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检索条件"任意字段=Conference on Advanced Signal Processing Algorithms"

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AI-Driven Sleep Apnea Detection And Prediction

AI-Driven Sleep Apnea Detection And Prediction

引用

Computational Intelligence and Computing Applications (ICCICA), International conference on

作者： Kulvinder Singh Aashita Mehta Akshat Chaudhary Department of Computer Science & Engineering Chandigarh University Mohali Punjab India

ISBN: (数字)9798350306446

ISBN: (纸本)9798350306453

Sleep apnea, a common yet underdiagnosed sleep disorder, causes a person’s breathing repeatedly stops and starts, which poses serious health risks if left untreated. Existing diagnostic methods are often inconvenient, expensive, and inaccessible to many individuals. To address these challenges, this paper introduces an AI-powered system DreamGuardian for the early detection and prediction of sleep apnea. This system utilizes a combination of machine learning algorithms and advanced signal processing techniques to analyze data from non-invasive sensors integrated into a wearable device. These sensors monitor various physiological signals during sleep, including respiratory patterns, heart rate variability, and movement, enabling comprehensive sleep analysis in real-time. The methodology that we have followed for sleep apnea detection and prediction involves acquiring a diverse dataset from sleep clinics and repositories, formatting it, and selecting key features based on existing literature. Non-invasive sensors are integrated into a wearable device prototype to monitor physiological parameters. Standardized protocols are developed for data collection, and ethical considerations are being followed. The data collected from the users will be analysed using a machine learning algorithm. The system accurately predicts the presence or absence of sleep apnea based on variables such as heart rate, BMI, age, gender, respiratory rate, ESS score, AHI, and oxygen saturation.

关键词： Technological innovation Machine learning algorithms signal processing Sleep apnea Real-time systems Biomedical monitoring Wearable devices

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Angle-Of-Arrival Target Tracking Using A Mobile Uav In External signal-Denied Environment

Angle-Of-Arrival Target Tracking Using A Mobile Uav In Exter...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Bing Zhu Sheng Xu Feng Rice Kutluyıl Doğançay Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China QinetiQ Australia Mawson Lakes SA Australia UniSA STEM University of South Australia Mawson Lakes Australia

This paper focuses on the angle-of-arrival (AOA) target tracking problem using a mobile unmanned aerial vehicle (UAV) equipped with an angle-of-arrival (AOA) sensor to observe targets in an external-denied (no global positioning system, inertial navigation system aid) environment. The mathematical formulations are based on two known anchors. The extended Kalman filter (EKF) is modified to calculate the UAV’s and target’s absolute coordinates. To improve the tracking accuracy, a gradient-based UAV path optimization algorithm using simultaneous perturbation stochastic approximation (SPSA) is developed. The geometry of anchors and UAV impacts the estimation accuracy, especially when the selected anchors are close to the target. The simulations have demonstrated the effectiveness of the proposed scheme.

关键词： Geometry Target tracking Perturbation methods Estimation signal processing algorithms signal processing Autonomous aerial vehicles

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Real-Time Sign Language and Audio Conversion Using AI

Real-Time Sign Language and Audio Conversion Using AI

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Communication, Control and Intelligent Systems (CCIS)

作者： Boobal A Loyola Jasmine J Chennama Charan Kesava Reddy Challa Akshay Reddy Chaluvadi Bala Venkata Sai Rohith Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Virudhnagar TamilNadu India

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

The appearance of audio conversion and the appearance of gesture language have greatly advanced communication technologies, especially for hearing impairment and blind. These double -purpose technologies promote communication between these groups, provide opportunities for expression and speech behind. The technology uses advanced artificial intelligence algorithms to provide real-time speech and sign language translation to improve accessibility and inclusivity. It is essential to protect data privacy, maintain the accuracy of AI models to avoid misinterpretations, and address ergonomic issues associated with long-term use. Technology converts audio entry into a gestic signal that can be seen by avatars using computer vision and natural language processing. There is a depth learning model that improves voice recognition and the acquisition of signs, and is fully adapted to many languages and sign dialects. Addressing such health and safety issues is essential to advancing the communication and optimization of this advanced technology.

关键词： Sign language Computer vision Translation Communication systems Computational modeling Auditory system Assistive technologies Real-time systems Natural language processing Convolutional neural networks

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LiDAR-Enabled Spatial Awareness for Beamforming in IRS-Assisted Wireless Communication System

LiDAR-Enabled Spatial Awareness for Beamforming in IRS-Assis...

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International Symposium on advanced Networks and Telecommunication Systems (ANTS)

作者： Ashwin Sathish Kumar Sandeep Joshi Department of Electrical and Electronics Engineering Birla Institute of Technology and Science Pilani Rajasthan India

ISBN: (数字)9798350391725

ISBN: (纸本)9798350391732

Intelligent reflecting surfaces (IRS) have emerged as a promising technology for fifth-generation and beyond wireless communication networks that enhances performance by intelligently manipulating signal propagation paths. Integrating spatial awareness into IRS operations, particularly in urban environments, presents a unique opportunity to optimize wireless communications dynamically. In this study, we propose a refined beamforming pipeline, incorporating real-time spatial adjustments based on light detection and ranging (LiDAR)-derived obstructions. The proposed model demonstrates significant improvements in achievable rates using IRS, highlighting its role in mitigating signal blockage effects. We also present an improved phase shift optimization algorithm, achieving a faster convergence speed and reducing computational overhead. The results highlight the effectiveness of integrating IRS and LiDAR technologies for vehicular networks, paving the way for adaptive beamforming techniques and facilitating the practical deployment of IRS-based systems.

关键词： Wireless communication Laser radar Array signal processing Heuristic algorithms Urban areas Pipelines Real-time systems Telecommunications Sensors Optimization

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Control Strategies for 3L-T-Type Inverter in Islanded and Grid-Tied Modes Using Controller-Hardware in the Loop

Control Strategies for 3L-T-Type Inverter in Islanded and Gr...

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International conference on Power Electronic Drives

作者： Dhiraj Kumar Yojan Sharma Aakash Singh Suvendu Samanta Department of Electrical Engineering Indian Institute of Technology Kanpur Uttar Pradesh India

ISBN: (数字)9798350372472

ISBN: (纸本)9798350372489

This paper presents the closed-loop control of a three-level T-type (3L-TNPC) inverter in both islanded and gridtied modes, with a focus on optimizing control strategies using a digital signal processor (DSP) microcontroller in conjunction with controller-hardware in the loop (C-HIL) through space vector pulse width modulation (SVPWM). The study leverages C-HIL to validate control algorithms in a realistic environment. It progresses to a comprehensive simulation phase in MATLAB/Simulink, utilizing proportional-integral (PI) control mechanisms to regulate the converter's operations. Furthermore, a 67 kVA power-rated inverter is evaluated through a C-HIL experimental setup in Typhoon HIL, an advanced real-time simulation platform. The performance of these methodologies is validated across various load types, both linear and nonlinear. The model is also tested in grid-tied mode, delivering 67 kVA of power to the grid at unity power factor (UPF). Additionally, total harmonic distortion (THD) is observed for both modes.

关键词： Space vector pulse width modulation Total harmonic distortion Tropical cyclones Microcontrollers Digital signal processors signal processing algorithms Inverters Real-time systems Mathematical models Load modeling

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Grid-integrated Photovoltaic System with Reactive and Active Power Capability

Grid-integrated Photovoltaic System with Reactive and Active...

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IEEE International conference on signal processing, Informatics, Communication and Energy Systems (SPICES)

作者： Aneetta Benny Angel Mariya K.S Ashna Pious Cinta Ann Philip Tomson Thomas Anoopraj M. R. Dept. of Electrical and Electronics Engineering St. Joseph’s College of Engineering and Technology Kottayam India

ISBN: (数字)9798350376135

ISBN: (纸本)9798350376142

The incorporation of sustainable energy sources, such as wind and solar electricity, into the contemporary power grid has presented several new management and stability issues. This paper aims to provide sustainable, efficient, and dependable power generation and distribution while taking into account the erratic and unpredictable nature of renewables. Real power control, often referred to as active power control, is the process of controlling electrical output from clean energy sources to match demand. In order to maximize power extraction from the photovoltaic (PV) array, the Perturb and Observe (P&O), a maximum power point tracking (MPPT) technique is employed to continually track and alter the duty cycle for sending switching pulses to the boost converter. A two-level inverter facilitates the AC-DC conversion with pulse-width modulation (PWM) control. A phase-locked loop (PLL) system is employed as well to synchronize the PV system at particular phase angles and frequencies with the grid. To guarantee the provision of reactive as well as active energy under a variety of operating circumstances, a specialized control circuit is meticulously built. Efficient active power control is essential to maintain grid stability and prevent frequency deviations. Reactive power control is equally crucial, as it manages voltage levels and ensures that the power system remains within permissible voltage limits. Utilizing reactive power control devices, such as capacitors and reactors, and advanced control algorithms, grid operators can maintain the system's voltage profile and minimize losses.

关键词： Photovoltaic systems Maximum power point trackers Reactive power control Power control signal processing algorithms Power system stability Stability analysis Inverters Circuit stability Voltage control

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Towards Efficient Gait Analysis Using Gyroscope: Preliminary Results and Insights

Towards Efficient Gait Analysis Using Gyroscope: Preliminary...

引用

International conference on Smart Sensors and Application (ICSSA)

作者： Thenmoli Manogar Ahmad Shakaff Ali Yeon Mohd Nor Fakhzan Mohd Kazim Shuhaida Yahud Centre of Excellence for Advanced Sensor Technology University Malaysia Perlis (UniMAP) Arau Perlis Faculty of Electrical Engineering Technology University Malaysia Perlis (UniMAP) Arau Perlis Faculty of Electronic Engineering and Technology University Malaysia Perlis (UniMAP) Arau Perlis

ISBN: (数字)9798350354294

ISBN: (纸本)9798350354300

Wearable sensor technology, combined with smartphone capabilities, has become a powerful and costeffective solution for gait analysis, offering real-time monitoring of human movements. This study introduces a sensor-based gait event detection system using gyroscope data from the publicly available MotionSense dataset to analyze walking and jogging. The dataset, which includes six subjects of varying demographics, provides a broader understanding of gait patterns. Gyroscope data from the X-axis was used to detect key biomechanical events, such as heel strikes, toe-offs, and mid-swings, as these align with the sagittal plane and are critical in understanding walking dynamics. The gait event detection algorithm The detection algorithm, developed in Python, incorporates advanced signal processing techniques like the Savitzky-Golay filter, to reduce noise while preserving key data. By using a threshold-based and sliding window methods, the system identifies gait events accurately and calculates key gait parameters such as cadence, stance time, swing time, and phase distributions. The results show significant differences between walking and jogging, with jogging exhibiting a higher cadence (82.71-90.23 steps/min) and shorter stance times (0.37-0.46 seconds) compared to walking (52.63-60.15 steps/min, stance time 0.61-0.85 seconds). This research demonstrates that wearable sensor technology offers precise and scalable alternatives to expensive, complex traditional gait analysis systems. The findings show the system's potential for clinical monitoring, rehabilitation, sports science, and smart wearable device development.

关键词： Legged locomotion Event detection Heuristic algorithms signal processing algorithms Gain measurement Gyroscopes Wearable sensors Monitoring Intelligent sensors Sports

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Graph Anomaly Detection via Multi-Scale Reconstruction of Graph Encoder-Decoder Networks

Graph Anomaly Detection via Multi-Scale Reconstruction of Gr...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Jiaqi Yu Hong Yang Peng Zhang Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Existing unsupervised graph anomaly detection (GAD) methods can be categorized into reconstruction based methods and contrastive learning based methods. The principle of reconstruction methods is to capture anomalous nodes based on data reconstruction errors. However, existing reconstruction methods are limited to a single scale reconstruction of graph structures, typically predicting edges solely based on direct connections, without considering the rich contextual information within node neighborhoods. Moreover, reconstructing original low-density inputs usually introduce noise, where the reconstruction model may overfit the anomalous data. To this end, we propose a new reconstruction based graph anomaly detection method (GADMR for short). GADMR introduces a multi-scale reconstruction, which contains both structure and feature levels. From structure level, we use a node-subgraph reconstruction method to capture the relationship between a node and their neighboring subgraphs at multiple scales. From feature level, we employ a multi-layer representation reconstruction method to facilitate the evaluation of discrepancies in high-level feature representations. Extensive experiments on six benchmark datasets show that GADMR outperforms popular anomaly detection methods.

关键词： Image edge detection Noise Neural networks Contrastive learning Reconstruction algorithms Data models Decoding Speech processing Anomaly detection Periodic structures

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A New optical diagnostics tools for grading additive manufactured parts 21

A New optical diagnostics tools for grading additive manufac...

引用

conference on Interferometry XXI

作者： Trolinger, James Davis Gao, Jian Hess, Cecil F. Lal, Amit K. Metrolaser Inc Laguna Hills CA 92653 USA Opt Measurement Syst Corp Laguna Hills CA USA

ISBN: (纸本)9781510654310;9781510654303

In previous papers, we described a diagnostics tool for additive manufacturing products that is based on the concept that the acoustical/vibrational spectrum of an object can be used as a unique signature that characterizes the material and geometry of a product sufficiently to enable its comparison with a perfect reference to identify anomalies. This enables a user to identify rogue parts, such as defective, counterfeit, suspicious or problem parts such as defective or failing to meet specifications. The instrument produces a signature by measuring, with a laser Doppler vibrometer, the vibration of surface points on the part while it is energized by a swept frequency, piezo-electric exciter. Since its first introduction, additional research and development has enhanced, automated, and moved the instrument to a new level in terms of capability and ease of use. This paper describes the latest enhancements, including improved procedures and automation to enable use by an unsophisticated user with minimum training. The latest version provides automatic signal processing and comparison of acoustical signatures of reference and test objects that provide a quantitative grade for the object in terms of material properties, geometrical anomalies, and defects. This is achieved with specially developed algorithms that employ unique types of correlation of vibrational spectra taken from different objects or spectra produced by a simulation of a perfect object. The instrument can quickly produce an optimized correlation coefficient that serves as a numeric grade for a part for identifying suspicious or problem parts such as counterfeits, defective, or failing to meet specifications. The user can set acceptance criteria and initiate a pass or fail signal that can be used for large quantity inspections. Such an instrument is expected to find widespread applications in the AM industry.

关键词： Composites Additive manufacturing Inspection Finite element methods Amplitude modulation Laser spectroscopy Optical diagnostics Optics manufacturing signal processing Nondestructive evaluation

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Test-Time Training-Free Domain Adaptation

Test-Time Training-Free Domain Adaptation

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Yongxiang Feng Weihua He Kaichao You Bing Liu Ziyang Zhang Yaoyuan Wang Minglei Li Yihang Lou Jiawei Li Guoqi Li Jianxing Liao Advanced Computing and Storage Lab Huawei Technologies Co. Ltd. School of Electronics Engineering and Computer Science Peking University China Language & Speech Innovation Lab Huawei Technologies Co. Ltd. GoTen AI Lab Department of Intelligent Vision Huawei Technologies Co. Ltd. China Department of Production Automation Development Huawei Technologies Co. Ltd. China Institute of Automation Chinese Academy of Sciences China

Deploying deep learning models to new environments is very challenging. Domain adaptation (DA) is a promising paradigm to solve the problem by collecting and adapting to unlabeled data in new environments. Though research efforts have led to steady performance improvement over the past decade, DA algorithms are still hard to deploy, as training on unlabeled new data makes tuning difficult and not feasible for inference-only devices. To make DA practical, in this paper we study a new problem named Test-time Training-Free Domain Adaptation (TTDA), where trained models must adapt to a single input (mimicking the test-time scenario) without training. By exploiting spatial activation that was previously overlooked and simply averaged out, we propose a simple method based on Feature Statistics Transformation (FST) on-the-fly for each test example. The proposed algorithm is tested in the TTDA setting on two standard DA benchmarks. Surprisingly, it surpasses or performs on par with state-of-the-art DA methods, even though they require additional training. We envision that this training-free paradigm has the potential to bring DA to embedded devices and would be of interest to audience of community.

关键词： Training Performance evaluation Adaptation models Transfer learning signal processing algorithms Statistical distributions Classification algorithms

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