scholarly journals Smart Seismocardiography: A Machine Learning Approach for Automatic Data Processing

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Omar Y. López-Rico ◽  
Roberto G. Ramírez-Chavarría
Keyword(s):  
Heart Rate ◽  
Data Processing ◽  
Clustering Algorithm ◽  
Low Cost ◽  
Piezoelectric Sensor ◽  
Signal Spectrum ◽  
Automatic Data ◽  
Vibration Sensors ◽  
Custom Made ◽  
Invasive Method

Seismocardiography (SCG) is a non-invasive method that measures local vibrations created by the mechanical cardiovascular exercises on the chest wall. Thereby, mechanical movements of the heart are recorded in real-time from vibration sensors positioned on the chest of the subject, to further compute the heart rate and retrieve the SCG waveform. Although such events have been widely studied, robust signal processing methods remain a challenging task. On the other hand, the use of piezoelectric sensors has been favored in recent years due to its features and low cost. However, robust data processing techniques should be developed to increase their performance and reliability. In this work, we propose an attractive method for SCG data processing based on the K-Means clustering algorithm to automatically label waveform events. Interestingly, the SCG signals are recovered from a custom-made device built around an ultra-low-cost piezoelectric sensor. Once the signals are measured, they are pre-processed by spectral filtering. Afterwards, the signal spectrum is used to compute the heart rate (HR). Thereby, the filtered signal is sequentially segmented, and every frame is processed by a light-weight K-Means algorithm. Finally, we show the performance of the smart seismocardiography by analyzing SCG waveforms at different physiological conditions.

scholarly journals Cloud Computing and Its Application in Big Data Processing of Distance Higher Education

2015 ◽  
Vol 10 (8) ◽  
pp. 55 ◽  
Author(s):  
Guolei Zhang ◽  
Jia Li ◽  
Li Hao
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Distance Education ◽  
Big Data ◽  
Data Processing ◽  
Clustering Algorithm ◽  
Evaluation Method ◽  
Low Cost ◽  
Science And Technology ◽  
Large Data

In the development of information technology the development of scientific theory has brought the progress of science and technology. The progress of science and technology has an impact on the educational field, which changes the way of education. The arrival of the era of big data for the promotion and dissemination of educational resources has played an important role, it makes more and more people benefit. Modern distance education relies on the background of big data and cloud computing, which is composed of a series of tools to support a variety of teaching mode. Clustering algorithm can provide an effective evaluation method for students' personality characteristics and learning status in distance education. However, the traditional K-means clustering algorithm has the characteristics of randomness, uncertainty, high time complexity, and it does not meet the requirements of large data processing. In this paper, we study the parallel K-means clustering algorithm based on cloud computing platform Hadoop, and give the design and strategy of the algorithm. Then, we carry out experiments on several different sizes of data sets, and compare the performance of the proposed method with the general clustering method. Experimental results show that the proposed algorithm which is accelerated has good speed up and low cost. It is suitable for the analysis and mining of large data in the distance higher education.

scholarly journals Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 507 ◽  
Author(s):  
Yi-Chun Du ◽  
David Lin ◽  
Chun-Ping Jen ◽  
Choon Ng ◽  
Chi-Ying Chang ◽  
...  
Keyword(s):  
Transmission Rate ◽  
Low Cost ◽  
Rapid Development ◽  
High Sensitivity ◽  
Piezoelectric Sensor ◽  
Vibration Sensor ◽  
Mesh Network ◽  
Robotic Arm ◽  
Vibration Sensors ◽  
Wireless Mesh

In recent years, multi-axis robots are indispensable in automated factories due to the rapid development of Industry 4.0. Many related processes were required to have the increasing demand for accuracy, reproducibility, and abnormal detection. The monitoring function and immediate feedback for correction is more and more important. This present study integrated a highly sensitive lithium niobate (LiNbO3) vibration sensor as a sensor node (SN) and architecture of wireless mesh network (WMN) to develop a monitoring system (MS) for the robotic arm. The advantages of the thin-film LiNbO3 piezoelectric sensor were low-cost, high-sensitivity and good electrical compatibility. The experimental results obtained from the vibration platform show that the sensitivity achieved 50 mV/g and the reaction time within 1 ms. The results of on-site testing indicated that the SN could be configured on the relevant equipment quickly and detect the abnormal vibration in specific equipment effectively. Each SN could be used more than 10 h at the 80 Hz transmission rate under WMN architecture and the loss rate of transmission was less than 0.01% within 20 m.

Data Screening Methods – Application to Differential Diagnosis in Pancreatic Pathology from Radiological Signs

1978 ◽  
Vol 17 (01) ◽  
pp. 36-40 ◽  
Author(s):  
J.-P. Durbec ◽  
Jaqueline Cornée ◽  
P. Berthezene
Keyword(s):  
Differential Diagnosis ◽  
Mutual Information ◽  
Data Processing ◽  
Screening Methods ◽  
Automatic Data ◽  
Chronic Calcifying Pancreatitis ◽  
Number Of Patients ◽  
Calcifying Pancreatitis ◽  
Pancreatic Pathology ◽  
Data Screening

The practice of systematic examinations in hospitals and the increasing development of automatic data processing permits the storing of a great deal of information about a large number of patients belonging to different diagnosis groups.To predict or to characterize these diagnosis groups some descriptors are particularly useful, others carry no information. Data screening based on the properties of mutual information and on the log cross products ratios in contingency tables is developed. The most useful descriptors are selected. For each one the characterized groups are specified.This approach has been performed on a set of binary (presence—absence) radiological variables. Four diagnoses groups are concerned: cancer of pancreas, chronic calcifying pancreatitis, non-calcifying pancreatitis and probable pancreatitis. Only twenty of the three hundred and forty initial radiological variables are selected. The presence of each corresponding sign is associated with one or more diagnosis groups.

scholarly journals Biomechanics of Trail Running Performance: Quantification of Spatio-Temporal Parameters by Using Low Cost Sensors in Ecological Conditions

2021 ◽  
Vol 11 (5) ◽  
pp. 2093
Author(s):  
Noé Perrotin ◽  
Nicolas Gardan ◽  
Arnaud Lesprillier ◽  
Clément Le Goff ◽  
Jean-Marc Seigneur ◽  
...  
Keyword(s):  
Heart Rate ◽  
Low Cost ◽  
Step Length ◽  
Measurement Unit ◽  
Ecological Conditions ◽  
Sports Science ◽  
Ground Contact Time ◽  
Spatio Temporal ◽  
Performance Results ◽  
Trail Running

The recent popularity of trail running and the use of portable sensors capable of measuring many performance results have led to the growth of new fields in sports science experimentation. Trail running is a challenging sport; it usually involves running uphill, which is physically demanding and therefore requires adaptation to the running style. The main objectives of this study were initially to use three “low-cost” sensors. These low-cost sensors can be acquired by most sports practitioners or trainers. In the second step, measurements were taken in ecological conditions orderly to expose the runners to a real trail course. Furthermore, to combine the collected data to analyze the most efficient running techniques according to the typology of the terrain were taken, as well on the whole trail circuit of less than 10km. The three sensors used were (i) a Stryd sensor (Stryd Inc. Boulder CO, USA) based on an inertial measurement unit (IMU), 6 axes (3-axis gyroscope, 3-axis accelerometer) fixed on the top of the runner’s shoe, (ii) a Global Positioning System (GPS) watch and (iii) a heart belt. Twenty-eight trail runners (25 men, 3 women: average age 36 ± 8 years; height: 175.4 ± 7.2 cm; weight: 68.7 ± 8.7 kg) of different levels completed in a single race over a 8.5 km course with 490 m of positive elevation gain. This was performed with different types of terrain uphill (UH), downhill (DH), and road sections (R) at their competitive race pace. On these sections of the course, cadence (SF), step length (SL), ground contact time (GCT), flight time (FT), vertical oscillation (VO), leg stiffness (Kleg), and power (P) were measured with the Stryd. Heart rate, speed, ascent, and descent speed were measured by the heart rate belt and the GPS watch. This study showed that on a ≤10 km trail course the criteria for obtaining a better time on the loop, determined in the test, was consistency in the effort. In a high percentage of climbs (>30%), two running techniques stand out: (i) maintaining a high SF and a short SL and (ii) decreasing the SF but increasing the SL. In addition, it has been shown that in steep (>28%) and technical descents, the average SF of the runners was higher. This happened when their SL was shorter in lower steep and technically challenging descents.

scholarly journals An Innovative and Cost-Advantage CAD Solution for Cubitus Varus Surgical Planning in Children

2021 ◽  
Vol 11 (9) ◽  
pp. 4057
Author(s):  
Leonardo Frizziero ◽  
Gian Maria Santi ◽  
Christian Leon-Cardenas ◽  
Giampiero Donnici ◽  
Alfredo Liverani ◽  
...  
Keyword(s):  
Computer Aided Design ◽  
Low Cost ◽  
Cost Effective ◽  
Varus Deformity ◽  
Patient Specific ◽  
Cubitus Varus ◽  
Surgical Guide ◽  
Traditional Procedure ◽  
Custom Made ◽  
Patient Specific Instruments

The study of CAD (computer aided design) modeling, design and manufacturing techniques has undergone a rapid growth over the past decades. In medicine, this development mainly concerned the dental and maxillofacial sectors. Significant progress has also been made in orthopedics with pre-operative CAD simulations, printing of bone models and production of patient-specific instruments. However, the traditional procedure that formulates the surgical plan based exclusively on two-dimensional images and interventions performed without the aid of specific instruments for the patient and is currently the most used surgical technique. The production of custom-made tools for the patient, in fact, is often expensive and its use is limited to a few hospitals. The purpose of this study is to show an innovative and cost-effective procedure aimed at prototyping a custom-made surgical guide for address the cubitus varus deformity on a pediatric patient. The cutting guides were obtained through an additive manufacturing process that starts from the 3D digital model of the patient’s bone and allows to design specific models using Creo Parametric. The result is a tool that adheres perfectly to the patient’s bone and guides the surgeon during the osteotomy procedure. The low cost of the methodology described makes it worth noticing by any health institution.

scholarly journals Design, manufacture and testing of a prototype obstacle-detection device at blind corners: an automated highway system technology

2020 ◽  
Author(s):  
Charles Atombo ◽  
Emmanuel Gbey ◽  
Apevienyeku Kwami Holali
Keyword(s):  
Traffic Accidents ◽  
Low Cost ◽  
Effective Area ◽  
Obstacle Detection ◽  
The Road ◽  
Vibration Sensors ◽  
Road Signs ◽  
Sensor Module ◽  
Vehicle Path ◽  
Automated Highway

Abstract Traffic accidents on highways are attributed mostly to the "invisibility" of oncoming traffic and road signs. "Speeding" also causes drivers to reduce the effective radius of the vehicle path in the curve, thus trespassing into the lane of the oncoming traffic. The main aim of this paper was to develop a multisensory obstacle-detection device that is affordable, easy to implement and easy to maintain to reduce the risk of road accidents at blind corners. An ultrasonic sensor module with a maximum measuring angle of 15° was used to ensure that a significant portion of the lane was detected at the blind corner. The sensor covered a minimum effective area of 0.5 m2 of the road for obstacle detection. Yellow light was employed to signify caution while negotiating the blind corner. Two photoresistors (PRs) were used as sensors because of the limited number of pins on the microcontroller (Arduino Uno). However, the device developed for this project achieved obstacle detection at blind corners at relatively low cost and can be accessed by all road users. In real-world applications, the use of piezoelectric accelerometers (vibration sensors) instead of PR sensors would be more desirable in order to detect not only cars but also two-wheelers.

scholarly journals Clustering-Based Component Fraction Estimation in Solid–Liquid Two-Phase Flow in Dredging Engineering

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5697
Author(s):  
Chang Sun ◽  
Shihong Yue ◽  
Qi Li ◽  
Huaxiang Wang
Keyword(s):  
Clustering Algorithm ◽  
Two Phase Flow ◽  
Low Cost ◽  
Fast Response ◽  
New Method ◽  
Phase Flow ◽  
Reference Distribution ◽  
Two Phase ◽  
Long Time ◽  
Solid Liquid

Component fraction (CF) is one of the most important parameters in multiple-phase flow. Due to the complexity of the solid–liquid two-phase flow, the CF estimation remains unsolved both in scientific research and industrial application for a long time. Electrical resistance tomography (ERT) is an advanced type of conductivity detection technique due to its low-cost, fast-response, non-invasive, and non-radiation characteristics. However, when the existing ERT method is used to measure the CF value in solid–liquid two-phase flow in dredging engineering, there are at least three problems: (1) the dependence of reference distribution whose CF value is zero; (2) the size of the detected objects may be too small to be found by ERT; and (3) there is no efficient way to estimate the effect of artifacts in ERT. In this paper, we proposed a method based on the clustering technique, where a fast-fuzzy clustering algorithm is used to partition the ERT image to three clusters that respond to liquid, solid phases, and their mixtures and artifacts, respectively. The clustering algorithm does not need any reference distribution in the CF estimation. In the case of small solid objects or artifacts, the CF value remains effectively computed by prior information. To validate the new method, a group of typical CF estimations in dredging engineering were implemented. Results show that the new method can effectively overcome the limitations of the existing method, and can provide a practical and more accurate way for CF estimation.

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