scholarly journals Detection of Sleep Biosignals Using an Intelligent Mattress Based on Piezoelectric Ceramic Sensors

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3843 ◽  
Author(s):  
Min Peng ◽  
Zhizhong Ding ◽  
Lusheng Wang ◽  
Xusheng Cheng
Keyword(s):  
Heart Rate ◽  
Wavelet Analysis ◽  
Respiratory Rate ◽  
Piezoelectric Ceramic ◽  
Detection System ◽  
Low Cost ◽  
Ensemble Empirical Mode Decomposition ◽  
High Accuracy ◽  
Health Condition ◽  
Sleep State

Physiological information such as respiratory rate and heart rate in the sleep state can be used to evaluate the health condition of the sleeper. Traditional sleep monitoring systems need body contact and are intrusive, which limits their applicability. Thus, a comfortable sleep biosignals detection system with both high accuracy and low cost is important for health care. In this paper, we design a sleep biosignals detection system based on low-cost piezoelectric ceramic sensors. 18 piezoelectric ceramic sensors are deployed under the mattress to capture the pressure data. The appropriate sensor that captures respiration and heartbeat sensitively is selected by the proposed channel-selection algorithm. Then, we propose a dynamic smoothing algorithm to extract respiratory rate and heart rate using the selected data. The dynamic smoothing can separate heartbeat signals from respiratory signals with low complexity by dynamically choosing the smooth window, and it is suitable for real-time implementation in low-cost embedded systems. For comparison, wavelet analysis and ensemble empirical mode decomposition (EEMD) are performed in a personal computer (PC). Experimental results show that data collected by piezoelectric ceramic sensors can be used for respiratory-rate and heart-rate detection with high accuracy. In addition, the dynamic smoothing can achieve high accuracy close to wavelet analysis and EEMD, while it has much lower complexity.

Transcutaneous Oxygen Tension During Nonnutritive Sucking in Preterm Infants

PEDIATRICS ◽  
1984 ◽  
Vol 74 (4) ◽  
pp. 539-542
Author(s):  
Roberto Paludetto ◽  
Steven S. Robertson ◽  
Maureen Hack ◽  
Chandra R. Shivpuri ◽  
Richard J. Martin
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Preterm Infants ◽  
Oxygen Tension ◽  
Sleep State ◽  
Transcutaneous Oxygen Tension ◽  
Transcutaneous Oxygen ◽  
Beneficial Effects ◽  
Nonnutritive Sucking ◽  
Postconceptional Age

The effects of nonnutritive sucking on transcutaneous oxygen tension, heart rate, and respiratory rate were studied sequentially in 14 sleeping preterm infants breathing room air. Transcutaneous oxygen tension increased during nonnutritive sucking in infants between 32 and 35 weeks postconceptional age, but not in those between 36 and 39 weeks. This response was not associated with a change in respiratory rate or sleep state, although heart rate tended to increase. These data offer further support for the beneficial effects of nonnutritive sucking in preterm infants.

scholarly journals Non-intrusive vital sign monitoring using an intelligent pillow based on a piezoelectric ceramic sensor

2020 ◽  
Vol 15 ◽  
pp. 155892502097726
Author(s):  
Wei Wang ◽  
Zhiqiang Pang ◽  
Ling Peng ◽  
Fei Hu
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Piezoelectric Ceramic ◽  
Low Cost ◽  
Body Movement ◽  
Vital Signs ◽  
High Heart Rate ◽  
Detection Accuracy ◽  
Processing Unit ◽  
Real Time Monitoring

Performing real-time monitoring for human vital signs during sleep at home is of vital importance to achieve timely detection and rescue. However, the existing smart equipment for monitoring human vital signs suffers the drawbacks of high complexity, high cost, and intrusiveness, or low accuracy. Thus, it is of great need to develop a simplified, nonintrusive, comfortable and low cost real-time monitoring system during sleep. In this study, a novel intelligent pillow was developed based on a low-cost piezoelectric ceramic sensor. It was manufactured by locating a smart system (consisting of a sensing unit i.e. a piezoelectric ceramic sensor, a data processing unit and a GPRS communication module) in the cavity of the pillow made of shape memory foam. The sampling frequency of the intelligent pillow was set at 1000 Hz to capture the signals more accurately, and vital signs including heart rate, respiratory rate and body movement were derived through series of well established algorithms, which were sent to the user’s app. Validation experimental results demonstrate that high heart-rate detection accuracy (i.e. 99.18%) was achieved in using the intelligent pillow. Besides, human tests were conducted by detecting vital signs of six elder participants at their home, and results showed that the detected vital signs may well predicate their health conditions. In addition, no contact discomfort was reported by the participants. With further studies in terms of validity of the intelligent pillow and large-scale human trials, the proposed intelligent pillow was expected to play an important role in daily sleep monitoring.

scholarly journals Sliding wire detection system of electric lock screw tool based on motor characteristics

2021 ◽  
Vol 2137 (1) ◽  
pp. 012009
Author(s):  
Ning Zhang ◽  
Yinxin Yan ◽  
Houcheng Yang ◽  
Zhangsi Yu
Keyword(s):  
Real Time ◽  
Detection System ◽  
Low Cost ◽  
High Sensitivity ◽  
High Accuracy ◽  
Normal Operation ◽  
Automatic Assembly ◽  
The Real ◽  
Current Change ◽  
Real Time Detection

Abstract This paper presents a sliding wire detection system of electric screw locking tool based on the characteristics of motor. The system can judge whether the screw has sliding wire through the current change of motor during normal operation, and realize the real-time detection and alarm of sliding wire. The system has the advantages of high sensitivity, low cost and high accuracy. It can be widely used in automatic assembly and other fields.

scholarly journals Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3238
Author(s):  
Ruisheng Lei ◽  
Bingo Wing-Kuen Ling ◽  
Peihua Feng ◽  
Jinrong Chen
Keyword(s):  
Heart Rate ◽  
Independent Component Analysis ◽  
Respiratory Rate ◽  
Empirical Mode Decomposition ◽  
Matrix Factorization ◽  
Component Analysis ◽  
Ensemble Empirical Mode Decomposition ◽  
Independent Component ◽  
Mode Decomposition ◽  
Non Negative Matrix Factorization

This paper proposes a framework combining the complementary ensemble empirical mode decomposition with both the independent component analysis and the non-negative matrix factorization for estimating both the heart rate and the respiratory rate from the photoplethysmography (PPG) signal. After performing the complementary ensemble empirical mode decomposition on the PPG signal, a finite number of intrinsic mode functions are obtained. Then, these intrinsic mode functions are divided into two groups to perform the further analysis via both the independent component analysis and the non-negative matrix factorization. The surrogate cardiac signal related to the heart activity and another surrogate respiratory signal related to the respiratory activity are reconstructed to estimate the heart rate and the respiratory rate, respectively. Finally, different records of signals acquired from the Medical Information Mart for Intensive Care database downloaded from the Physionet Automated Teller Machine (ATM) data bank are employed for demonstrating the outperformance of our proposed method. The results show that our proposed method outperforms both the digital filtering approach and the conventional empirical mode decomposition based methods in terms of reconstructing both the surrogate cardiac signal and the respiratory signal from the PPG signal as well as both achieving the higher accuracy and the higher reliability for estimating both the heart rate and the respiratory rate.

scholarly journals A Low Cost Wearable Medical Device for Vital Signs Monitoring in Low-Resource Settings

2019 ◽  
Vol 9 (4) ◽  
pp. 2321
Author(s):  
Muhammad Niswar ◽  
Muhammad Nur ◽  
Idar Mappangara
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Medical Device ◽  
Low Cost ◽  
Vital Signs ◽  
Oxygen Saturation Level ◽  
Low Resource Settings ◽  
Low Resource ◽  
Vital Signs Monitoring ◽  
Wearable Medical

Medical devices are often expensive, so people in low-income countries cannot afford them. This paper presents the design of a low-cost wearable medical device to measure vital signs of a patient including heart rate, blood oxygen saturation level (SpO2) and respiratory rate. The wearable medical device mainly consists of a microcontroller and two biomedical sensors including airflow thermal sensor to measure respiratory rate and pulse oximeter sensor to measure SpO2 and heart rate. We can monitor the vital signs from a smartphone using a web browser through IEEE802.11 wireless connectivity to the wearable medical device. Furthermore, the wearable medical device requires simple management to operate; hence, it can be easily used. Performance evaluation results show that the designed wearable medical device works as good as a standard SpO2 device and it can measure the respiratory rate properly.  The designed wearable medical device is inexpensive and appropriate for low-resource settings. Moreover, as its components are commonly available in the market, it easy to assembly and repair locally.

scholarly journals Low-Cost Multisensor Integrated System for Online Walking Gait Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Lingyun Yan ◽  
Guowu Wei ◽  
Zheqi Hu ◽  
Haohua Xiu ◽  
Yuyang Wei ◽  
...  
Keyword(s):  
Detection System ◽  
Low Cost ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Integrated System ◽  
Heel Strike ◽  
Detection Accuracy ◽  
Time Error ◽  
Kinematic Data ◽  
Compact Size

A three-dimensional motion capture system is a useful tool for analysing gait patterns during walking or exercising, and it is frequently applied in biomechanical studies. However, most of them are expensive. This study designs a low-cost gait detection system with high accuracy and reliability that is an alternative method/equipment in the gait detection field to the most widely used commercial system, the virtual user concept (Vicon) system. The proposed system integrates mass-produced low-cost sensors/chips in a compact size to collect kinematic data. Furthermore, an x86 mini personal computer (PC) running at 100 Hz classifies motion data in real-time. To guarantee gait detection accuracy, the embedded gait detection algorithm adopts a multilayer perceptron (MLP) model and a rule-based calibration filter to classify kinematic data into five distinct gait events: heel-strike, foot-flat, heel-off, toe-off, and initial-swing. To evaluate performance, volunteers are requested to walk on the treadmill at a regular walking speed of 4.2 km/h while kinematic data are recorded by a low-cost system and a Vicon system simultaneously. The gait detection accuracy and relative time error are estimated by comparing the classified gait events in the study with the Vicon system as a reference. The results show that the proposed system obtains a high accuracy of 99.66% with a smaller time error (32 ms), demonstrating that it performs similarly to the Vicon system in the gait detection field.

scholarly journals Highly Sensitive Room-Temperature Sensor Based on Nanostructured K2W7O22 for Application in the Non-Invasive Diagnosis of Diabetes

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3703 ◽  
Author(s):  
Md Hossain ◽  
Qifeng Zhang ◽  
Michael Johnson ◽  
Danling Wang
Keyword(s):  
Blood Glucose ◽  
Detection Limit ◽  
Room Temperature ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Low Cost ◽  
Health Condition ◽  
Exhaled Breath ◽  
Glucose Levels ◽  
Non Invasive

Diabetes is one of the most rapidly-growing chronic diseases in the world. Acetone, a volatile organic compound in exhaled breath, shows a positive correlation with blood glucose and has proven to be a biomarker for type-1 diabetes. Measuring the level of acetone in exhaled breath can provide a non-invasive, low risk of infection, low cost, and convenient way to monitor the health condition of diabetics. There has been continuous demand for the improvement of this non-invasive, sensitive sensor system to provide a fast and real-time electronic readout of blood glucose levels. A novel nanostructured K2W7O22 has been recently used to test acetone with concentration from 0 parts-per-million (ppm) to 50 ppm at room temperature. The results revealed that a K2W7O22 sensor shows a sensitive response to acetone, but the detection limit is not ideal due to the limitations of the detection system of the device. In this paper, we report a K2W7O22 sensor with an improved sensitivity and detection limit by using an optimized circuit to minimize the electronic noise and increase the signal to noise ratio for the purpose of weak signal detection while the concentration of acetone is very low.

scholarly journals FahamecV1:A Low Cost Automated Metaphase Detection System

2017 ◽  
Vol 7 (6) ◽  
pp. 2160-2166
Author(s):  
H. Yilmaz ◽  
M. Kamil Turan
Keyword(s):  
Detection System ◽  
Electronic Control Unit ◽  
Low Cost ◽  
Control Unit ◽  
Chromosome Analysis ◽  
Active Role ◽  
High Accuracy ◽  
True Negative ◽  
Metaphase Stage ◽  
Microscope Stage

In this study, FahamecV1 is introduced and investigated as a low cost and high accuracy solution for metaphase detection. Chromosome analysis is performed at the metaphase stage and high accuracy and automated detection of the metaphase stage plays an active role in decreasing analysis time. FahamecV1 includes an optic microscope, a motorized microscope stage, an electronic control unit, a camera, a computer and a software application. Printing components of the motorized microscope stage (using a 3D printer) is of the main reasons for cost reduction. Operations such as stepper motor calibration, are detection, focusing, scanning, metaphase detection and saving of coordinates into a database are automatically performed. To detect metaphases, a filter named Metafilter is developed and applied. Average scanning time per preparate is 77 sec/cm2. True positive rate is calculated as 95.1%, true negative rate is calculated as 99.0% and accuracy is calculated as 98.8%.

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