scholarly journals A Robust Beat-to-Beat Artifact Detection Algorithm for Pulse Wave

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Qihan Hu ◽  
Xintao Deng ◽  
Xin Liu ◽  
Aiguo Wang ◽  
Cuiwei Yang
Keyword(s):  
Pulse Wave ◽  
Smart Cities ◽  
Detection Algorithm ◽  
Wearable Devices ◽  
Segmentation Algorithm ◽  
Artifact Detection ◽  
Physiological Conditions ◽  
Physiological Signal ◽  
Pulse Waves ◽  
Complex Algorithm

With the rise of the concept of smart cities and healthcare, artificial intelligence helps people pay increasing attention to the health of themselves. People can wear a variety of wearable devices to monitor their physiological conditions. The pulse wave is a kind of physiological signal which is widely applied in the physiological monitoring system. However, the pulse wave is susceptible to artifacts, which prevents its popularization. In this work, we propose a novel beat-to-beat artifact detection algorithm, which performs pulse wave segmentation based on wavelet transform and then detects artifacts beat by beat based on the decision list. We verified our method on data acquired from different databases and compared with experts’ annotations. The segmentation algorithm achieved an accuracy of 96.13%. When it is applied to detect main peaks, the performance achieved an accuracy of 99.11%. After the previous segmentation algorithm, the artifact detection algorithm can detect beat-to-beat pulse waves and artifacts with an accuracy of 98.11%. The result indicated that the proposed method is robust for pulse waves of different patterns and could effectively detect the artifact without the complex algorithm. In summary, our proposed algorithm is capable of annotating pulse waves of various patterns and determining pulse wave quality. Since our method is developed and evaluated on the transmission-mode PPG data, it is more suitable for the devices and applications inside the hospitals instead of reflectance-mode PPG.

Design and Implementation of Processing Software for D-Peak Changed Pulse Wave

2014 ◽  
Vol 687-691 ◽  
pp. 1101-1104
Author(s):  
Yu Fei ◽  
Jing Xia Wang ◽  
Zhao Jie
Keyword(s):  
Pulse Wave ◽  
Important Change ◽  
Physiological Signal ◽  
Design And Implementation ◽  
Human Organs ◽  
Pulse Waves ◽  
Processing Software

The pulse wave is a very useful physiological signal which can reveal the information of human organs. D-peak change is an important change of pulse. To study the spectrum of the D-peak changed pulse wave quantitatively and get the statistics result of such kind of change, a new algorithm was proposed and a kind of processing software was designed and implemented. The software was tested by more than 200 person-times PPG pulse waves and showed good performance.

scholarly journals Design of Pulse Wave Feature Vigilance Detection System Based on Computer Software Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yidong Zeng ◽  
Jun Ji ◽  
Jinghua Wang ◽  
Jiasuo Gao ◽  
Jie Hu ◽  
...  
Keyword(s):  
Pulse Wave ◽  
Detection System ◽  
Skin Resistance ◽  
Computer Software ◽  
Pulse Amplitude ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Blood Oxygen Saturation ◽  
Software Technology ◽  
Physiological Signal

In this paper, the pulse wave feature alertness detection system based on computer software technology is researched. First, the computer software technology designs the alertness detection system and then conducts the system alertness test experiment using a system that can not affect the subjects’ alertness, a portable multichannel physiological signal acquisition system that measures the subjects’ ECG signal, skin resistance, blood oxygen saturation, and other physiological signals in the case of a degree task experiment. The multichannel physiological signal acquisition system collects the signals during the vigilance task experiment. At the same time, before, during, and after the experiment, subjects are required to fill in the Stanford Sleepiness Scale (SSS) and evaluate the level of individual alertness through subjective self-evaluation. The relevant experimental data show that, 10 minutes before the experiment, the pulse amplitude increased rapidly, then slowly decreased at the beginning, reached a peak in about 25 minutes, and then began to rise.

scholarly journals IoT Driven Automated Object Detection Algorithm for Urban Surveillance System in Smart City

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1687-1691
Keyword(s):  
Object Detection ◽  
Road Traffic ◽  
Smart Cities ◽  
Digital Camera ◽  
Detection Algorithm ◽  
License Plate ◽  
Surveillance Systems ◽  
Research Issues ◽  
Automated Object Detection ◽  
Research Challenge

Automated object detection algorithm is an important research challenge in intelligent urban surveillance systems for Internet of Things (IoT) and smart cities applications. In particular, smart vehicle license plate recognition and vehicle detection are recognized as core research issues of these IoTdriven intelligent urban surveillance systems. They are key techniques in most of the traffic related IoT applications, such as road traffic real-time monitoring, security control of restricted areas, automatic parking access control, searching stolen vehicles, etc. In this paper, we propose a novel unified method of automated object detection for urban surveillance systems. We use this novel method to determine and pick out the highest energy frequency areas of the images from the digital camera imaging sensors, that is, either to pick the vehicle license plates or the vehicles out from the images. The other sensors like flame and ultrasonic sensor are used to monitor nearby objects. Our proposed method can not only help to detect object vehicles rapidly and accurately, but also can be used to reduce big data volume needed to be stored in urban surveillance systems

Computer Forensic Investigation in Cloud of Things

2019 ◽  
pp. 256-270
Author(s):  
A. Surendar
Keyword(s):  
Smart Cities ◽  
Wearable Devices ◽  
Digital Data ◽  
Challenging Problem ◽  
Smart Vehicles ◽  
Healthcare Data ◽  
Iot Devices ◽  
Smart Governance ◽  
Computer Forensic ◽  
Individual Healthcare

Digital data transformation is most challenging in developing countries. In recent days, all the applications are functioning with the support of internet of things (IoT). Wearable devices involve the most insightful information, which includes individual healthcare data. Health records of patients must be protected. IoT devices could be hacked, and criminals use this information. Smart cities with IoT use information technology to collect, analyze, and integrate information. Smart reduces the network traffic using the ground sensors, micro-radars, and drones monitor traffic to the traffic controller based on that signals are designed. The data collected includes the images and convey information to smart vehicles, which in turn, if data are hacked, may affect many people. Smart city includes important features such as smart buildings, smart technology, smart governance, smart citizen, and smart security. Cyber threat is a challenging problem, and usage of apps may increase malware that affects various customers.

Detection of respiratory rate using pulse wave on near infrared wearable devices

2016 ◽  
Vol 24 (6) ◽  
pp. 1297-1306
Author(s):  
陈星池 CHEN Xing-chi ◽  
赵 海 ZHAO Hai ◽  
李 晗 LI Han ◽  
郑换霞 ZHENG Huan-xia
Keyword(s):  
Respiratory Rate ◽  
Near Infrared ◽  
Pulse Wave ◽  
Wearable Devices

scholarly journals Detection of Physiological Signals Based on Graphene Using a Simple and Low-Cost Method

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1656 ◽  
Author(s):  
Liping Xie ◽  
Xingyu Zi ◽  
Qingshi Meng ◽  
Zhiwen Liu ◽  
Lisheng Xu
Keyword(s):  
Graphene Sheet ◽  
Pulse Wave ◽  
Low Cost ◽  
Wearable Sensors ◽  
Unmet Need ◽  
Expansion Method ◽  
Physiological Signals ◽  
Physiological Signal ◽  
Solid Foundation ◽  
Processing Circuit

Despite that graphene has been extensively used in flexible wearable sensors, it remains an unmet need to fabricate a graphene-based sensor by a simple and low-cost method. Here, graphene nanoplatelets (GNPs) are prepared by thermal expansion method, and a sensor is fabricated by sealing of a graphene sheet with polyurethane (PU) medical film. Compared with other graphene-based sensors, it greatly simplifies the fabrication process and enables the effective measurement of signals. The resistance of graphene sheet changes linearly with the deformation of the graphene sensor, which lays a solid foundation for the detection of physiological signals. A signal processing circuit is developed to output the physiological signals in the form of electrical signals. The sensor was used to measure finger bending motion signals, respiration signals and pulse wave signals. All the results demonstrate that the graphene sensor fabricated by the simple and low-cost method is a promising platform for physiological signal measurement.

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