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A Wireless Respiratory Monitoring System Using a Wearable Patch sensor Network

IEEE sensorS JOURNAL 2019年第2期19卷 650-657页

作者： Elfaramawy, Tamer Fall, Cheikh Latyr Arab, Soodeh Morissette, Martin Lellouche, Francois Gosselin, Benoit Univ Laval Dept Elect & Comp Engn Quebec City PQ G1V 0A6 Canada OxyNov Inc Quebec City PQ G2J 0C4 Canada Univ Laval Res Ctr IUCPQ Quebec City PQ G1V 0A6 Canada

Wireless body sensors are increasingly used by clinicians and researchers in a wide range of applications, such as sports, space engineering, and medicine. Monitoring vital signs in real time can dramatically increase diagnosis accuracy and enable automatic curing procedures, e.g., detect and stop epilepsy or narcolepsy seizures. Breathing parameters are critical in oxygen therapy, hospital, and ambulatory monitoring, while the assessment of cough severity is essential when dealing with several diseases, such as chronic obstructive pulmonary disease. In this paper, a low-power wireless respiratory monitoring system with cough detection is proposed to measure the breathing rate and the frequency of coughing. This system uses wearable wireless multimodal patch sensors, designed using off-the-shelf components. These wearable sensors use a low-power nine-axis inertial measurement unit to quantify the respiratory movement and a MEMs microphone to record audio signals. Data processing and fusion algorithms are used to calculate the respiratory frequency and the coughing events. The architecture of each wireless patch-sensor is presented. In fact, the results show that the small 26.67 x 65.53 mm(2) patch-sensor consumes around 12-16.2 mA and can last at least 6 h with a miniature 100-mA lithium ion battery. The data processing algorithms, the acquisition, and wireless communication units are described. The proposed network performance is presented for experimental tests with a freely behaving user in parallel with the gold standard respiratory inductance plethysmography.

关键词： Breathing rate coughing detection inertial measurement unit wireless real-time low-power wearable patch sensors network data fusion

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Multi-sensor-fusion System for People Counting applications 1

Multi-Sensor-Fusion System for People Counting Applications

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1st International Conference on Societal Automation (SA)

作者： Stec, Michal Herrmann, viktor Stabernack, Benno Fraunhofer Heinrich Hertz Inst HHI Embedded Syst Grp Berlin Germany Univ Potsdam Embedded Syst Architectures Signal Proc Potsdam Germany

ISBN: (纸本)9781728133454

For economical as well as environmental reasons, logistical planning and efficient assignment of transport vehicles in public transportation need a precise knowledge of passenger utilization. To provide reliable figures sophisticated counting methods are demanded. Previously developed systems, mostly using a single 2D image sensor or a 3D depth sensor, can not fully achieve the required accuracy. In this paper, we present a robust people counting algorithm, based on multi sensor data fusion. Our solution runs on embedded systems with reasonable requirements with respect to computational power. 3D distance information, obtained from the ToF system, is used to perform the basic detection of objects. Once detected, the objects get additional classification features exploiting the data provided by a RGB camera and an IR thermal sensor. We describe the current state of fusing and processing of the collected data including the detection, classification (vital, non-vital), as well as sequential tracking and counting. We provide current counting results along with insights to future development concepts to improve the stated algorithms especially in terms of vital, nonvital classification and object recognition.

关键词： Multi sensor fusion 3D vision

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Soft body sensor networks: architectures and applications

Soft body sensor networks: Architectures and Applications

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IEEE International Conference on Networking, Sensing and Control

作者： Wentao Dong Xiao Cheng Daojin Yao School of Electrical and Automation Engineering East China Jiaotong University Nanchang China Rail Transportation Technology Innovation Center East China Jiaotong University Nanchang China

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

Body sensor networks (BSNs) are designed to collect, process, and transmit the biological data from different parts of human body from wearable electronics with limited resources. Conventional BSN node is also designed and fabricated by the rigid sensors, printed circuit board (PCB), and integrated chip (IC), which are not compatible with the soft human skin. The concepts of soft body sensor networks (SBSNs) are given in the manuscript based on wireless sensor networks and flexible electronics. SBSN node is composed of soft sensors, flexible data modulation and process unit and flexible wireless communication unit, and all the components of SBSN node are designed to be bended and be compatible with soft skin surface by flexible electronic. The architecture of SBSNs are built with several layers: soft sensors, data collection, wireless communication, body could, data fusion algorithm and monitoring interface for further online healthy monitoring. Multisensory decision fusion algorithm has been presented with biometric and medical monitoring applications which is subsequently analyzed for medical diagnosis. Emotion recognitions are realized to predict healthy state based on SBSNs using the intelligent data fusion algorithms.

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Towards Mobile Sensing with Event Cameras on High-agility Resource-constrained Devices: A Survey

arXiv

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arXiv 2025年

作者： Wang, Haoyang Guo, Ruishan Ma, Pengtao Ruan, Ciyu Luo, Xinyu Ding, Wenhua Zhong, Tianyang Xu, Jingao Liu, Yunhao Chen, Xinlei Shenzhen International Graduate School Tsinghua University Shenzhen China Computer Science Department of Carnegie Mellon University United States Global Innovation Exchange Tsinghua University Beijing China Department of Automation Tsinghua University Beijing China PengCheng Laboratory Shenzhen China RISC-V International Open Source Laboratory Shenzhen China

With the increasing complexity of mobile device applications, these devices are evolving toward high agility. This shift imposes new demands on mobile sensing, particularly in terms of achieving high accuracy and low latency. Event-based vision has emerged as a disruptive paradigm, offering high temporal resolution, low latency, and energy efficiency, making it well-suited for high-accuracy and low-latency sensing tasks on high-agility platforms. However, the presence of substantial noisy events, the lack of inherent semantic information, and the large data volume pose significant challenges for event-based data processing on resource-constrained mobile devices. This paper surveys the literature over the period 2014-2024, provides a comprehensive overview of event-based mobile sensing systems, covering fundamental principles, event abstraction methods, algorithmic advancements, hardware and software acceleration strategies. We also discuss key applications of event cameras in mobile sensing, including visual odometry, object tracking, optical flow estimation, and 3D reconstruction, while highlighting the challenges associated with event data processing, sensor fusion, and real-time deployment. Furthermore, we outline future research directions, such as improving event camera hardware with advanced optics, leveraging neuromorphic computing for efficient processing, and integrating bio-inspired algorithms to enhance perception. To support ongoing research, we provide an open-source Online Sheet with curated resources and recent developments. We hope this survey serves as a valuable reference, facilitating the adoption of event-based vision across diverse applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Data reduction

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System-level Simulation of Cooperative sensor Data fusion Strategies for Improved vulnerable Road Users Safety 16

System-level Simulation of Cooperative Sensor Data Fusion St...

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16th Workshop on Positioning, Navigation and Communications (WPNC)

作者： da Silva, Alex Pereira Brahmi, Imane Horiya Leirens, Sylvain Denis, Benoit CEA Leti Minatec Campus17 Ave Martyrs F-38054 Grenoble 9 France

ISBN: (纸本)9781728120829

Cooperation between vehicles and/or with static elements of the road infrastructure enables a wide number of applications and services, such as traffic monitoring and prediction, localization and mapping, or novel safety approaches for vulnerable road users. For instance, relying on on-board sensors, on conventional navigation systems, and on v2X wireless connectivity, vehicles can represent geo-tagged measurements (e.g., LiDAR) in the form of local occupancy grid maps accounting for the presence of obstacles. The latter maps can be subsequently shared, either directly (e.g., with other fellow vehicles around) or via a centralized entity (e.g., edge cloud...). Through cooperative fusion, equipped vehicles thus contribute to elaborate a global view of the physical environment. In this paper, we first describe a flexible end-to-end system simulator that can evaluate such cooperative mapping strategies in complex road driving environments. The overall simulation flow spans from sensor and v2X connectivity abstractions up to fusion algorithms running at the application level. We then present a few illustrating simulation results in a smart intersection scenario, confirming the importance of v2X-aided cooperation to enhance the physical perception of standalone vehicles in terms of both coverage and detection performances.

关键词： vehicles

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Realization and performance assessment of a force-sensing based smart floor panel for indoor localization applications

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sensorS AND ACTUATORS A-PHYSICAL 2019年 285卷 468-481页

作者： Cheng, Chung-Hao Wu, Ming-Feng Guo, Shu-Heng Chen, Kuo-Shen Natl Cheng Kung Univ Dept Mech Engn 1 Dasyue Rd Tainan 701 Taiwan

Accurate position detection of indoor objects is crucial for many intelligent life applications and can be realized by various approaches. In certain applications, indoor position detection can be performed using some forms of touch-based floor sensing systems to avoid problems faced by using vision or inertial navigation approaches. The present study develops a floor panel test stage (1 x 1 m(2)) and its associated localization schemes based on rigid body statics for evaluating the feasibility and the positioning performance on determining the indoor locations of moving objects such as mobile robots. The motion signals are detected by four load cells located at the panel corners and are used to determine the position of the applied forces by means of rigid body statics. Essential tests are performed to examine the system performance. Noticed that due to the existence of boundary reaction moments, traditional predictions based on rigid body statics may not be sufficient and a calibration procedure is required. In parallel, for accommodating different possible scenarios, the corresponding associated localization schemes for estimating the force-applied locations based on the readout history and algorithms are also proposed and realized. The results indicate that the localization accuracy is approximately +/- 1 cm over a 1 m span after calibration. Although the method is essentially static, it can still detect object motion provided the motion frequency less than 2 Hz. Furthermore, demonstrations are also presented to highlight other possible applications such as center of gravity measurement of objects and the fusion of multiple localization schemes in indoor environment. Finally, an indoor localization demonstration based on both wiimote IR LED and this smart floor is presented to elucidate the possible application of this work in sensor fusion for indoor motion control. (C) 2018 Elsevier B.v. All rights reserved.

关键词： Localization Load-cell Smart floor Touch panel Force sensing

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Dynamic buffer sizing for out-of-order event compensation for time-sensitive applications

arXiv

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arXiv 2020年

作者： Weiss, Wolfgang Expósito Jiménez, víctor J. Zeiner, Herwig JOANNEUM RESEARCH Forschungsgesellschaft mbH Austria VIRTUAL VEHICLE Research GmbH Austria

Today’s sensor network implementations often comprise various types of nodes connected with different types of networks. These and various other aspects influence the delay of transmitting data and therefore of out-of-order data occurrences. This turns into a crucial problem in time-sensitive applications where data must be processed promptly and decisions must be reliable. In this paper, we were researching dynamic buffer sizing algorithms for multiple, distributed and independent sources, which reorder event streams, thus enabling subsequent time-sensitive applications to work correctly. To be able to evaluate such algorithms, we had to record datasets first. Five novel dy namic buffer sizing algorithms were implemented and compared to state-of-the-art approaches in this domain. The evaluation has shown that the use of a dynamic time-out buffering method is preferable over a static buffer. The higher the variation of the network or other influences in the environment, the more necessary it becomes to use an algorithm which dynamically adapts its buffer size. These algorithms are universally applicable, easy to integrate in existing architectures, and particularly interesting for time-sensitive applications. Dynamic time-out buffering is still a trade-off between reaction time and out-of-order event compensation. Copyright © 2020, The Authors. All rights reserved.

关键词： Economic and social effects

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Autonomous Unmanned Heterogeneous vehicles for Persistent Monitoring

Autonomous Unmanned Heterogeneous Vehicles for Persistent Mo...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Shin, H. Y. Tsourdos, A. Lappas, v Ampatzoglou, A. Kostopoulos, v Bertrand, S. Marzat, J. Piet-Lahanier, H. Lindgren, D. Detratti, M. Cranfield Univ Sch Aerosp Transport & Mfg Cranfield Beds England Univ Patras Dept Mech Engn & Aeronaut Patras Greece Off Natl Etud & Rech Aerosp Palaiseau France Swedish Def Res Agcy FOI Stockholm Sweden European Def Agcy EDA Brussels Belgium

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

Swarms of unmanned vehicles (air and ground) can increase the efficiency and effectiveness of military and law enforcement operations by enhancing situational awareness and allow the persistent monitoring of multiple hostile targets. The key focus in the development of the enabling technologies for swarm systems, is the minimisation of uncertainties in situational awareness information for surveillance operations supported by a 'system of systems' composed by static and mobile heterogeneous sensors. The identified critical enabling techniques and technologies for adaptive, informative and reconfigurable operations of unmanned swarm systems are: Robust Static sensor network design, mobile sensor tasking (including re-allocation), sensor fusion, Information fusion including behaviour monitoring. The work presented in this paper describes one of the first attempts to integrate all swarm related technologies into a practical demonstration, demonstrating the benefits of swarms of heterogeneous vehicles for defence applications used for the persistent monitoring of high value assets such as military installations and camps. The key enabling swarm system technologies are analysed and novel algorithms are developed and presented, which can be implemented in COTS based unmanned vehicles available today and have thus been designed and optimised to require small computational power, be flexible, reconfigurable and which can be implemented in a large range of commercially available unmanned vehicles (air and ground).

关键词： Infrared sensors Unmanned vehicles Neural Network Methods Model Predictive Control Greedy Algorithm Yaw Unmanned Ground vehicle Inertial Measurement Unit Autonomous Systems Numerical Optimization

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Focussing Learned Image Compression to Semantic Classes for v2X applications

Focussing Learned Image Compression to Semantic Classes for ...

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IEEE Symposium on Intelligent vehicle

作者： Jonas Löhdefink Andreas Bär Nico M. Schmidt Fabian Hüger Peter Schlicht Tim Fingscheidt Institute for Communications Technology Technische Universität Braunschweig Braunschweig Germany Volkswagen Group Innovation Wolfsburg Germany

ISBN: (数字)9781728166735

ISBN: (纸本)9781728166742

Cooperative perception with many sensors involved greatly improves the performance of perceptual systems in autonomous vehicles. However, the increasing amount of sensor data leads to a bottleneck due to limited capacity of vehicle-to-X (v2X) communication channels. We leverage lossy learned image compression by means of an autoencoder with adversarial loss function to reduce the overall bitrate. Our key contribution is to focus image compression on regions of interest (ROIs) governed by a binary mask. A transmitter-sided semantic segmentation network extracts semantically important classes being the basis for the generation of a ROI. A second key contribution is that the mask is not transmitted as side information, only the quantized bottleneck data is transmitted. To train the network, we use a loss function operating only on the pixels in the ROI. We report peak-signal-to-noise ratio (PSNR) both in the entire image and only in the ROI, evaluating various fusion architectures and fusion operations involving input image and mask. Showing the high generalizability of our approach, we achieve consistent improvements in the ROI in all experiments on the Cityscapes dataset.

关键词： Image coding Semantics Image segmentation Image reconstruction sensors Receivers Generative adversarial networks

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fusion of Data from Radar and Depth sensors Applied for Healthcare-Oriented Characterization of Persons’ Gait

Fusion of Data from Radar and Depth Sensors Applied for Heal...

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Signal Processing algorithms, architectures, Arrangements and applications (SPA)

作者： Paweł Mazurek Jakub Wagner Roman Z. Morawski Faculty of Electronics and Information Technology Institute of Radioelectronics and Multimedia Technology Warsaw University of Technology Warsaw Poland

ISBN: (纸本)9781728139906

The research reported in this paper is related to the fusion of measurement data from the impulse-radar sensors and infrared depth sensors applied in a system for unobtrusive monitoring of elderly persons. The performance of monitoring systems, based on both types of sensors - when used separately and when used in combination - has been compared with respect to their potential for decreasing the uncertainty of estimation of several quantities, carrying information important for medical and healthcare services, viz. the state of being in motion, the direction of the movement, the travelled distance and the mean walking speed. The results of the numerical experimentation - performed on real-world data - show that the fusion of data enables more robust and accurate estimation of those parameters, and therefore more reliable monitoring of elderly persons.

关键词： Monitoring Legged locomotion sensor fusion Estimation Radar Biomedical monitoring

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