1
|
Du Y, Liu X, Yi Y, Wei K. Optimizing Road Safety: Advancements in Lightweight YOLOv8 Models and GhostC2f Design for Real-Time Distracted Driving Detection. SENSORS (BASEL, SWITZERLAND) 2023; 23:8844. [PMID: 37960543 PMCID: PMC10649436 DOI: 10.3390/s23218844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 10/28/2023] [Accepted: 10/29/2023] [Indexed: 11/15/2023]
Abstract
The rapid detection of distracted driving behaviors is crucial for enhancing road safety and preventing traffic accidents. Compared with the traditional methods of distracted-driving-behavior detection, the YOLOv8 model has been proven to possess powerful capabilities, enabling it to perceive global information more swiftly. Currently, the successful application of GhostConv in edge computing and embedded systems further validates the advantages of lightweight design in real-time detection using large models. Effectively integrating lightweight strategies into YOLOv8 models and reducing their impact on model performance has become a focal point in the field of real-time distracted driving detection based on deep learning. Inspired by GhostConv, this paper presents an innovative GhostC2f design, aiming to integrate the idea of linear transformation to generate more feature maps without additional computation into YOLOv8 for real-time distracted-driving-detection tasks. The goal is to reduce model parameters and computational load. Additionally, enhancements have been made to the path aggregation network (PAN) to amplify multi-level feature fusion and contextual information propagation. Furthermore, simple attention mechanisms (SimAMs) are introduced to perform self-normalization on each feature map, emphasizing feature maps with valuable information and suppressing redundant information interference in complex backgrounds. Lastly, the nine distinct distracted driving types in the publicly available SFDDD dataset were expanded to 14 categories, and nighttime scenarios were introduced. The results indicate a 5.1% improvement in model accuracy, with model weight size and computational load reduced by 36.7% and 34.6%, respectively. During 30 real vehicle tests, the distracted-driving-detection accuracy reached 91.9% during daylight and 90.3% at night, affirming the exceptional performance of the proposed model in assisting distracted driving detection when driving and contributing to accident-risk reduction.
Collapse
Affiliation(s)
- Yingjie Du
- School of Automotive and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China; (X.L.); (Y.Y.); (K.W.)
| | | | | | | |
Collapse
|
2
|
Saleem AA, Siddiqui HUR, Raza MA, Rustam F, Dudley S, Ashraf I. A systematic review of physiological signals based driver drowsiness detection systems. Cogn Neurodyn 2023; 17:1229-1259. [PMID: 37786662 PMCID: PMC10542071 DOI: 10.1007/s11571-022-09898-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/11/2022] [Accepted: 09/14/2022] [Indexed: 11/03/2022] Open
Abstract
Driving a vehicle is a complex, multidimensional, and potentially risky activity demanding full mobilization and utilization of physiological and cognitive abilities. Drowsiness, often caused by stress, fatigue, and illness declines cognitive capabilities that affect drivers' capability and cause many accidents. Drowsiness-related road accidents are associated with trauma, physical injuries, and fatalities, and often accompany economic loss. Drowsy-related crashes are most common in young people and night shift workers. Real-time and accurate driver drowsiness detection is necessary to bring down the drowsy driving accident rate. Many researchers endeavored for systems to detect drowsiness using different features related to vehicles, and drivers' behavior, as well as, physiological measures. Keeping in view the rising trend in the use of physiological measures, this study presents a comprehensive and systematic review of the recent techniques to detect driver drowsiness using physiological signals. Different sensors augmented with machine learning are utilized which subsequently yield better results. These techniques are analyzed with respect to several aspects such as data collection sensor, environment consideration like controlled or dynamic, experimental set up like real traffic or driving simulators, etc. Similarly, by investigating the type of sensors involved in experiments, this study discusses the advantages and disadvantages of existing studies and points out the research gaps. Perceptions and conceptions are made to provide future research directions for drowsiness detection techniques based on physiological signals.
Collapse
Affiliation(s)
- Adil Ali Saleem
- Faculty of Computer Science and Information Technology, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, 64200 Pakistan
| | - Hafeez Ur Rehman Siddiqui
- Faculty of Computer Science and Information Technology, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, 64200 Pakistan
| | - Muhammad Amjad Raza
- Faculty of Computer Science and Information Technology, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, 64200 Pakistan
| | - Furqan Rustam
- School of Computer Science, University College Dublin, Dublin, D04 V1W8 Ireland
| | - Sandra Dudley
- School of Engineering, London South Bank University, London, SE1 0AA UK
| | - Imran Ashraf
- Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541 South Korea
| |
Collapse
|
3
|
Brishtel I, Krauss S, Chamseddine M, Rambach JR, Stricker D. Driving Activity Recognition Using UWB Radar and Deep Neural Networks. SENSORS (BASEL, SWITZERLAND) 2023; 23:818. [PMID: 36679616 PMCID: PMC9862485 DOI: 10.3390/s23020818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/19/2022] [Accepted: 01/04/2023] [Indexed: 06/17/2023]
Abstract
In-car activity monitoring is a key enabler of various automotive safety functions. Existing approaches are largely based on vision systems. Radar, however, can provide a low-cost, privacy-preserving alternative. To this day, such systems based on the radar are not widely researched. In our work, we introduce a novel approach that uses the Doppler signal of an ultra-wideband (UWB) radar as an input to deep neural networks for the classification of driving activities. In contrast to previous work in the domain, we focus on generalization to unseen persons and make a new radar driving activity dataset (RaDA) available to the scientific community to encourage comparison and the benchmarking of future methods.
Collapse
Affiliation(s)
- Iuliia Brishtel
- Department of Augmented Vision, German Research Center for Artificial Intelligence, Trippstadter Str. 122, 67663 Kaiserslautern, Germany
- Department of Computer Science, RPTU, Erwin-Schrödinger-Str. 57, 67663 Kaiserslautern, Germany
| | - Stephan Krauss
- Department of Augmented Vision, German Research Center for Artificial Intelligence, Trippstadter Str. 122, 67663 Kaiserslautern, Germany
| | - Mahdi Chamseddine
- Department of Augmented Vision, German Research Center for Artificial Intelligence, Trippstadter Str. 122, 67663 Kaiserslautern, Germany
| | - Jason Raphael Rambach
- Department of Augmented Vision, German Research Center for Artificial Intelligence, Trippstadter Str. 122, 67663 Kaiserslautern, Germany
| | - Didier Stricker
- Department of Augmented Vision, German Research Center for Artificial Intelligence, Trippstadter Str. 122, 67663 Kaiserslautern, Germany
- Department of Computer Science, RPTU, Erwin-Schrödinger-Str. 57, 67663 Kaiserslautern, Germany
| |
Collapse
|
4
|
Gao Z, Ali L, Wang C, Liu R, Wang C, Qian C, Sung H, Meng F. Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection. SENSORS (BASEL, SWITZERLAND) 2022; 22:7560. [PMID: 36236659 PMCID: PMC9573470 DOI: 10.3390/s22197560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 09/21/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0-6.3%, the respiration detection was 0-9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%.
Collapse
Affiliation(s)
- Zhiqiang Gao
- School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
| | - Luqman Ali
- School of Information and Communication, Harbin Institute of Technology, Harbin 150001, China
| | - Cong Wang
- School of Information and Communication, Harbin Institute of Technology, Harbin 150001, China
| | - Ruizhi Liu
- School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
| | - Chunwei Wang
- School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
| | - Cheng Qian
- Ocean College, Zhejiang University, Hangzhou 310027, China
| | - Hokun Sung
- Korea Advanced Nano Fab Center (KANC), Suwon-si 443270, Korea
| | - Fanyi Meng
- School of Information and Communication, Harbin Institute of Technology, Harbin 150001, China
| |
Collapse
|
5
|
Non-Contact Breathing Monitoring Using Sleep Breathing Detection Algorithm (SBDA) Based on UWB Radar Sensors. SENSORS 2022; 22:s22145249. [PMID: 35890928 PMCID: PMC9321517 DOI: 10.3390/s22145249] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/05/2022] [Accepted: 07/09/2022] [Indexed: 01/25/2023]
Abstract
Ultra-wideband radar application for sleep breathing monitoring is hampered by the difficulty of obtaining breathing signals for non-stationary subjects. This occurs due to imprecise signal clutter removal and poor body movement removal algorithms for extracting accurate breathing signals. Therefore, this paper proposed a Sleep Breathing Detection Algorithm (SBDA) to address this challenge. First, SBDA introduces the combination of variance feature with Discrete Wavelet Transform (DWT) to tackle the issue of clutter signals. This method used Daubechies wavelets with five levels of decomposition to satisfy the signal-to-noise ratio in the signal. Second, SBDA implements a curve fit based sinusoidal pattern algorithm for detecting periodic motion. The measurement was taken by comparing the R-square value to differentiate between chest and body movements. Last but not least, SBDA applied the Ensemble Empirical Mode Decomposition (EEMD) method for extracting breathing signals before transforming the signal to the frequency domain using Fast Fourier Transform (FFT) to obtain breathing rate. The analysis was conducted on 15 subjects with normal and abnormal ratings for sleep monitoring. All results were compared with two existing methods obtained from previous literature with Polysomnography (PSG) devices. The result found that SBDA effectively monitors breathing using IR-UWB as it has the lowest average percentage error with only 6.12% compared to the other two existing methods from past research implemented in this dataset.
Collapse
|
6
|
Ou TM, Hu WW, Chang CH, Hsu CC, Wang CH. Experimental demonstration of noncontact vital-sign measurement using pulse radar. Technol Health Care 2022; 30:1223-1231. [DOI: 10.3233/thc-thc220022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUD: Recently, monitoring the vital-sign with the noncontact method is a popular technology. OBJECTIVE: In this work, we present a fully pulse radar system including front-end sensing and back-end data processing. A series of ultra-wide band sensing pulses is generated and radiated to detect the subject’s chest vibration which in turn obtains the required vital-sign signals. METHODS: An artificial plywood with 3 centimeter thickness is placed between a transmitting/receiving antenna of the radar and subject to demonstrate the characteristic of noncontact sensing. The firmware and digital signal processing are also presented in this paper to optimize physiological data quality. RESULTS: The experimental results show that the continuous heart rate and breathing rate can be monitored by this customized system radar module. CONCLUSION: A fully customized ultra-wide band radar for vital-sign application is presented. The radar system plan with wall parameter is also incorporated into the design consideration to meet the FCC requirement and SNR.
Collapse
Affiliation(s)
- Tzu-Ming Ou
- Division of Gastroenterology, Department of Internal Medicine, Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan
| | - Wei-Wen Hu
- Department of Electrical Engineering, National Formosa University, Yunlin, Taiwan
| | - Chia-Hung Chang
- Department of Electrical Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan
| | - Chia-Chin Hsu
- Department of Electrical Engineering, Feng Chia University, Taichung, Taiwan
| | - Chih-Hsuan Wang
- Division of Gastroenterology, Department of Internal Medicine, Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan
| |
Collapse
|
7
|
Xu H, Ebrahim MP, Hasan K, Heydari F, Howley P, Yuce MR. Accurate Heart Rate and Respiration Rate Detection Based on a Higher-Order Harmonics Peak Selection Method Using Radar Non-Contact Sensors. SENSORS 2021; 22:s22010083. [PMID: 35009628 PMCID: PMC8747437 DOI: 10.3390/s22010083] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 08/11/2021] [Accepted: 08/12/2021] [Indexed: 12/01/2022]
Abstract
Vital signs such as heart rate and respiration rate are among the most important physiological signals for health monitoring and medical applications. Impulse radio (IR) ultra-wideband (UWB) radar becomes one of the essential sensors in non-contact vital signs detection. The heart pulse wave is easily corrupted by noise and respiration activity since the heartbeat signal has less power compared with the breathing signal and its harmonics. In this paper, a signal processing technique for a UWB radar system was developed to detect the heart rate and respiration rate. There are four main stages of signal processing: (1) clutter removal to reduce the static random noise from the environment; (2) independent component analysis (ICA) to do dimension reduction and remove noise; (3) using low-pass and high-pass filters to eliminate the out of band noise; (4) modified covariance method for spectrum estimation. Furthermore, higher harmonics of heart rate were used to estimate heart rate and minimize respiration interference. The experiments in this article contain different scenarios including bed angle, body position, as well as interference from the visitor near the bed and away from the bed. The results were compared with the ECG sensor and respiration belt. The average mean absolute error (MAE) of heart rate results is 1.32 for the proposed algorithm.
Collapse
Affiliation(s)
- Hongqiang Xu
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia; (H.X.); (M.P.E.); (K.H.); (F.H.)
| | - Malikeh P. Ebrahim
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia; (H.X.); (M.P.E.); (K.H.); (F.H.)
| | - Kareeb Hasan
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia; (H.X.); (M.P.E.); (K.H.); (F.H.)
| | - Fatemeh Heydari
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia; (H.X.); (M.P.E.); (K.H.); (F.H.)
| | - Paul Howley
- Planet Innovation, Box Hill, VIC 3128, Australia;
| | - Mehmet Rasit Yuce
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia; (H.X.); (M.P.E.); (K.H.); (F.H.)
- Correspondence: ; Tel.: +61-3-990-53932
| |
Collapse
|
8
|
Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars. SENSORS 2021; 21:s21165503. [PMID: 34450945 PMCID: PMC8402280 DOI: 10.3390/s21165503] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 08/09/2021] [Accepted: 08/10/2021] [Indexed: 11/16/2022]
Abstract
Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest-abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.
Collapse
|
9
|
Feasibility of non-contact cardiorespiratory monitoring using impulse-radio ultra-wideband radar in the neonatal intensive care unit. PLoS One 2020; 15:e0243939. [PMID: 33370375 PMCID: PMC7769476 DOI: 10.1371/journal.pone.0243939] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 11/26/2020] [Indexed: 11/23/2022] Open
Abstract
Background Current cardiorespiratory monitoring equipment can cause injuries and infections in neonates with fragile skin. Impulse-radio ultra-wideband (IR-UWB) radar was recently demonstrated to be an effective contactless vital sign monitor in adults. The purpose of this study was to assess heart rates (HRs) and respiratory rates (RRs) in the neonatal intensive care unit (NICU) using IR-UWB radar and to evaluate its accuracy and reliability compared to conventional electrocardiography (ECG)/impedance pneumography (IPG). Methods The HR and RR were recorded in 34 neonates between 3 and 72 days of age during minimal movement (51 measurements in total) using IR-UWB radar (HRRd, RRRd) and ECG/IPG (HRECG, RRIPG) simultaneously. The radar signals were processed in real time using algorithms for neonates. Radar and ECG/IPG measurements were compared using concordance correlation coefficients (CCCs) and Bland-Altman plots. Results From the 34 neonates, 12,530 HR samples and 3,504 RR samples were measured. Both the HR and RR measured using the two methods were highly concordant when the neonates had minimal movements (CCC = 0.95 between the RRRd and RRIPG, CCC = 0.97 between the HRRd and HRECG). In the Bland-Altman plot, the mean biases were 0.17 breaths/min (95% limit of agreement [LOA] -7.0–7.3) between the RRRd and RRIPG and -0.23 bpm (95% LOA -5.3–4.8) between the HRRd and HRECG. Moreover, the agreement for the HR and RR measurements between the two modalities was consistently high regardless of neonate weight. Conclusions A cardiorespiratory monitor using IR-UWB radar may provide accurate non-contact HR and RR estimates without wires and electrodes for neonates in the NICU.
Collapse
|
10
|
Experimental Comparison of IR-UWB Radar and FMCW Radar for Vital Signs. SENSORS 2020; 20:s20226695. [PMID: 33238557 PMCID: PMC7768379 DOI: 10.3390/s20226695] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 11/11/2020] [Accepted: 11/14/2020] [Indexed: 11/17/2022]
Abstract
In this paper, we compare the performances of impulse radio ultra-wideband (IR-UWB) and frequency modulation continuous wave (FMCW) radars in measuring noncontact vital signs such as respiration rate and heart rate. These two type radars have been widely used in various fields and have shown their applicability to extract vital signs in noncontact ways. IR-UWB radar can extract vital signs using distance information. On the other hand, FMCW radar requires phase information to estimate vital signs, and the result can be enhanced with Multi-input Multi-output (MIMO) antenna topologies. By using commercial radar chipsets, the operation of radars under different conditions and frequency bands will also affect the performance of vital sign detection capabilities. We compared the accuracy and signal-to-noise (SNR) ratios of IR-UWB and FMCW radars in various scenarios, such as distance, orientation, carotid pulse, harmonics, and obstacle penetration. In general, the IR-UWB radars offer a slightly better accuracy and higher SNR in comparison to FMCW radar. However, each radar system has its own unique advantages, with IR-UWB exhibiting fewer harmonics and a higher SNR, while FMCW can combine the results from each channel.
Collapse
|
11
|
IR-UWB Sensor Based Fall Detection Method Using CNN Algorithm. SENSORS 2020; 20:s20205948. [PMID: 33096727 PMCID: PMC7589193 DOI: 10.3390/s20205948] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/14/2020] [Accepted: 10/19/2020] [Indexed: 11/17/2022]
Abstract
Falls are the leading cause of fatal injuries in the elderly such as fractures, and secondary damage from falls can lead to death. As such, fall detection is a crucial topic. However, due to the trade-off relationship between privacy preservation, user convenience, and fall detection performance, it is generally difficult to develop a fall detection system that simultaneously satisfies all conditions. The main goal of this study is to build a practical fall detection framework that can effectively classify the various behavior types into "Fall" and "Activities of daily living (ADL)" while securing privacy preservation and user convenience. For this purpose, signal data containing the motion information of objects was collected using a non-contact, unobtrusive, and non-restraint impulse-radio ultra wideband (IR-UWB) radar. These data were then applied to a convolutional neural network (CNN) algorithm to create an object behavior type classifier that can classify the behavior types of objects into "Fall" and "ADL." The data were collected by actually performing various activities of daily living, including falling. The performance of the classifier yielded satisfactory results. By combining an IR-UWB and CNN algorithm, this study demonstrates the feasibility of building a practical fall detection system that exceeds a certain level of detection accuracy while also ensuring privacy preservation and user convenience.
Collapse
|
12
|
Yang X, Zhang X, Qian H, Ding Y, Zhang L. MMT-HEAR: Multiple Moving Targets Heartbeats Estimation and Recovery Using IR-UWB Radars. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:5733-5736. [PMID: 33019276 DOI: 10.1109/embc44109.2020.9175318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Populations around the world are rapidly ageing. Age-friendly environments address the significance of continuous inhome vital sign monitoring. Impulse Radio Ultra-WideBand (IR-UWB) radar serves as a household healthcare assistance, providing non-contact vital sign monitoring without privacy issues and illumination limitation. However, the body movements bring difficulty in extracting heartbeat from radar signals, let alone obtaining complete information with body occlusions among multiple targets. This paper proposes a Multiple Moving Targets Heartbeat Estimation And Recovery (MMT-HEAR) approach to extract vital signs using IR-UWB radars. CLEAN and Joint Probability Data Association (JPDA) algorithms are firstly performed on each radar to estimate target-to-antenna distances of multiple targets. Considering signal obstruction and attenuation for targets occluded by others, the location-based distance optimization is proposed to refine these distances by combining information from all radars. Then the mapping from signal amplitudes to refined distances is introduced and combined with the Variational Nonlinear Chirp Mode Decomposition (VNCMD) to extract vital signs with body movements. To the best of our knowledge, this is the first attempt to monitor vital signs of multiple moving targets with radars. The averaging accuracy for two moving targets heartbeat monitoring during a 20-minutes observation is 85.93% with MMT-HEAR. Compared to two other conventional methods, the MMT-HEAR approach yields improvements of 16.11% and 10.16%, revealing the efficiency and robustness of this proposed approach.
Collapse
|
13
|
Sidikova M, Martinek R, Kawala-Sterniuk A, Ladrova M, Jaros R, Danys L, Simonik P. Vital Sign Monitoring in Car Seats Based on Electrocardiography, Ballistocardiography and Seismocardiography: A Review. SENSORS 2020; 20:s20195699. [PMID: 33036313 PMCID: PMC7582509 DOI: 10.3390/s20195699] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 09/29/2020] [Accepted: 09/30/2020] [Indexed: 12/15/2022]
Abstract
This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated.
Collapse
Affiliation(s)
- Michaela Sidikova
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
- Correspondence: (M.S.); (R.M.)
| | - Radek Martinek
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
- Correspondence: (M.S.); (R.M.)
| | - Aleksandra Kawala-Sterniuk
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Proszkowska 76, 45-758 Opole, Poland;
| | - Martina Ladrova
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
| | - Rene Jaros
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
| | - Lukas Danys
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
| | - Petr Simonik
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
| |
Collapse
|
14
|
Wireless Body Sensor Communication Systems Based on UWB and IBC Technologies: State-of-the-Art and Open Challenges. SENSORS 2020; 20:s20123587. [PMID: 32630376 PMCID: PMC7349302 DOI: 10.3390/s20123587] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 06/18/2020] [Accepted: 06/22/2020] [Indexed: 11/21/2022]
Abstract
In recent years there has been an increasing need for miniature, low-cost, commercially accessible, and user-friendly sensor solutions for wireless body area networks (WBAN), which has led to the adoption of new physical communication interfaces providing distinctive advantages over traditional wireless technologies. Ultra-wideband (UWB) and intrabody communication (IBC) have been the subject of intensive research in recent years due to their promising characteristics as means for short-range, low-power, and low-data-rate wireless interfaces for interconnection of various sensors and devices placed on, inside, or in the close vicinity of the human body. The need for safe and standardized solutions has resulted in the development of two relevant standards, IEEE 802.15.4 (for UWB) and IEEE 802.15.6 (for UWB and IBC), respectively. This paper presents an in-depth overview of recent studies and advances in the field of application of UWB and IBC technologies for wireless body sensor communication systems.
Collapse
|
15
|
Khan F, Ghaffar A, Khan N, Cho SH. An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver. SENSORS 2020; 20:s20092479. [PMID: 32349382 PMCID: PMC7248922 DOI: 10.3390/s20092479] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 04/24/2020] [Accepted: 04/25/2020] [Indexed: 11/16/2022]
Abstract
Non-invasive remote health monitoring plays a vital role in epidemiological situations such as SARS outbreak (2003), MERS (2015) and the recently ongoing outbreak of COVID-19 because it is extremely risky to get close to the patient due to the spread of contagious infections. Non-invasive monitoring is also extremely necessary in situations where it is difficult to use complicated wired connections, such as ECG monitoring for infants, burn victims or during rescue missions when people are buried during building collapses/earthquakes. Due to the unique characteristics such as higher penetration capabilities, extremely precise ranging, low power requirement, low cost, simple hardware and robustness to multipath interferences, Impulse Radio Ultra Wideband (IR-UWB) technology is appropriate for non-invasive medical applications. IR-UWB sensors detect the macro as well as micro movement inside the human body due to its fine range resolution. The two vital signs, i.e., respiration rate and heart rate, can be measured by IR-UWB radar by measuring the change in the magnitude of signal due to displacement caused by human lungs, heart during respiration and heart beating. This paper reviews recent advances in IR- UWB radar sensor design for healthcare, such as vital signs measurements of a stationary human, vitals of a non-stationary human, vital signs of people in a vehicle, through the wall vitals measurement, neonate’s health monitoring, fall detection, sleep monitoring and medical imaging. Although we have covered many topics related to health monitoring using IR-UWB, this paper is mainly focused on signal processing techniques for measurement of vital signs, i.e., respiration and heart rate monitoring.
Collapse
Affiliation(s)
- Faheem Khan
- Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea; (F.K.); (A.G.)
- Department of Electrical Engineering, Engineering University, Peshawar 25000, Pakistan;
| | - Asim Ghaffar
- Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea; (F.K.); (A.G.)
| | - Naeem Khan
- Department of Electrical Engineering, Engineering University, Peshawar 25000, Pakistan;
| | - Sung Ho Cho
- Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea; (F.K.); (A.G.)
- Correspondence:
| |
Collapse
|
16
|
Wang J, Warnecke JM, Haghi M, Deserno TM. Unobtrusive Health Monitoring in Private Spaces: The Smart Vehicle. SENSORS (BASEL, SWITZERLAND) 2020; 20:E2442. [PMID: 32344815 PMCID: PMC7249030 DOI: 10.3390/s20092442] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 04/22/2020] [Accepted: 04/23/2020] [Indexed: 11/18/2022]
Abstract
Unobtrusive in-vehicle health monitoring has the potential to use the driving time to perform regular medical check-ups. This work intends to provide a guide to currently proposed sensor systems for in-vehicle monitoring and to answer, in particular, the questions: (1) Which sensors are suitable for in-vehicle data collection? (2) Where should the sensors be placed? (3) Which biosignals or vital signs can be monitored in the vehicle? (4) Which purposes can be supported with the health data? We reviewed retrospective literature systematically and summarized the up-to-date research on leveraging sensor technology for unobtrusive in-vehicle health monitoring. PubMed, IEEE Xplore, and Scopus delivered 959 articles. We firstly screened titles and abstracts for relevance. Thereafter, we assessed the entire articles. Finally, 46 papers were included and analyzed. A guide is provided to the currently proposed sensor systems. Through this guide, potential sensor information can be derived from the biomedical data needed for respective purposes. The suggested locations for the corresponding sensors are also linked. Fifteen types of sensors were found. Driver-centered locations, such as steering wheel, car seat, and windscreen, are frequently used for mounting unobtrusive sensors, through which some typical biosignals like heart rate and respiration rate are measured. To date, most research focuses on sensor technology development, and most application-driven research aims at driving safety. Health-oriented research on the medical use of sensor-derived physiological parameters is still of interest.
Collapse
Affiliation(s)
- Ju Wang
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, D-38106 Braunschweig, Lower Saxony, Germany; (J.M.W.); (M.H.); (T.M.D.)
| | | | | | | |
Collapse
|
17
|
Non-Contact Driver Respiration Rate Detection Technology Based on Suppression of Multipath Interference with Directional Antenna. INFORMATION 2020. [DOI: 10.3390/info11040192] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Non-contact driver respiration rate detection is a challenging problem in the Internet of Vehicles, because the automobile environment is much narrower, and thus the multipath effect is greater. To overcome these challenges, a 2.4 GHz continuous wave forward-scattering radar respiratory detection system is proposed based on the theory that the radar cross-section (RCS) of the human body changes with human breathing. We also analyze the impact of the multipath effect in the vehicle on the received radar signal and compare the output signal captured by a directional antenna with that captured by an omnidirectional antenna in the proposed system. In addition, the mean value of the received signal’s envelope is used to judge whether the driver’s posture is reasonable. Finally, compared with the existing contact respiratory detection system, the actual test results demonstrate the effectiveness of the proposed FSR system, and the driver respiration rates obtained by the proposed system are consistent with those obtained by the contact respiratory detection system.
Collapse
|
18
|
Non-contact diagnosis of obstructive sleep apnea using impulse-radio ultra-wideband radar. Sci Rep 2020; 10:5261. [PMID: 32210266 PMCID: PMC7093464 DOI: 10.1038/s41598-020-62061-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 03/04/2020] [Indexed: 11/24/2022] Open
Abstract
While full-night polysomnography is the gold standard for the diagnosis of obstructive sleep apnea, its limitations include a high cost and first-night effects. This study developed an algorithm for the detection of respiratory events based on impulse-radio ultra-wideband radar and verified its feasibility for the diagnosis of obstructive sleep apnea. A total of 94 subjects were enrolled in this study (23 controls and 24, 14, and 33 with mild, moderate, and severe obstructive sleep apnea, respectively). Abnormal breathing detected by impulse-radio ultra-wideband radar was defined as a drop in the peak radar signal by ≥30% from that in the pre-event baseline. We compared the abnormal breathing index obtained from impulse-radio ultra-wideband radar and apnea–hypopnea index (AHI) measured from polysomnography. There was an excellent agreement between the Abnormal Breathing Index and AHI (intraclass correlation coefficient = 0.927). The overall agreements of the impulse-radio ultra-wideband radar were 0.93 for Model 1 (AHI ≥ 5), 0.91 for Model 2 (AHI ≥ 15), and 1 for Model 3 (AHI ≥ 30). Impulse-radio ultra-wideband radar accurately detected respiratory events (apneas and hypopneas) during sleep without subject contact. Therefore, impulse-radio ultra-wideband radar may be used as a screening tool for obstructive sleep apnea.
Collapse
|
19
|
Zeng X, Robakowski J, Persson M, Monteith A, Fhager A. Investigation of an Ultra Wideband Noise Sensor for Health Monitoring. SENSORS 2020; 20:s20041034. [PMID: 32075120 PMCID: PMC7071039 DOI: 10.3390/s20041034] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 01/27/2020] [Accepted: 02/10/2020] [Indexed: 01/21/2023]
Abstract
Quick on-scene assessment and early intervention is the key to reduce the mortality of stroke and trauma patients, and it is highly desirable to develop ambulance-based diagnostic and monitoring devices in order to provide additional support to the medical personnel. We developed a compact and low cost ultra wideband noise sensor for medical diagnostics and vital sign monitoring in pre-hospital settings. In this work, we demonstrated the functionality of the sensor for respiration and heartbeat monitoring. In the test, metronome was used to manipulate the breathing pattern and the heartbeat rate reference was obtained with a commercial electrocardiogram (ECG) device. With seventeen tests performed for respiration rate detection, sixteen of them were successfully detected. The results also show that it is possible to detect the heartbeat rate accurately with the developed sensor.
Collapse
Affiliation(s)
- Xuezhi Zeng
- Department of Electrical Engineering, Chalmers University of Technology, SE412-96 Gothenburg, Sweden
- Correspondence:
| | - Joakim Robakowski
- Department of Electrical Engineering, Chalmers University of Technology, SE412-96 Gothenburg, Sweden
| | - Mikael Persson
- Department of Electrical Engineering, Chalmers University of Technology, SE412-96 Gothenburg, Sweden
| | - Albert Monteith
- Department of Space, Earth and Environment, Chalmers University of Technology, SE412-96 Gothenburg, Sweden
| | - Andreas Fhager
- Department of Electrical Engineering, Chalmers University of Technology, SE412-96 Gothenburg, Sweden
| |
Collapse
|
20
|
Kim DH. Lane Detection Method with Impulse Radio Ultra-Wideband Radar and Metal Lane Reflectors. SENSORS 2020; 20:s20010324. [PMID: 31935964 PMCID: PMC6982763 DOI: 10.3390/s20010324] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 12/28/2019] [Accepted: 01/04/2020] [Indexed: 11/21/2022]
Abstract
An advanced driver-assistance system (ADAS), based on lane detection technology, detects dangerous situations through various sensors and either warns the driver or takes over direct control of the vehicle. At present, cameras are commonly used for lane detection; however, their performance varies widely depending on the lighting conditions. Consequently, many studies have focused on using radar for lane detection. However, when using radar, it is difficult to distinguish between the plain road surface and painted lane markers, necessitating the use of radar reflectors for guidance. Previous studies have used long-range radars which may receive interference signals from various objects, including other vehicles, pedestrians, and buildings, thereby hampering lane detection. Therefore, we propose a lane detection method that uses an impulse radio ultra-wideband radar with high-range resolution and metal lane markers installed at regular intervals on the road. Lane detection and departure is realized upon using the periodically reflected signals as well as vehicle speed data as inputs. For verification, a field test was conducted by attaching radar to a vehicle and installing metal lane markers on the road. Experimental scenarios were established by varying the position and movement of the vehicle, and it was demonstrated that the proposed method enables lane detection based on the data measured.
Collapse
Affiliation(s)
- Dae-Hyun Kim
- ICT Based Public Transportation Research Team, Korea Railroad Research Institute, Uiwang 16105, Korea
| |
Collapse
|
21
|
Noncontact Detection of Respiration Rate Based on Forward Scatter Radar. SENSORS 2019; 19:s19214778. [PMID: 31684132 PMCID: PMC6864815 DOI: 10.3390/s19214778] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 10/18/2019] [Accepted: 10/31/2019] [Indexed: 11/28/2022]
Abstract
Bioradar-based noncontact breathing detection technology has been widely studied due to its superior detection performance. In this paper, a breath detection mechanism based on the change in radar cross section (RCS) is proposed by using a forward scatter radar and the deduction of the mathematical model of the received signal. Furthermore, we completed human breathing detection experiments in an anechoic chamber and in an ordinary chamber; we obtained the breathing rate through envelope detection in cases where the human orientation angle was 0, 30, 60, and 90°. The analysis of the measured data shows that the theoretical model fits well with the measured results. Compared with the existing single-base radar detection schemes, the proposed scheme can detect human respiratory rates in different orientations.
Collapse
|
22
|
Park JY, Lee Y, Choi YW, Heo R, Park HK, Cho SH, Cho SH, Lim YH. Preclinical Evaluation of a Noncontact Simultaneous Monitoring Method for Respiration and Carotid Pulsation Using Impulse-Radio Ultra-Wideband Radar. Sci Rep 2019; 9:11892. [PMID: 31417149 PMCID: PMC6695386 DOI: 10.1038/s41598-019-48386-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 08/05/2019] [Indexed: 11/09/2022] Open
Abstract
There has been the possibility for respiration and carotid pulsation to be simultaneously monitored from a distance using impulse-radio ultra-wideband (IR-UWB) radar. Therefore, we investigated the validity of simultaneous respiratory rates (RR), pulse rates (PR) and R-R interval measurement using IR-UWB radar. We included 19 patients with a normal sinus rhythm (NSR) and 14 patients with persistent atrial fibrillation (PeAF). The RR, PR, R-R interval and rhythm were obtained simultaneously from the right carotid artery area in a supine position and under normal breathing conditions using IR-UWB radar. There was excellent agreement between the RR obtained by IR-UWB radar and that manually counted by a physician (intraclass correlation coefficient [ICC] 0.852). In the NSR group, there was excellent agreement between the PR (ICC 0.985), average R-R interval (ICC 0.999), and individual R-R interval (ICC 0.910) measured by IR-UWB radar and electrocardiography. In the PeAF group, PR (ICC 0.930), average R-R interval (ICC 0.957) and individual R-R interval (ICC 0.701) also agreed well between the two methods. These results demonstrate that IR-UWB radar can simultaneously monitor respiration, carotid pulse and heart rhythm with high precision and may thus be utilized as a noncontact continuous vital sign monitoring in clinical practice.
Collapse
Affiliation(s)
- Jun-Young Park
- Department of Electronics and Computer Engineering, Hanyang University, Seoul, 04763, Republic of Korea
| | - Yonggu Lee
- Division of Cardiology, Department of Internal Medicine, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea
| | - Yeon-Woo Choi
- Division of Cardiology, Department of Internal Medicine, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea
| | - Ran Heo
- Division of Cardiology, Department of Internal Medicine, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea
| | - Hyun-Kyung Park
- Department of Pediatrics, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea
| | - Seok-Hyun Cho
- Department of Otorhinolaryngology, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea
| | - Sung Ho Cho
- Department of Electronics and Computer Engineering, Hanyang University, Seoul, 04763, Republic of Korea.
| | - Young-Hyo Lim
- Division of Cardiology, Department of Internal Medicine, College of Medicine, Hanyang University, Seoul, 04763, Republic of Korea.
| |
Collapse
|
23
|
Kang S, Lee Y, Lim YH, Park HK, Cho SH, Cho SH. Validation of noncontact cardiorespiratory monitoring using impulse-radio ultra-wideband radar against nocturnal polysomnography. Sleep Breath 2019; 24:841-848. [DOI: 10.1007/s11325-019-01908-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 07/18/2019] [Accepted: 07/24/2019] [Indexed: 12/01/2022]
|
24
|
Kim JD, Lee WH, Lee Y, Lee HJ, Cha T, Kim SH, Song KM, Lim YH, Cho SH, Cho SH, Park HK. Non-contact respiration monitoring using impulse radio ultrawideband radar in neonates. ROYAL SOCIETY OPEN SCIENCE 2019; 6:190149. [PMID: 31312485 PMCID: PMC6599793 DOI: 10.1098/rsos.190149] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 05/10/2019] [Indexed: 05/04/2023]
Abstract
Vital sign monitoring in neonates requires adhesive electrodes, which often damage fragile newborn skin. Because impulse radio ultrawideband (IR-UWB) radar has been reported to recognize chest movement without contact in adult humans, IR-UWB may be used to measure respiratory rates (RRs) in a non-contact fashion. We investigated the feasibility of radar sensors for respiration monitoring in neonates without any respiratory support to compare the accuracy and reliability of radar measurements with those of conventional impedance pneumography measurements. In the neonatal intensive care unit, RRs were measured using radar (RRRd) and impedance pneumography (RRIP) simultaneously. The neonatal voluntary movements were measured using the radar sensor and categorized into three levels (low [M0], intermediate [M1] and high [M2]). RRRd highly agreed with RRIP (r = 0.90; intraclass correlation coefficient [ICC] = 0.846 [0.835-0.856]). For the M0 movement, there was good agreement between RRRd and RRIP (ICC = 0.893; mean bias -0.15 [limits of agreement (LOA) -9.6 to 10.0]). However, the agreement was slightly lower for the M1 (ICC = 0.833; mean bias = 0.95 [LOA -11.4 to 13.3]) and M2 (ICC = 0.749; mean bias = 3.04 [LOA -9.30 to 15.4]) movements than for the M0 movement. In conclusion, IR-UWB radar can provide accurate and reliable estimates of RR in neonates in a non-contact fashion. The performance of radar measurements could be affected by neonate movement.
Collapse
Affiliation(s)
- Jong Deok Kim
- Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Won Hyuk Lee
- Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Yonggu Lee
- Division of Cardiology, Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Hyun Ju Lee
- Division of Neonatology, Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Teahyen Cha
- Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Seung Hyun Kim
- Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Ki-Min Song
- Department of Health Sciences, Graduate School, Hanyang University, Seoul, Republic of Korea
| | - Young-Hyo Lim
- Division of Cardiology, Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Seok Hyun Cho
- Department of Otorhinolaryngology, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Sung Ho Cho
- Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea
- Authors for correspondence: Sung Ho Cho e-mail:
| | - Hyun-Kyung Park
- Division of Neonatology, Department of Pediatrics, Hanyang University College of Medicine, Seoul, Republic of Korea
- Authors for correspondence: Hyun-Kyung Park e-mail:
| |
Collapse
|
25
|
Abstract
Heart rate (HR) change during sleepy driving has never been investigated. Healthy volunteers who planned to drive a long distance were recruited and monitored with a 24-hour Holter. Six healthy volunteers were enrolled. Their mean driving time was 297.7 ± 111 minutes. Mean duration of sleepy time while driving was 27 ± 24.5 minutes. Driving HR showed a trend for increment as compared to day time mean HR, from 85 ± 5.6 to 89.8 ± 5.6 beats/min (by 7%) (P = 0.093). Mean HR while sleepy driving significantly decreased to 81.5 ± 9.2 beats/min by 9.3% ± 7.4% (P = 0.046). This pilot study for the first time demonstrated that HR decreased while sleepy driving.
Collapse
Affiliation(s)
- Sang-Ho Jo
- Division of Cardiology, Department of Internal Medicine, Hallym University Sacred Heart Hospital, Anyang, Korea
| | | | - Dong Kyoo Kim
- Electronics and Telecommunications Research Institute, Daejeon, Korea
| |
Collapse
|
26
|
Random-Noise Denoising and Clutter Elimination of Human Respiration Movements Based on an Improved Time Window Selection Algorithm Using Wavelet Transform. SENSORS 2018; 19:s19010095. [PMID: 30597894 PMCID: PMC6338991 DOI: 10.3390/s19010095] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 12/11/2018] [Accepted: 12/24/2018] [Indexed: 11/17/2022]
Abstract
This paper considers vital signs (VS) such as respiration movement detection of human subjects using an impulse ultra-wideband (UWB) through-wall radar with an improved sensing algorithm for random-noise de-noising and clutter elimination. One filter is used to improve the signal-to-noise ratio (SNR) of these VS signals. Using the wavelet packet decomposition, the standard deviation based spectral kurtosis is employed to analyze the signal characteristics to provide the distance estimate between the radar and human subject. The data size is reduced based on a defined region of interest (ROI), and this improves the system efficiency. The respiration frequency is estimated using a multiple time window selection algorithm. Experimental results are presented which illustrate the efficacy and reliability of this method. The proposed method is shown to provide better VS estimation than existing techniques in the literature.
Collapse
|
27
|
HEAR: Approach for Heartbeat Monitoring with Body Movement Compensation by IR-UWB Radar. SENSORS 2018; 18:s18093077. [PMID: 30217049 PMCID: PMC6165065 DOI: 10.3390/s18093077] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 09/01/2018] [Accepted: 09/07/2018] [Indexed: 11/16/2022]
Abstract
Further applications of impulse radio ultra-wideband radar in mobile health are hindered by the difficulty in extracting such vital signals as heartbeats from moving targets. Although the empirical mode decomposition based method is applied in recovering waveforms of heartbeats and estimating heart rates, the instantaneous heart rate is not achievable. This paper proposes a Heartbeat Estimation And Recovery (HEAR) approach to expand the application to mobile scenarios and extract instantaneous heartbeats. Firstly, the HEAR approach acquires vital signals by mapping maximum echo amplitudes to the fast time delay and compensating large body movements. Secondly, HEAR adopts the variational nonlinear chirp mode decomposition in extracting instantaneous frequencies of heartbeats. Thirdly, HEAR extends the clutter removal method based on the wavelet decomposition with a two-parameter exponential threshold. Compared to heart rates simultaneously collected by electrocardiograms (ECG), HEAR achieves a minimum error rate 4.6% in moving state and 2.25% in resting state. The Bland⁻Altman analysis verifies the consistency of beat-to-beat intervals in ECG and extracted heartbeat signals with the mean deviation smaller than 0.1 s. It indicates that HEAR is practical in offering clinical diagnoses such as the heart rate variability analysis in mobile monitoring.
Collapse
|