video Analysis
Daith Piercing, a Social Media Hype on Youtube for the Treatment of Migraine? A Systematic Video Analysis Open
Background and Aims Nowadays, the social media video‐sharing website YouTube is globally accessible and used for sharing news and information. It also serves as a tool for migraine sufferers seeking guidance about Daith piercing (DP) as a …
View article: FEMBA: Efficient and Scalable EEG Analysis with a Bidirectional Mamba Foundation Model
FEMBA: Efficient and Scalable EEG Analysis with a Bidirectional Mamba Foundation Model Open
Accurate and efficient electroencephalography (EEG) analysis is essential for detecting seizures and artifacts in long-term monitoring, with applications spanning hospital diagnostics to wearable health devices. Robust EEG analytics have t…
View article: Daith piercing, a social media hype on YouTube for the treatment of migraine? A systematic video analysis of quality and reliability
Daith piercing, a social media hype on YouTube for the treatment of migraine? A systematic video analysis of quality and reliability Open
Background Nowadays, social media video-sharing website YouTube is globally accessible and used for sharing news and information. It also serves as a tool for migraine sufferers seeking guidance about Daith piercing as a potential migraine…
View article: CEReBrO: Compact Encoder for Representations of Brain Oscillations Using Efficient Alternating Attention
CEReBrO: Compact Encoder for Representations of Brain Oscillations Using Efficient Alternating Attention Open
Electroencephalograph (EEG) is a crucial tool for studying brain activity. Recently, self-supervised learning methods leveraging large unlabeled datasets have emerged as a potential solution to the scarcity of widely available annotated EE…
View article: A chronological overview of common Chinese medicine treatment methods
A chronological overview of common Chinese medicine treatment methods Open
This overview provides a synopsis of the history and development of Traditional Chinese Medicine (TCM) treatment methods, highlighting its foundational principles and key modalities. While certain concepts are exclusive to TCM, other appli…
View article: EnhancePPG: Improving PPG-based Heart Rate Estimation with Self-Supervision and Augmentation
EnhancePPG: Improving PPG-based Heart Rate Estimation with Self-Supervision and Augmentation Open
Heart rate (HR) estimation from photoplethysmography (PPG) signals is a key feature of modern wearable devices for health and wellness monitoring. While deep learning models show promise, their performance relies on the availability of lar…
View article: Patient demographics, medical factors, treatment modalities and satisfaction at five traditional Chinese medicine practices: A cross-sectional study.
Patient demographics, medical factors, treatment modalities and satisfaction at five traditional Chinese medicine practices: A cross-sectional study. Open
BACKGROUND: Traditional Chinese Medicine (TCM) is increasingly integrated into healthcare and insurance systems, therefore, it is essential to understand its current status and patients perspectives. METHODS: This cross-sectional study was…
View article: <scp>SzCORE</scp>: Seizure Community Open‐Source Research Evaluation framework for the validation of <scp>electroencephalography</scp>‐based automated seizure detection algorithms
<span>SzCORE</span>: Seizure Community Open‐Source Research Evaluation framework for the validation of <span>electroencephalography</span>‐based automated seizure detection algorithms Open
The need for high‐quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long‐term EEG monitoring. Heterogeneity in validation methods of th…
View article: Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine Interfaces
Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine Interfaces Open
Brain-machine interfaces (BMIs) are expanding beyond clinical settings thanks to advances in hardware and algorithms. However, they still face challenges in user-friendliness and signal variability. Classification models need periodic adap…
View article: An Ultra-Low Power Wearable BMI System With Continual Learning Capabilities
An Ultra-Low Power Wearable BMI System With Continual Learning Capabilities Open
Driven by the progress in efficient embedded processing, there is an accelerating trend toward running machine learning models directly on wearable Brain-Machine Interfaces (BMIs) to improve portability and privacy and maximize battery lif…
View article: Optimization and Deployment of Deep Neural Networks for PPG-based Blood Pressure Estimation Targeting Low-power Wearables
Optimization and Deployment of Deep Neural Networks for PPG-based Blood Pressure Estimation Targeting Low-power Wearables Open
PPG-based Blood Pressure (BP) estimation is a challenging biosignal processing task for low-power devices such as wearables. State-of-the-art Deep Neural Networks (DNNs) trained for this task implement either a PPG-to-BP signal-to-signal r…
View article: The First General Consent Implementation in Swiss Traditional Chinese Medicine Practices. A Prospective One-Year Study
The First General Consent Implementation in Swiss Traditional Chinese Medicine Practices. A Prospective One-Year Study Open
Summary Background Traditional Chinese Medicine (TCM) encompasses a wide range of treatments focused on diagnosing and managing illnesses, with increasing adoption in Western countries. TCM is often applied in isolated practices, therefore…
View article: Traditional Chinese Medicine Research Activity in Switzerland. A Systematic Review and Bibliometric Analysis
Traditional Chinese Medicine Research Activity in Switzerland. A Systematic Review and Bibliometric Analysis Open
Importance Traditional Chinese Medicine (TCM) becomes popular in Switzerland, however, Swiss TCM research activity and scientific output have not been investigated. Objective To describe the Swiss TCM research activities and main health co…
View article: A Spiking Neural Network Decoder for Implantable Brain Machine Interfaces and its Sparsity-aware Deployment on RISC-V Microcontrollers
A Spiking Neural Network Decoder for Implantable Brain Machine Interfaces and its Sparsity-aware Deployment on RISC-V Microcontrollers Open
Implantable Brain-machine interfaces (BMIs) are promising for motor rehabilitation and mobility augmentation, and they demand accurate and energy-efficient algorithms. In this paper, we propose a novel spiking neural network (SNN) decoder …
View article: BrainFuseNet: Enhancing Wearable Seizure Detection Through EEG-PPG-Accelerometer Sensor Fusion and Efficient Edge Deployment
BrainFuseNet: Enhancing Wearable Seizure Detection Through EEG-PPG-Accelerometer Sensor Fusion and Efficient Edge Deployment Open
This paper introduces BrainFuseNet, a novel lightweight seizure detection network based on the sensor fusion of electroencephalography (EEG) with photoplethysmography (PPG) and accelerometer (ACC) signals, tailored for low-channel count we…
View article: SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithms
SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithms Open
The need for high-quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long-term EEG monitoring. Heterogeneity in validation methods of th…
View article: Enhancing Performance, Calibration Time and Efficiency in Brain-Machine Interfaces through Transfer Learning and Wearable EEG Technology
Enhancing Performance, Calibration Time and Efficiency in Brain-Machine Interfaces through Transfer Learning and Wearable EEG Technology Open
Brain-machine interfaces (BMIs) have emerged as a transformative force in assistive technologies, empowering individuals with motor impairments by enabling device control and facilitating functional recovery. However, the persistent challe…
View article: Nonlinear and machine learning analyses on high-density EEG data of math experts and novices
Nonlinear and machine learning analyses on high-density EEG data of math experts and novices Open
Current trend in neurosciences is to use naturalistic stimuli, such as cinema, class-room biology or video gaming, aiming to understand the brain functions during ecologically valid conditions. Naturalistic stimuli recruit complex and over…
View article: Nonlinear and machine learning analyses on high-density EEG data of math experts and novices
Nonlinear and machine learning analyses on high-density EEG data of math experts and novices Open
Current trend in neurosciences is to use naturalistic stimuli, such as cinema, class-room biology or video gaming, aiming to understand the brain functions during ecologically valid conditions. Naturalistic stimuli recruit complex and over…
View article: EpiDeNet: An Energy-Efficient Approach to Seizure Detection for Embedded Systems
EpiDeNet: An Energy-Efficient Approach to Seizure Detection for Embedded Systems Open
Epilepsy is a prevalent neurological disorder that affects millions of individuals globally, and continuous monitoring coupled with automated seizure detection appears as a necessity for effective patient treatment. To enable long-term car…
View article: Exploring Automatic Gym Workouts Recognition Locally on Wearable Resource-Constrained Devices
Exploring Automatic Gym Workouts Recognition Locally on Wearable Resource-Constrained Devices Open
Automatic gym activity recognition on energy- and resource-constrained\nwearable devices removes the human-interaction requirement during intense gym\nsessions - like soft-touch tapping and swiping. This work presents a tiny and\nhighly ac…
View article: An Energy-Efficient Spiking Neural Network for Finger Velocity Decoding for Implantable Brain-Machine Interface
An Energy-Efficient Spiking Neural Network for Finger Velocity Decoding for Implantable Brain-Machine Interface Open
Brain-machine interfaces (BMIs) are promising for motor rehabilitation and mobility augmentation. High-accuracy and low-power algorithms are required to achieve implantable BMI systems. In this paper, we propose a novel spiking neural netw…
View article: Reducing neural architecture search spaces with training-free statistics and computational graph clustering
Reducing neural architecture search spaces with training-free statistics and computational graph clustering Open
The computational demands of neural architecture search (NAS) algorithms are usually directly proportional to the size of their target search spaces. Thus, limiting the search to high-quality subsets can greatly reduce the computational lo…
View article: MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain--Machine Interfaces with EEG Channel Selection
MI-BMInet: An Efficient Convolutional Neural Network for Motor Imagery Brain--Machine Interfaces with EEG Channel Selection Open
A brain--machine interface (BMI) based on motor imagery (MI) enables the control of devices using brain signals while the subject imagines performing a movement. It plays a vital role in prosthesis control and motor rehabilitation. To impr…
View article: Leveraging Tactile Sensors for Low Latency Embedded Smart Hands for Prosthetic and Robotic Applications
Leveraging Tactile Sensors for Low Latency Embedded Smart Hands for Prosthetic and Robotic Applications Open
Tactile sensing is a crucial perception mode for robots and human amputees in need of controlling a prosthetic device. Today robotic and prosthetic systems are still missing the important feature of accurate tactile sensing. This lack is m…
View article: Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces
Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces Open
Motor imagery brain--machine interfaces enable us to control machines by merely thinking of performing a motor action. Practical use cases require a wearable solution where the classification of the brain signals is done locally near the s…