scholarly journals A Novel Multi-Dimensional Composition Method Based on Time Series Similarity for Array Pulse Wave Signals Detecting

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 297
Author(s):  
Hongjie Zou ◽  
Yitao Zhang ◽  
Jun Zhang ◽  
Chuanglu Chen ◽  
Xingguang Geng ◽  
...  
Keyword(s):  
Time Series ◽  
Sensor Array ◽  
Pulse Wave ◽  
Dynamic Pressure ◽  
Sensor Arrays ◽  
Disease Diagnosis ◽  
Micro Electro Mechanical System ◽  
Processing Method ◽  
Multiple Test ◽  
Multiple Sensors

Pulse wave signal sensed over the radial artery on the wrist is a crucial physiological indicator in disease diagnosis. The sensor array composed of multiple sensors has the ability to collect abundant pulse wave information. As a result, it has gradually attracted the attention of practitioners. However, few practical methods are used to obtain a one-dimensional pulse wave from the sensor array’s spatial multi-dimensional signals. The current algorithm using pulse wave with the highest amplitude value as the significant data suffers from low consistency because the signal acquired each time differs significantly due to the sensor’s relative position shift to the test area. This paper proposes a processing method based on time series similarity, which can take full advantage of sensor arrays’ spatial multi-dimensional characteristics and effectively avoid the above factors’ influence. A pulse wave acquisition system (PWAS) containing a micro-electro-mechanical system (MEMS) sensor array is continuously extruded using a stable dynamic pressure input source to simulate the pulse wave acquisition process. Experiments are conducted at multiple test locations with multiple data acquisitions to evaluate the performance of the algorithm. The experimental results show that the newly proposed processing method using time series similarity as the criterion has better consistency and stability.

scholarly journals A 3D Wrist Pulse Signal Acquisition System for Width Information of Pulse Wave

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 11 ◽  
Author(s):  
Chuanglu Chen ◽  
Zhiqiang Li ◽  
Yitao Zhang ◽  
Shaolong Zhang ◽  
Jiena Hou ◽  
...  
Keyword(s):  
Sensor Array ◽  
Pulse Wave ◽  
Pulse Signal ◽  
Micro Electro Mechanical System ◽  
Acquisition System ◽  
Measuring Instruments ◽  
Signal Acquisition ◽  
Mems Sensor ◽  
Signal Collection ◽  
Pulse Waves

During pulse signal collection, width information of pulse waves is essential for the diagnosis of disease. However, currently used measuring instruments can only detect the amplitude while can’t acquire the width information. This paper proposed a novel wrist pulse signal acquisition system, which could realize simultaneous measurements of the width and amplitude of dynamic pulse waves under different static forces. A tailor-packaged micro-electro-mechanical system (MEMS) sensor array was employed to collect pulse signals, a conditioning circuit was designed to process the signals, and a customized algorithm was developed to compute the width. Experiments were carried out to validate the accuracy of the sensor array and system effectiveness. The results showed the system could acquire not only the amplitude of pulse wave but also the width of it. The system provided more information about pulse waves, which could help doctors make the diagnosis.

Utilizing Sensor Arrays to Attain High-Operating Bandwidth

2004 ◽  
Vol 126 (2) ◽  
pp. 294-302
Author(s):  
Sugathevan Suranthiran ◽  
Suhada Jayasuriya
Keyword(s):  
Sensor Array ◽  
Sensor Arrays ◽  
Cost Effective ◽  
Sensor Data ◽  
Pass Band ◽  
Multiple Sensors ◽  
High Bandwidth ◽  
Small Bandwidth ◽  
Operating Bandwidth ◽  
Single Sensor

Proposed in this paper is a methodology for the design of a sensor array of small bandwidth passband sensors (sensors with small bandwidth but different bandwidths) to attain a high operating bandwidth. In certain control applications, it is necessary that a high bandwidth sensor be used for feedback efficiency. The design of a single sensor with the desired high bandwidth may not be easy and economically feasible. A new approach, which recommends the use of an array of small bandwidth pass-band sensors in place of a single sensor of high bandwidth is proposed. It is shown that the idea of sensor arrays can be utilized to obtain a cost effective and efficient solution to the problem posed. The proposed sensor array that consists of multiple sensors with possible overlapping operating regions as defined by their pass-bands requires that an effective fusion technique be used to unite multi-sensor data. A multi-sensor data fusion scheme using Frequency Response Methods is developed to facilitate the possible implementation of proposed sensor arrays.

scholarly journals A Flexible Two-Sensor System for Temperature and Bending Angle Monitoring

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2962
Author(s):  
Yifeng Mu ◽  
Rou Feng ◽  
Qibei Gong ◽  
Yuxuan Liu ◽  
Xijun Jiang ◽  
...  
Keyword(s):  
Electronic System ◽  
Disease Diagnosis ◽  
Accurate Information ◽  
Polyimide Films ◽  
Bending Angle ◽  
Multiple Sensors ◽  
Constituent Material ◽  
Application Potential ◽  
Wearable Electronic ◽  
Bending Angles

A wearable electronic system constructed with multiple sensors with different functions to obtain multidimensional information is essential for making accurate assessments of a person’s condition, which is especially beneficial for applications in the areas of health monitoring, clinical diagnosis, and therapy. In this work, using polyimide films as substrates and Pt as the constituent material of serpentine structures, flexible temperature and angle sensors were designed that can be attached to the surface of an object or the human body for monitoring purposes. In these sensors, changes in temperature and bending angle are converted into variations in resistance through thermal resistance and strain effects with a sensitivity of 0.00204/°C for temperatures in the range of 25 to 100 °C and a sensitivity of 0.00015/° for bending angles in the range of 0° to 150°. With an appropriate layout design, two sensors were integrated to measure temperature and bending angles simultaneously in order to obtain decoupled, compensated, and more accurate information of temperature and angle. Finally, the system was tested by being attached to the surface of a knee joint, demonstrating its application potential in disease diagnosis, such as in arthritis assessment.

Fundamental Sensor Development in Electrical Resistance Tomography

2015 ◽  
Vol 73 (6) ◽  
Author(s):  
Ling En Hong ◽  
Ruzairi Hj. Abdul Rahim ◽  
Anita Ahmad ◽  
Mohd Amri Md. Yunus ◽  
Khairul Hamimah Aba ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Data Acquisition ◽  
Electrical Resistance ◽  
Sensor Array ◽  
Sensor Arrays ◽  
Region Of Interest ◽  
Display System ◽  
Electrical Resistance Tomography ◽  
Fundamental Understanding ◽  
Collection Strategies

This paper will provide a fundamental understanding of one of the most commonly used tomography, Electrical Resistance Tomography (ERT). Unlike the other tomography systems, ERT displayed conductivity distribution in the Region of Interest (ROI) and commonly associated to Sensitivity Theorem in their image reconstruction. The fundamental construction of ERT includes a sensor array spaced equally around the imaged object periphery, a Data Acquisition (DAQ), image reconstruction and display system. Four ERT data collection strategies that will be discussed are Adjacent Strategy, Opposite Strategy, Diagonal Strategy and Conducting Boundary Strategy. We will also explain briefly on some of the possible Data Acquisition System (DAQ), forward and inverse problems, different arrangements for conducting and non-conducting pipes and factors that influence sensor arrays selections. 

scholarly journals Sensor Fusion for Recognition of Activities of Daily Living

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4029 ◽  
Author(s):  
Jiaxuan Wu ◽  
Yunfei Feng ◽  
Peng Sun
Keyword(s):  
Time Series ◽  
Sensor Fusion ◽  
Daily Living ◽  
Single Point ◽  
Recognition System ◽  
Sensor Data ◽  
Multiple Sensors ◽  
Life Patterns ◽  
Functional Capabilities ◽  
Correction Technique

Activity of daily living (ADL) is a significant predictor of the independence and functional capabilities of an individual. Measurements of ADLs help to indicate one’s health status and capabilities of quality living. Recently, the most common ways to capture ADL data are far from automation, including a costly 24/7 observation by a designated caregiver, self-reporting by the user laboriously, or filling out a written ADL survey. Fortunately, ubiquitous sensors exist in our surroundings and on electronic devices in the Internet of Things (IoT) era. We proposed the ADL Recognition System that utilizes the sensor data from a single point of contact, such as smartphones, and conducts time-series sensor fusion processing. Raw data is collected from the ADL Recorder App constantly running on a user’s smartphone with multiple embedded sensors, including the microphone, Wi-Fi scan module, heading orientation of the device, light proximity, step detector, accelerometer, gyroscope, magnetometer, etc. Key technologies in this research cover audio processing, Wi-Fi indoor positioning, proximity sensing localization, and time-series sensor data fusion. By merging the information of multiple sensors, with a time-series error correction technique, the ADL Recognition System is able to accurately profile a person’s ADLs and discover his life patterns. This paper is particularly concerned with the care for the older adults who live independently.

scholarly journals Curating Metal-Organic Frameworks to Compose Robust Gas Sensor Arrays in Dilute Conditions

2019 ◽  
Author(s):  
Arni Sturluson ◽  
Rachel Sousa ◽  
Yujing Zhang ◽  
Melanie T. Huynh ◽  
Caleb Laird ◽  
...  
Keyword(s):  
Sensor Array ◽  
Gas Sensing ◽  
Metal Organic Frameworks ◽  
Sensor Arrays ◽  
Gas Composition ◽  
Composition Space ◽  
The Matrix ◽  
Metal Organic ◽  
Analyte Detection ◽  
Value Decomposition

Metal-organic frameworks (MOFs)-- tunable, nano-porous materials-- are alluring recognition elements for gas sensing. Mimicking human olfaction, an array of cross-sensitive, MOF-based sensors could enable analyte detection in complex, variable gas mixtures containing confounding gas species. Herein, we address the question: given a set of MOF candidates and their adsorption properties, how do we select the optimal subset to compose a sensor array that accurately and robustly predicts the gas composition via monitoring the adsorbed mass in each MOF? We first mathematically formulate the MOF-based sensor array problem under dilute conditions. Instructively, the sensor array can be viewed as a linear map from <i>gas composition space</i> to <i>sensor array response space</i> defined by the matrix <b>H</b> of Henry coefficients of the gases in the MOFs. Characterizing this mapping, the singular value decomposition of <b>H </b>is a useful tool for evaluating MOF subsets for sensor arrays, as it determines the sensitivity of the predicted gas composition to measurement error, quantifies the magnitude of the response to changes in composition, and recovers which direction in gas composition space elicits the largest/smallest response. To illustrate, on the basis of experimental adsorption data, we curate MOFs for a sensor array with the objective of determining the concentration of CO<sub>2</sub> and SO<sub>2</sub> in the gas phase.

scholarly journals Development of a Pattern Recognition Tool for the Classification of Electronic Tongue Signals Using Machine Learning

2021 ◽  
Vol 5 (1) ◽  
pp. 21
Author(s):  
Edgar G. Mendez-Lopez ◽  
Jersson X. Leon-Medina ◽  
Diego A. Tibaduiza
Keyword(s):  
Machine Learning ◽  
Dimensionality Reduction ◽  
Performance Measures ◽  
Sensor Array ◽  
Three Dimensional ◽  
Electronic Tongue ◽  
Sensor Arrays ◽  
Classification Performance ◽  
Supervised Machine Learning ◽  
Electrochemical Tests

Electronic tongue type sensor arrays are made of different materials with the property of capturing signals independently by each sensor. The signals captured when conducting electrochemical tests often have high dimensionality, which increases when performing the data unfolding process. This unfolding process consists of arranging the data coming from different experiments, sensors, and sample times, thus the obtained information is arranged in a two-dimensional matrix. In this work, a description of a tool for the analysis of electronic tongue signals is developed. This tool is developed in Matlab® App Designer, to process and classify the data from different substances analyzed by an electronic tongue type sensor array. The data processing is carried out through the execution of the following stages: (1) data unfolding, (2) normalization, (3) dimensionality reduction, (4) classification through a supervised machine learning model, and finally (5) a cross-validation procedure to calculate a set of classification performance measures. Some important characteristics of this tool are the possibility to tune the parameters of the dimensionality reduction and classifier algorithms, and also plot the two and three-dimensional scatter plot of the features after reduced the dimensionality. This to see the data separability between classes and compatibility in each class. This interface is successfully tested with two electronic tongue sensor array datasets with multi-frequency large amplitude pulse voltammetry (MLAPV) signals. The developed graphical user interface allows comparing different methods in each of the mentioned stages to find the best combination of methods and thus obtain the highest values of classification performance measures.

scholarly journals Sensor arrays: an inspired idea or an objective measurement of environmental odours?

2001 ◽  
Vol 44 (9) ◽  
pp. 53-58 ◽  
Author(s):  
R.M. Stuetz ◽  
J. Nicolas
Keyword(s):  
Sensor Array ◽  
Sensory System ◽  
Sensor Arrays ◽  
Objective Measurement ◽  
Chemical Compositions ◽  
Response Patterns ◽  
Human Response ◽  
Control And Prevention ◽  
On Line ◽  
The Right

The measure of annoyance odours from sewage tratment, landfill and agricultural practise has become highly significant in the control and prevention of dorous emissions from existing facilities and its crucial for new planning applications. Current methods (such as GC-MS analysis, H2S and NH3 measurements) provide an accurate description of chemical compositions or act as surrogates for odour strength, but tell us very little about the perceived effect, whereas olfactometry gives the right human response but is very subjective and expensive. The use of non-specific sensor arrays may offer an objective and on-line instrument for assessing olfactive annoyance. Results have shown that sensor array systems can discriminate between different odour sources (wastewater, livestock and landfill). The response patterns from these sources can be significantly different and that the intensity of sensor responses is proportional to the concentration of the volatiles. The correlation of the sensors responses against odour strengths have also shown that reasonable fits can be obtained for a range of odour concentrations (100-800,000 ou/m3). However, the influence of environmental fluctuations (humidity and temperature) on sensor baselines still remains an obstacle, as well as the need for periodic calibration of the sensory system and the choice of a suitable gas for different environmental odours.

scholarly journals Spline approximation-based data compression for sensor arrays in the wireless hydrologic monitoring system

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769258
Author(s):  
Danyang Li ◽  
Wei Huangfu ◽  
Keping Long
Keyword(s):  
Data Compression ◽  
Monitoring System ◽  
Sensor Array ◽  
Spline Approximation ◽  
Sensor Arrays ◽  
Huffman Coding ◽  
Long Distance ◽  
Data Set ◽  
Array Data ◽  
Hydrologic Monitoring

A sensor array produces lots of bits of data every sample period, which may cause a heavy burden on the long-distance wireless data transmission, especially in the scenarios of wireless sensor networks. A lossy but error-bounded sensor array data compression algorithm is proposed, in which the major part of the sensor array data are approximated by the Catmull-Rom spline curve and the residual errors are quantized and encoded with Huffman coding. The performance of this algorithm has been evaluated with a real data set from the wireless hydrologic monitoring system deployed in Qinhuangdao Port of China. The results show that the algorithm performs well for the hydrologic sensor array data.

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