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Shahbakhti M, Hakimi N, Horschig JM, Floor-Westerdijk M, Claassen J, Colier WNJM. Estimation of Respiratory Rate during Biking with a Single Sensor Functional Near-Infrared Spectroscopy (fNIRS) System. SENSORS (BASEL, SWITZERLAND) 2023; 23:3632. [PMID: 37050692 PMCID: PMC10099192 DOI: 10.3390/s23073632] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 03/28/2023] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
OBJECTIVE The employment of wearable systems for continuous monitoring of vital signs is increasing. However, due to substantial susceptibility of conventional bio-signals recorded by wearable systems to motion artifacts, estimation of the respiratory rate (RR) during physical activities is a challenging task. Alternatively, functional Near-Infrared Spectroscopy (fNIRS) can be used, which has been proven less vulnerable to the subject's movements. This paper proposes a fusion-based method for estimating RR during bicycling from fNIRS signals recorded by a wearable system. METHODS Firstly, five respiratory modulations are extracted, based on amplitude, frequency, and intensity of the oxygenated hemoglobin concentration (O2Hb) signal. Secondly, the dominant frequency of each modulation is computed using the fast Fourier transform. Finally, dominant frequencies of all modulations are fused, based on averaging, to estimate RR. The performance of the proposed method was validated on 22 young healthy subjects, whose respiratory and fNIRS signals were simultaneously recorded during a bicycling task, and compared against a zero delay Fourier domain band-pass filter. RESULTS The comparison between results obtained by the proposed method and band-pass filtering indicated the superiority of the former, with a lower mean absolute error (3.66 vs. 11.06 breaths per minute, p<0.05). The proposed fusion strategy also outperformed RR estimations based on the analysis of individual modulation. SIGNIFICANCE This study orients towards the practical limitations of traditional bio-signals for RR estimation during physical activities.
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Affiliation(s)
- Mohammad Shahbakhti
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
- Biomedical Engineering Institute, Kaunas University of Technology, K. Barsausko 59, LT-51423 Kaunas, Lithuania
| | - Naser Hakimi
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
- Department of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The Netherlands
| | - Jörn M. Horschig
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands
| | | | - Jurgen Claassen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Houtlaan 4, 6525 XZ Nijmegen, The Netherlands
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Kaduk SI, Roberts AP, Stanton NA. Circadian effect on physiology and driving performance in semi-automated vehicles. THEORETICAL ISSUES IN ERGONOMICS SCIENCE 2022. [DOI: 10.1080/1463922x.2022.2121440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
| | - A. P. Roberts
- Transportation Research Group, Faculty of Engineering and the Environment, University of Southampton, Southampton, UK
| | - N. A. Stanton
- School of Civil Engineering and the Environment, University of Southampton, Southampton, UK
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A BLE-Connected Piezoresistive and Inertial Chest Band for Remote Monitoring of the Respiratory Activity by an Android Application: Hardware Design and Software Optimization. FUTURE INTERNET 2022. [DOI: 10.3390/fi14060183] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Breathing is essential for human life. Issues related to respiration can be an indicator of problems related to the cardiorespiratory system; thus, accurate breathing monitoring is fundamental for establishing the patient’s condition. This paper presents a ready-to-use and discreet chest band for monitoring the respiratory parameters based on the piezoresistive transduction mechanism. In detail, it relies on a strain sensor realized with a pressure-sensitive fabric (EeonTex LTT-SLPA-20K) for monitoring the chest movements induced by respiration. In addition, the band includes an Inertial Measurement Unit (IMU), which is used to remove the motion artefacts from the acquired signal, thereby improving the measurement reliability. Moreover, the band comprises a low-power conditioning and acquisition section that processes the signal from sensors, providing a reliable measurement of the respiration rate (RR), in addition to other breathing parameters, such as inhalation (TI) and exhalation (TE) times, inhalation-to-exhalation ratio (IER), and flow rate (V). The device wirelessly transmits the extracted parameters to a host device, where a custom mobile application displays them. Different test campaigns were carried out to evaluate the performance of the designed chest band in measuring the RR, by comparing the measurements provided by the chest band with those obtained by breath count. In detail, six users, of different genders, ages, and physical constitutions, were involved in the tests. The obtained results demonstrated the effectiveness of the proposed approach in detecting the RR. The achieved performance was in line with that of other RR monitoring systems based on piezoresistive textiles, but which use more powerful acquisition systems or have low wearability. In particular, the inertia-assisted piezoresistive chest band obtained a Pearson correlation coefficient with respect to the measurements based on breath count of 0.96 when the user was seated. Finally, Bland–Altman analysis demonstrated that the developed system obtained 0.68 Breaths Per Minute (BrPM) mean difference (MD), and Limits of Agreement (LoAs) of +3.20 and −1.75 BrPM when the user was seated.
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Mechanical sensors based on two-dimensional materials: Sensing mechanisms, structural designs and wearable applications. iScience 2022; 25:103728. [PMID: 35072014 PMCID: PMC8762477 DOI: 10.1016/j.isci.2021.103728] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Compared with bulk materials, atomically thin two-dimensional (2D) crystals possess a range of unique mechanical properties, including relatively high in-plane stiffness and large bending flexibility. The atomic 2D building blocks can be reassembled into precisely designed heterogeneous composite structures of various geometries with customized mechanical sensing behaviors. Due to their small specific density, high flexibility, and environmental adaptability, mechanical sensors based on 2D materials can conform to soft and curved surfaces, thus providing suitable solutions for functional applications in future wearable devices. In this review, we summarize the latest developments in mechanical sensors based on 2D materials from the perspective of function-oriented applications. First, typical mechanical sensing mechanisms are introduced. Second, we attempt to establish a correspondence between typical structure designs and the performance/multi-functions of the devices. Afterward, several particularly promising areas for potential applications are discussed, following which we present perspectives on current challenges and future opportunities
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Respiration Monitoring via Forcecardiography Sensors. SENSORS 2021; 21:s21123996. [PMID: 34207899 PMCID: PMC8228286 DOI: 10.3390/s21123996] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 06/04/2021] [Accepted: 06/07/2021] [Indexed: 12/26/2022]
Abstract
In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R2 = 0.98) vs. 0.98, 0.11 s (R2 = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.
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Chelliah R, Wei S, Daliri EBM, Rubab M, Elahi F, Yeon SJ, Jo KH, Yan P, Liu S, Oh DH. Development of Nanosensors Based Intelligent Packaging Systems: Food Quality and Medicine. NANOMATERIALS (BASEL, SWITZERLAND) 2021; 11:1515. [PMID: 34201071 PMCID: PMC8226856 DOI: 10.3390/nano11061515] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/01/2021] [Accepted: 06/02/2021] [Indexed: 12/02/2022]
Abstract
The issue of medication noncompliance has resulted in major risks to public safety and financial loss. The new omnipresent medicine enabled by the Internet of things offers fascinating new possibilities. Additionally, an in-home healthcare station (IHHS), it is necessary to meet the rapidly increasing need for routine nursing and on-site diagnosis and prognosis. This article proposes a universal and preventive strategy to drug management based on intelligent and interactive packaging (I2Pack) and IMedBox. The controlled delamination material (CDM) seals and regulates wireless technologies in novel medicine packaging. As such, wearable biomedical sensors may capture a variety of crucial parameters via wireless communication. On-site treatment and prediction of these critical factors are made possible by high-performance architecture. The user interface is also highlighted to make surgery easier for the elderly, disabled, and patients. Land testing incorporates and validates an approach for prototyping I2Pack and iMedBox. Additionally, sustainability, increased product safety, and quality standards are crucial throughout the life sciences. To achieve these standards, intelligent packaging is also used in the food and pharmaceutical industries. These technologies will continuously monitor the quality of a product and communicate with the user. Data carriers, indications, and sensors are the three most important groups. They are not widely used at the moment, although their potential is well understood. Intelligent packaging should be used in these sectors and the functionality of the systems and the values presented in this analysis.
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Affiliation(s)
- Ramachandran Chelliah
- Department of Food Science and Biotechnology, College of Agriculture and Life Science, Kangwon National University, Chuncheon 24341, Korea; (E.B.-M.D.); (F.E.); (S.-J.Y.); (K.h.J.); (P.Y.)
| | - Shuai Wei
- College of Food Science and Technology, Guangdong Ocean University, Guangdong Provincial Key Laboratory of Aquatic Products Processing and Safety, Guangdong Province Engineering Laboratory for Marine Biological Products, Guangdong Provincial Engineering Technology Research Center of Marine Food, Key Laboratory of Advanced Processing of Aquatic Product of Guangdong Higher Education Institution, Zhanjiang 524088, China;
- Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
| | - Eric Banan-Mwine Daliri
- Department of Food Science and Biotechnology, College of Agriculture and Life Science, Kangwon National University, Chuncheon 24341, Korea; (E.B.-M.D.); (F.E.); (S.-J.Y.); (K.h.J.); (P.Y.)
| | - Momna Rubab
- School of Food and Agricultural Sciences, University of Management and Technology, Lahore 54770, Pakistan;
| | - Fazle Elahi
- Department of Food Science and Biotechnology, College of Agriculture and Life Science, Kangwon National University, Chuncheon 24341, Korea; (E.B.-M.D.); (F.E.); (S.-J.Y.); (K.h.J.); (P.Y.)
| | - Su-Jung Yeon
- Department of Food Science and Biotechnology, College of Agriculture and Life Science, Kangwon National University, Chuncheon 24341, Korea; (E.B.-M.D.); (F.E.); (S.-J.Y.); (K.h.J.); (P.Y.)
| | - Kyoung hee Jo
- Department of Food Science and Biotechnology, College of Agriculture and Life Science, Kangwon National University, Chuncheon 24341, Korea; (E.B.-M.D.); (F.E.); (S.-J.Y.); (K.h.J.); (P.Y.)
| | - Pianpian Yan
- Department of Food Science and Biotechnology, College of Agriculture and Life Science, Kangwon National University, Chuncheon 24341, Korea; (E.B.-M.D.); (F.E.); (S.-J.Y.); (K.h.J.); (P.Y.)
| | - Shucheng Liu
- College of Food Science and Technology, Guangdong Ocean University, Guangdong Provincial Key Laboratory of Aquatic Products Processing and Safety, Guangdong Province Engineering Laboratory for Marine Biological Products, Guangdong Provincial Engineering Technology Research Center of Marine Food, Key Laboratory of Advanced Processing of Aquatic Product of Guangdong Higher Education Institution, Zhanjiang 524088, China;
- Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
| | - Deog Hwan Oh
- Department of Food Science and Biotechnology, College of Agriculture and Life Science, Kangwon National University, Chuncheon 24341, Korea; (E.B.-M.D.); (F.E.); (S.-J.Y.); (K.h.J.); (P.Y.)
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da Cunha-Martins BSM, Motta-Ribeiro GC, Jandre FC. Short-term usage of three non-invasive ventilation interfaces causes progressive discomfort in healthy adults. RESEARCH ON BIOMEDICAL ENGINEERING 2021. [PMCID: PMC7787606 DOI: 10.1007/s42600-020-00114-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
Purpose To evaluate the effect of three different non-invasive ventilation (NIV) interfaces on the subjective discomfort of healthy individuals, and on a set of physiological parameters hypothesized to change in correspondence to discomfort. Methods Continuous pressure NIV was applied to 20 subjects using Total Face, Nasal, and Face masks for 10 min each. Tidal volume (VT) and respiratory period (RP) were estimated from respiratory inductance plethysmography. Electrodermal activity was estimated from conductance signals. Heart rate variability was measured using the time-domain indices SDNN and RMSSD, and the respiratory sinus arrhythmia amplitude (RSAp). Parameters were referenced to 5-min rest periods at beginning and end of protocol. A Likert-like scale of subjective discomfort with the masks and the ventilation was applied after 1, 5, and 9 min using each mask. Results RP and VT increased with the three mask models. Whereas the mean heart rate and RSAp did not change, both SDNN and RMSSD increased during NIV with Nasal and Face masks. Spontaneous electrodermal activity fluctuations were less frequent during NIV than at rest, with significant differences for Total Face and Nasal masks. Discomfort with all masks increased from minutes 1 to 9, markedly in the Total Face mask, considered most uncomfortable by 11 subjects. Conclusion In healthy subjects, the three masks resulted in similar respiratory responses to NIV. Correspondence between changes in physiological parameters and discomfort with NIV interface could not be detected, whereas self-report with the Likert-like scale identified progressive discomfort and the Total Face mask as the most uncomfortable interface. Supplementary Information The online version contains supplementary material available at 10.1007/s42600-020-00114-3.
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Affiliation(s)
- Beatriz Silva Menezes da Cunha-Martins
- Biomedical Engineering Programme, COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
- Instituto Nacional de Câncer José Alencar Gomes da Silva, Rio de Janeiro, Brazil
| | | | - Frederico Caetano Jandre
- Biomedical Engineering Programme, COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
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Senyurek V, Imtiaz M, Belsare P, Tiffany S, Sazonov E. Electromyogram in Cigarette Smoking Activity Recognition. SIGNALS 2021; 2:87-97. [PMID: 36380814 PMCID: PMC9645678 DOI: 10.3390/signals2010008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
In this study, information from surface electromyogram (sEMG) signals was used to recognize cigarette smoking. The sEMG signals collected from lower arm were used in two different ways: (1) as an individual predictor of smoking activity and (2) as an additional sensor/modality along with the inertial measurement unit (IMU) to augment recognition performance. A convolutional and a recurrent neural network were utilized to recognize smoking-related hand gestures. The model was developed and evaluated with leave-one-subject-out (LOSO) cross-validation on a dataset from 16 subjects who performed ten activities of daily living including smoking. The results show that smoking detection using only sEMG signal achieved an F1-score of 75% in person-independent cross-validation. The combination of sEMG and IMU improved reached the F1-score of 84%, while IMU alone sensor modality was 81%. The study showed that using only sEMG signals would not provide superior cigarette smoking detection performance relative to IMU signals. However, sEMG improved smoking detection results when combined with IMU signals without using an additional device.
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Affiliation(s)
- Volkan Senyurek
- Geosystems Research Institute, Mississippi State University, Starkville, MS 39759, USA
| | - Masudul Imtiaz
- Department of Electrical and Computer Engineering, Clarkson University, Postdam, NY 13699, USA
| | - Prajakta Belsare
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA
| | - Stephen Tiffany
- Department of Psychology, University at Buffalo, The State University of New York, Buffalo, NY 14260, USA
| | - Edward Sazonov
- Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA
- Correspondence:
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Nicolò A, Massaroni C, Schena E, Sacchetti M. The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6396. [PMID: 33182463 PMCID: PMC7665156 DOI: 10.3390/s20216396] [Citation(s) in RCA: 99] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 11/05/2020] [Accepted: 11/08/2020] [Indexed: 12/11/2022]
Abstract
Respiratory rate is a fundamental vital sign that is sensitive to different pathological conditions (e.g., adverse cardiac events, pneumonia, and clinical deterioration) and stressors, including emotional stress, cognitive load, heat, cold, physical effort, and exercise-induced fatigue. The sensitivity of respiratory rate to these conditions is superior compared to that of most of the other vital signs, and the abundance of suitable technological solutions measuring respiratory rate has important implications for healthcare, occupational settings, and sport. However, respiratory rate is still too often not routinely monitored in these fields of use. This review presents a multidisciplinary approach to respiratory monitoring, with the aim to improve the development and efficacy of respiratory monitoring services. We have identified thirteen monitoring goals where the use of the respiratory rate is invaluable, and for each of them we have described suitable sensors and techniques to monitor respiratory rate in specific measurement scenarios. We have also provided a physiological rationale corroborating the importance of respiratory rate monitoring and an original multidisciplinary framework for the development of respiratory monitoring services. This review is expected to advance the field of respiratory monitoring and favor synergies between different disciplines to accomplish this goal.
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Affiliation(s)
- Andrea Nicolò
- Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, 00135 Rome, Italy;
| | - Carlo Massaroni
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy; (C.M.); (E.S.)
| | - Emiliano Schena
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy; (C.M.); (E.S.)
| | - Massimo Sacchetti
- Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, 00135 Rome, Italy;
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Vega-Barbas M, Diaz-Olivares JA, Lu K, Forsman M, Seoane F, Abtahi F. P-Ergonomics Platform: Toward Precise, Pervasive, and Personalized Ergonomics using Wearable Sensors and Edge Computing. SENSORS 2019; 19:s19051225. [PMID: 30862019 PMCID: PMC6427483 DOI: 10.3390/s19051225] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 03/01/2019] [Accepted: 03/06/2019] [Indexed: 12/03/2022]
Abstract
Preventive healthcare has attracted much attention recently. Improving people’s lifestyles and promoting a healthy diet and wellbeing are important, but the importance of work-related diseases should not be undermined. Musculoskeletal disorders (MSDs) are among the most common work-related health problems. Ergonomists already assess MSD risk factors and suggest changes in workplaces. However, existing methods are mainly based on visual observations, which have a relatively low reliability and cover only part of the workday. These suggestions concern the overall workplace and the organization of work, but rarely includes individuals’ work techniques. In this work, we propose a precise and pervasive ergonomic platform for continuous risk assessment. The system collects data from wearable sensors, which are synchronized and processed by a mobile computing layer, from which exposure statistics and risk assessments may be drawn, and finally, are stored at the server layer for further analyses at both individual and group levels. The platform also enables continuous feedback to the worker to support behavioral changes. The deployed cloud platform in Amazon Web Services instances showed sufficient system flexibility to affordably fulfill requirements of small to medium enterprises, while it is expandable for larger corporations. The system usability scale of 76.6 indicates an acceptable grade of usability.
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Affiliation(s)
- Mario Vega-Barbas
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 17177 Solna, Sweden.
| | - Jose A Diaz-Olivares
- School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, 14157 Huddinge, Sweden.
| | - Ke Lu
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 17177 Solna, Sweden.
| | - Mikael Forsman
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 17177 Solna, Sweden.
- School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, 14157 Huddinge, Sweden.
| | - Fernando Seoane
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Hälsovägen 7, 14157 Huddinge, Sweden.
- Swedish School of Textiles, University of Borås, Allégatan 1, 50190 Borås, Sweden.
- Departm and t of Biomedical Engineering, Karolinska University Hospital, 1, 17176 Solna, Sweden.
| | - Farhad Abtahi
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 17177 Solna, Sweden.
- School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, 14157 Huddinge, Sweden.
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Massaroni C, Nicolò A, Lo Presti D, Sacchetti M, Silvestri S, Schena E. Contact-Based Methods for Measuring Respiratory Rate. SENSORS (BASEL, SWITZERLAND) 2019; 19:E908. [PMID: 30795595 PMCID: PMC6413190 DOI: 10.3390/s19040908] [Citation(s) in RCA: 125] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 02/15/2019] [Accepted: 02/17/2019] [Indexed: 01/05/2023]
Abstract
There is an ever-growing demand for measuring respiratory variables during a variety of applications, including monitoring in clinical and occupational settings, and during sporting activities and exercise. Special attention is devoted to the monitoring of respiratory rate because it is a vital sign, which responds to a variety of stressors. There are different methods for measuring respiratory rate, which can be classed as contact-based or contactless. The present paper provides an overview of the currently available contact-based methods for measuring respiratory rate. For these methods, the sensing element (or part of the instrument containing it) is attached to the subject's body. Methods based upon the recording of respiratory airflow, sounds, air temperature, air humidity, air components, chest wall movements, and modulation of the cardiac activity are presented. Working principles, metrological characteristics, and applications in the respiratory monitoring field are presented to explore potential development and applicability for each method.
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Affiliation(s)
- Carlo Massaroni
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy.
| | - Andrea Nicolò
- Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", 00135 Rome, Italy.
| | - Daniela Lo Presti
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy.
| | - Massimo Sacchetti
- Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", 00135 Rome, Italy.
| | - Sergio Silvestri
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy.
| | - Emiliano Schena
- Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy.
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Lu K, Yang L, Seoane F, Abtahi F, Forsman M, Lindecrantz K. Fusion of Heart Rate, Respiration and Motion Measurements from a Wearable Sensor System to Enhance Energy Expenditure Estimation. SENSORS (BASEL, SWITZERLAND) 2018; 18:E3092. [PMID: 30223429 PMCID: PMC6164120 DOI: 10.3390/s18093092] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 09/07/2018] [Accepted: 09/11/2018] [Indexed: 02/05/2023]
Abstract
This paper presents a new method that integrates heart rate, respiration, and motion information obtained from a wearable sensor system to estimate energy expenditure. The system measures electrocardiography, impedance pneumography, and acceleration from upper and lower limbs. A multilayer perceptron neural network model was developed, evaluated, and compared to two existing methods, with data from 11 subjects (mean age, 27 years, range, 21⁻65 years) who performed a 3-h protocol including submaximal tests, simulated work tasks, and periods of rest. Oxygen uptake was measured with an indirect calorimeter as a reference, with a time resolution of 15 s. When compared to the reference, the new model showed a lower mean absolute error (MAE = 1.65 mL/kg/min, R² = 0.92) than the two existing methods, i.e., the flex-HR method (MAE = 2.83 mL/kg/min, R² = 0.75), which uses only heart rate, and arm-leg HR+M method (MAE = 2.12 mL/kg/min, R² = 0.86), which uses heart rate and motion information. As indicated, this new model may, in combination with a wearable system, be useful in occupational and general health applications.
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Affiliation(s)
- Ke Lu
- School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, 141 57 Huddinge, Sweden.
| | - Liyun Yang
- School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, 141 57 Huddinge, Sweden.
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
| | - Fernando Seoane
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Hälsovägen 7, 141 57 Huddinge, Sweden.
- Swedish School of Textiles, University of Borås, Allégatan 1, 501 90 Borås, Sweden.
- Department of Biomedical Engineering, Karolinska University Hospital, 1, 171 76 Solna, Sweden.
| | - Farhad Abtahi
- School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, 141 57 Huddinge, Sweden.
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
| | - Mikael Forsman
- School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Hälsovägen 11C, 141 57 Huddinge, Sweden.
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
| | - Kaj Lindecrantz
- Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
- Swedish School of Textiles, University of Borås, Allégatan 1, 501 90 Borås, Sweden.
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13
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A Wearable System for Real-Time Continuous Monitoring of Physical Activity. JOURNAL OF HEALTHCARE ENGINEERING 2018; 2018:1878354. [PMID: 29849993 PMCID: PMC5925007 DOI: 10.1155/2018/1878354] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Accepted: 01/11/2018] [Indexed: 11/23/2022]
Abstract
Over the last decades, wearable systems have gained interest for monitoring of physiological variables, promoting health, and improving exercise adherence in different populations ranging from elite athletes to patients. In this paper, we present a wearable system for the continuous real-time monitoring of respiratory frequency (fR), heart rate (HR), and movement cadence during physical activity. The system has been experimentally tested in the laboratory (by simulating the breathing pattern with a mechanical ventilator) and by collecting data from one healthy volunteer. Results show the feasibility of the proposed device for real-time continuous monitoring of fR, HR, and movement cadence both in resting condition and during activity. Finally, different synchronization techniques have been investigated to enable simultaneous data collection from different wearable modules.
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14
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Wearable Intrinsically Soft, Stretchable, Flexible Devices for Memories and Computing. SENSORS 2018; 18:s18020367. [PMID: 29382050 PMCID: PMC5855892 DOI: 10.3390/s18020367] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 01/22/2018] [Accepted: 01/23/2018] [Indexed: 12/28/2022]
Abstract
A recent trend in the development of high mass consumption electron devices is towards electronic textiles (e-textiles), smart wearable devices, smart clothes, and flexible or printable electronics. Intrinsically soft, stretchable, flexible, Wearable Memories and Computing devices (WMCs) bring us closer to sci-fi scenarios, where future electronic systems are totally integrated in our everyday outfits and help us in achieving a higher comfort level, interacting for us with other digital devices such as smartphones and domotics, or with analog devices, such as our brain/peripheral nervous system. WMC will enable each of us to contribute to open and big data systems as individual nodes, providing real-time information about physical and environmental parameters (including air pollution monitoring, sound and light pollution, chemical or radioactive fallout alert, network availability, and so on). Furthermore, WMC could be directly connected to human brain and enable extremely fast operation and unprecedented interface complexity, directly mapping the continuous states available to biological systems. This review focuses on recent advances in nanotechnology and materials science and pays particular attention to any result and promising technology to enable intrinsically soft, stretchable, flexible WMC.
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15
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A Wearable System for the Evaluation of the Human-Horse Interaction: A Preliminary Study. ELECTRONICS 2016. [DOI: 10.3390/electronics5040063] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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16
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Lanata A, Guidi A, Baragli P, Paradiso R, Valenza G, Scilingo EP. Removing movement artifacts from equine ECG recordings acquired with textile electrodes. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2015:1955-8. [PMID: 26736667 DOI: 10.1109/embc.2015.7318767] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This study reports on the implementation of a novel system to detect and reduce movement artifact (MA) contribution in electrocardiogram (ECG) recordings acquired from horses in free movement conditions. The system comprises both integrated textile electrodes for ECG acquisition and one triaxial accelerometer for movement monitoring. Here, ECG and physical activity are continuously acquired from seven horses through the wearable system and a model that integrates cardiovascular and movement information to estimate the MA contribution is implemented. Moreover, in this study we propose a new algorithm where the Stationary Wavelet Transform (SWT) decomposition algorithm is employed to identify and remove movement artifacts from ECG recodigns. Achieved results showed a reduction of MA percentage greater than 40% between before- and after- the application of the proposed algorithm to seven hours of recordings.
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17
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Kim H, Kim JY, Im CH. Fast and Robust Real-Time Estimation of Respiratory Rate from Photoplethysmography. SENSORS 2016; 16:s16091494. [PMID: 27649182 PMCID: PMC5038767 DOI: 10.3390/s16091494] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Revised: 09/08/2016] [Accepted: 09/09/2016] [Indexed: 11/16/2022]
Abstract
Respiratory rate (RR) is a useful vital sign that can not only provide auxiliary information on physiological changes within the human body, but also indicate early symptoms of various diseases. Recently, methods for the estimation of RR from photoplethysmography (PPG) have attracted increased interest, because PPG can be readily recorded using wearable sensors such as smart watches and smart bands. In the present study, we propose a new method for the fast and robust real-time estimation of RR using an adaptive infinite impulse response (IIR) notch filter, which has not yet been applied to the PPG-based estimation of RR. In our offline simulation study, the performance of the proposed method was compared to that of recently developed RR estimation methods called an adaptive lattice-type RR estimator and a Smart Fusion. The results of the simulation study show that the proposed method could not only estimate RR more quickly and more accurately than the conventional methods, but also is most suitable for online RR monitoring systems, as it does not use any overlapping moving windows that require increased computational costs. In order to demonstrate the practical applicability of the proposed method, an online RR estimation system was implemented.
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Affiliation(s)
- Hodam Kim
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.
| | - Jeong-Youn Kim
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.
| | - Chang-Hwan Im
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.
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18
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A Real-Time Health Monitoring System for Remote Cardiac Patients Using Smartphone and Wearable Sensors. Int J Telemed Appl 2015; 2015:373474. [PMID: 26788055 PMCID: PMC4692989 DOI: 10.1155/2015/373474] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Revised: 11/11/2015] [Accepted: 11/12/2015] [Indexed: 11/17/2022] Open
Abstract
Online telemedicine systems are useful due to the possibility of timely and efficient healthcare services. These systems are based on advanced wireless and wearable sensor technologies. The rapid growth in technology has remarkably enhanced the scope of remote health monitoring systems. In this paper, a real-time heart monitoring system is developed considering the cost, ease of application, accuracy, and data security. The system is conceptualized to provide an interface between the doctor and the patients for two-way communication. The main purpose of this study is to facilitate the remote cardiac patients in getting latest healthcare services which might not be possible otherwise due to low doctor-to-patient ratio. The developed monitoring system is then evaluated for 40 individuals (aged between 18 and 66 years) using wearable sensors while holding an Android device (i.e., smartphone under supervision of the experts). The performance analysis shows that the proposed system is reliable and helpful due to high speed. The analyses showed that the proposed system is convenient and reliable and ensures data security at low cost. In addition, the developed system is equipped to generate warning messages to the doctor and patient under critical circumstances.
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19
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Lanata A, Guidi A, Baragli P, Valenza G, Scilingo EP. A Novel Algorithm for Movement Artifact Removal in ECG Signals Acquired from Wearable Systems Applied to Horses. PLoS One 2015; 10:e0140783. [PMID: 26484686 PMCID: PMC4618928 DOI: 10.1371/journal.pone.0140783] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Accepted: 09/30/2015] [Indexed: 11/19/2022] Open
Abstract
This study reports on a novel method to detect and reduce the contribution of movement artifact (MA) in electrocardiogram (ECG) recordings gathered from horses in free movement conditions. We propose a model that integrates cardiovascular and movement information to estimate the MA contribution. Specifically, ECG and physical activity are continuously acquired from seven horses through a wearable system. Such a system employs completely integrated textile electrodes to monitor ECG and is also equipped with a triaxial accelerometer for movement monitoring. In the literature, the most used technique to remove movement artifacts, when noise bandwidth overlaps the primary source bandwidth, is the adaptive filter. In this study we propose a new algorithm, hereinafter called Stationary Wavelet Movement Artifact Reduction (SWMAR), where the Stationary Wavelet Transform (SWT) decomposition algorithm is employed to identify and remove movement artifacts from ECG signals in horses. A comparative analysis with the Normalized Least Mean Square Adaptive Filter technique (NLMSAF) is performed as well. Results achieved on seven hours of recordings showed a reduction greater than 40% of MA percentage (between before- and after- the application of the proposed algorithm). Moreover, the comparative analysis with the NLMSAF, applied to the same ECG recordings, showed a greater reduction of MA percentage in favour of SWMAR with a statistical significant difference (p-value < 0.0.5).
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Affiliation(s)
- Antonio Lanata
- Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
- * E-mail:
| | - Andrea Guidi
- Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
| | - Paolo Baragli
- Department of Veterinary Sciences, University of Pisa, Pisa, Italy
| | - Gaetano Valenza
- Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
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20
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Wang HB, Yen CW, Liang JT, Wang Q, Liu GZ, Song R. A robust electrode configuration for bioimpedance measurement of respiration. JOURNAL OF HEALTHCARE ENGINEERING 2015; 5:313-27. [PMID: 25193370 DOI: 10.1260/2040-2295.5.3.313] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Electrode configuration is an important issue in the continuous measurement of respiration using impedance pneumography (IP). The robust configuration is usually confirmed by comparing the amplitude of the IP signals acquired with different electrode configurations, while the relative change in waveform and the effects of body posture and respiratory pattern are ignored. In this study, the IP signals and respiratory volume are simultaneously acquired from 8 healthy subjects in supine, left lying, right lying and prone postures, and the subjects are asked to perform four respiratory patterns including free breathing, thoracic breathing, abdominal breathing and apnea. The IP signals are acquired with four different chest electrode configurations, and the volume are measured using pneumotachograph (PNT). Differences in correlation and absolute deviation between the IP-derived and PNT-derived respiratory volume are assessed. The influences of noise, respiratory pattern and body posture on the IP signals of different configurations have significant difference (p < 0.05). The robust electrode configuration is found on the axillary midline, which is suitable for long term respiration monitoring.
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Affiliation(s)
- Hong-Bin Wang
- School of Engineering, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Chen-Wen Yen
- Department of Mechanical and Electro-mechanical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan
| | - Jing-Tao Liang
- School of Engineering, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Qian Wang
- School of Engineering, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Guan-Zheng Liu
- School of Engineering, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Rong Song
- School of Engineering, Sun Yat-sen University, Guangzhou, People's Republic of China
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21
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Zheng YL, Ding XR, Poon CCY, Lo BPL, Zhang H, Zhou XL, Yang GZ, Zhao N, Zhang YT. Unobtrusive sensing and wearable devices for health informatics. IEEE Trans Biomed Eng 2015; 61:1538-54. [PMID: 24759283 PMCID: PMC7176476 DOI: 10.1109/tbme.2014.2309951] [Citation(s) in RCA: 247] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The aging population, prevalence of chronic diseases, and outbreaks of infectious diseases are some of the major challenges of our present-day society. To address these unmet healthcare needs, especially for the early prediction and treatment of major diseases, health informatics, which deals with the acquisition, transmission, processing, storage, retrieval, and use of health information, has emerged as an active area of interdisciplinary research. In particular, acquisition of health-related information by unobtrusive sensing and wearable technologies is considered as a cornerstone in health informatics. Sensors can be weaved or integrated into clothing, accessories, and the living environment, such that health information can be acquired seamlessly and pervasively in daily living. Sensors can even be designed as stick-on electronic tattoos or directly printed onto human skin to enable long-term health monitoring. This paper aims to provide an overview of four emerging unobtrusive and wearable technologies, which are essential to the realization of pervasive health information acquisition, including: 1) unobtrusive sensing methods, 2) smart textile technology, 3) flexible-stretchable-printable electronics, and 4) sensor fusion, and then to identify some future directions of research.
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22
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Lanata A, Valenza G, Nardelli M, Gentili C, Scilingo EP. Complexity Index From a Personalized Wearable Monitoring System for Assessing Remission in Mental Health. IEEE J Biomed Health Inform 2015; 19:132-9. [DOI: 10.1109/jbhi.2014.2360711] [Citation(s) in RCA: 111] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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23
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Zhang Z, Silva I, Wu D, Zheng J, Wu H, Wang W. Adaptive motion artefact reduction in respiration and ECG signals for wearable healthcare monitoring systems. Med Biol Eng Comput 2014; 52:1019-30. [PMID: 25273839 DOI: 10.1007/s11517-014-1201-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2013] [Accepted: 09/22/2014] [Indexed: 10/24/2022]
Abstract
Wearable healthcare monitoring systems (WHMSs) have received significant interest from both academia and industry with the advantage of non-intrusive and ambulatory monitoring. The aim of this paper is to investigate the use of an adaptive filter to reduce motion artefact (MA) in physiological signals acquired by WHMSs. In our study, a WHMS is used to acquire ECG, respiration and triaxial accelerometer (ACC) signals during incremental treadmill and cycle ergometry exercises. With these signals, performances of adaptive MA cancellation are evaluated in both respiration and ECG signals. To achieve effective and robust MA cancellation, three axial outputs of the ACC are employed to estimate the MA by a bank of gradient adaptive Laguerre lattice (GALL) filter, and the outputs of the GALL filters are further combined with time-varying weights determined by a Kalman filter. The results show that for the respiratory signals, MA component can be reduced and signal quality can be improved effectively (the power ratio between the MA-corrupted respiratory signal and the adaptive filtered signal was 1.31 in running condition, and the corresponding signal quality was improved from 0.77 to 0.96). Combination of the GALL and Kalman filters can achieve robust MA cancellation without supervised selection of the reference axis from the ACC. For ECG, the MA component can also be reduced by adaptive filtering. The signal quality, however, could not be improved substantially just by the adaptive filter with the ACC outputs as the reference signals.
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Affiliation(s)
- Zhengbo Zhang
- Department of Biomedical Engineering, Chinese PLA (People's Liberation Army) General Hospital, Beijing, China
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24
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Betella A, Zucca R, Cetnarski R, Greco A, Lanatà A, Mazzei D, Tognetti A, Arsiwalla XD, Omedas P, De Rossi D, Verschure PFMJ. Inference of human affective states from psychophysiological measurements extracted under ecologically valid conditions. Front Neurosci 2014; 8:286. [PMID: 25309310 PMCID: PMC4173664 DOI: 10.3389/fnins.2014.00286] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Accepted: 08/22/2014] [Indexed: 11/24/2022] Open
Abstract
Compared to standard laboratory protocols, the measurement of psychophysiological signals in real world experiments poses technical and methodological challenges due to external factors that cannot be directly controlled. To address this problem, we propose a hybrid approach based on an immersive and human accessible space called the eXperience Induction Machine (XIM), that incorporates the advantages of a laboratory within a life-like setting. The XIM integrates unobtrusive wearable sensors for the acquisition of psychophysiological signals suitable for ambulatory emotion research. In this paper, we present results from two different studies conducted to validate the XIM as a general-purpose sensing infrastructure for the study of human affective states under ecologically valid conditions. In the first investigation, we recorded and classified signals from subjects exposed to pictorial stimuli corresponding to a range of arousal levels, while they were free to walk and gesticulate. In the second study, we designed an experiment that follows the classical conditioning paradigm, a well-known procedure in the behavioral sciences, with the additional feature that participants were free to move in the physical space, as opposed to similar studies measuring physiological signals in constrained laboratory settings. Our results indicate that, by using our sensing infrastructure, it is indeed possible to infer human event-elicited affective states through measurements of psychophysiological signals under ecological conditions.
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Affiliation(s)
- Alberto Betella
- Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra Barcelona, Spain
| | - Riccardo Zucca
- Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra Barcelona, Spain
| | - Ryszard Cetnarski
- Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra Barcelona, Spain
| | - Alberto Greco
- Research Centre "E. Piaggio", University of Pisa Pisa, Italy ; Information Engineering Department, University of Pisa Pisa, Italy
| | - Antonio Lanatà
- Research Centre "E. Piaggio", University of Pisa Pisa, Italy ; Information Engineering Department, University of Pisa Pisa, Italy
| | - Daniele Mazzei
- Research Centre "E. Piaggio", University of Pisa Pisa, Italy
| | - Alessandro Tognetti
- Research Centre "E. Piaggio", University of Pisa Pisa, Italy ; Information Engineering Department, University of Pisa Pisa, Italy
| | - Xerxes D Arsiwalla
- Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra Barcelona, Spain
| | - Pedro Omedas
- Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra Barcelona, Spain
| | - Danilo De Rossi
- Research Centre "E. Piaggio", University of Pisa Pisa, Italy ; Information Engineering Department, University of Pisa Pisa, Italy
| | - Paul F M J Verschure
- Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Universitat Pompeu Fabra Barcelona, Spain ; ICREA, Institució Catalana de Recerca i Estudis Avançats Barcelona, Spain
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25
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Valenza G, Nardelli M, Lanata A, Gentili C, Bertschy G, Paradiso R, Scilingo EP. Wearable Monitoring for Mood Recognition in Bipolar Disorder Based on History-Dependent Long-Term Heart Rate Variability Analysis. IEEE J Biomed Health Inform 2014; 18:1625-35. [DOI: 10.1109/jbhi.2013.2290382] [Citation(s) in RCA: 109] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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26
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Fontecave-Jallon J, Videlier B, Baconnier P, Tanguy S, Calabrese P, Guméry PY. Detecting variations of blood volume shift due to heart beat from respiratory inductive plethysmography measurements in man. Physiol Meas 2013; 34:1085-101. [PMID: 23954865 DOI: 10.1088/0967-3334/34/9/1085] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The simultaneous study of the cardiac and respiratory activities and their interactions is of great physiological and clinical interest. For this purpose, we want to investigate if respiratory inductive plethysmography (RIP) can be used for cardiac functional exploration. We propose a system, based on RIP technology and time-scale approaches of signal processing, for the extraction of cardiac information. This study focuses on the monitoring of blood volume shift due to heart beat, noted ▵Vtr_c and investigates RIP for the detection of ▵Vtr_c variations by comparison to stroke volume (SV) variations estimated by impedance cardiography (IMP). We proposed a specific respiratory protocol assumed to induce significant variations of the SV. Fifteen healthy volunteers in the seated and supine positions were asked to alternate rest respiration and maneuvers, consisting in blowing into a manometer. A multi-step treatment including a variant of empirical mode decomposition was applied on RIP signals to extract cardiac volume signals and estimate beat-to-beat ▵Vtr_c. These were averaged in quasi-stationary states at rest and during the respiratory maneuvers, and analysed in view of SV estimations from IMP signals simultaneously acquired. Correlation and statistical tests over the data show that RIP can be used to detect variations of the cardiac blood shift in healthy young subjects.
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Affiliation(s)
- J Fontecave-Jallon
- University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France.
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27
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Valenza G, Lanatá A, Scilingo EP. Improving emotion recognition systems by embedding cardiorespiratory coupling. Physiol Meas 2013; 34:449-64. [PMID: 23524596 DOI: 10.1088/0967-3334/34/4/449] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This work aims at showing improved performances of an emotion recognition system embedding information gathered from cardiorespiratory (CR) coupling. Here, we propose a novel methodology able to robustly identify up to 25 regions of a two-dimensional space model, namely the well-known circumplex model of affect (CMA). The novelty of embedding CR coupling information in an autonomic nervous system-based feature space better reveals the sympathetic activations upon emotional stimuli. A CR synchrogram analysis was used to quantify such a coupling in terms of number of heartbeats per respiratory period. Physiological data were gathered from 35 healthy subjects emotionally elicited by means of affective pictures of the international affective picture system database. In this study, we finely detected five levels of arousal and five levels of valence as well as the neutral state, whose combinations were used for identifying 25 different affective states in the CMA plane. We show that the inclusion of the bivariate CR measures in a previously developed system based only on monovariate measures of heart rate variability, respiration dynamics and electrodermal response dramatically increases the recognition accuracy of a quadratic discriminant classifier, obtaining more than 90% of correct classification per class. Finally, we propose a comprehensive description of the CR coupling during sympathetic elicitation adapting an existing theoretical nonlinear model with external driving. The theoretical idea behind this model is that the CR system is comprised of weakly coupled self-sustained oscillators that, when exposed to an external perturbation (i.e. sympathetic activity), becomes synchronized and less sensible to input variations. Given the demonstrated role of the CR coupling, this model can constitute a general tool which is easily embedded in other model-based emotion recognition systems.
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Affiliation(s)
- Gaetano Valenza
- Department of Information Engineering and Research Center E. Piaggio, Faculty of Engineering, University of Pisa, Via G Caruso 16, I-56122 Pisa, Italy.
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28
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Fontecave-Jallon J, Guméry PY, Calabrese P, Briot R, Baconnier P. A Wearable Technology Revisited for Cardio-Respiratory Functional Exploration. INTERNATIONAL JOURNAL OF E-HEALTH AND MEDICAL COMMUNICATIONS 2013. [DOI: 10.4018/jehmc.2013010102] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The objective of the present study is to extract new information from complex signals generated by Respiratory Inductive Plethysmography (RIP). This indirect cardio-respiratory (CR) measure is a well-known wearable solution. The authors applied time-scale analysis to estimate cardiac activity from thoracic volume variations, witnesses of CR interactions. Calibrated RIP signals gathered from 4 healthy volunteers in resting conditions are processed by Ensemble Empirical Mode Decomposition to extract cardiac volume signals and estimate stroke volumes. Averaged values of these stroke volumes (SVRIP) are compared with averaged values of stroke volumes determined simultaneously by electrical impedance cardiography (SVICG). There is a satisfactory correlation between SVRIP and SVICG (r=0.76, p<0.001) and the limits of agreement between the 2 types of measurements (±23%) satisfies the required criterion (±30%). The observed under-estimation (-58%) is argued. This validates the use of RIP for following stroke volume variations and suggests that one simple transducer can provide a quantitative exploration of both ventilatory and cardiac volumes.
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Affiliation(s)
- Julie Fontecave-Jallon
- University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
| | - Pierre-Yves Guméry
- University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
| | - Pascale Calabrese
- University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
| | - Raphaël Briot
- University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
| | - Pierre Baconnier
- University Joseph Fourier-Grenoble 1, CNRS, TIMC-IMAG Laboratory CNRS UMR 5525, PRETA team, Grenoble, F-38041, France
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29
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Lee SJ, Motai Y, Weiss E, Sun SS. Irregular breathing classification from multiple patient datasets using neural networks. ACTA ACUST UNITED AC 2012; 16:1253-64. [PMID: 22922728 DOI: 10.1109/titb.2012.2214395] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Complicated breathing behaviors including uncertain and irregular patterns can affect the accuracy of predicting respiratory motion for precise radiation dose delivery [3-6, 25, 36]. So far investigations on irregular breathing patterns have been limited to respiratory monitoring of only extreme inspiration and expiration [37]. Using breathing traces acquired on a Cyberknife treatment facility, we retrospectively categorized breathing data into several classes based on the extracted feature metrics derived from breathing data of multiple patients. The novelty of this paper is that the classifier using neural networks can provide clinical merit for the statistical quantitative modeling of irregular breathing motion based on a regular ratio representing how many regular/irregular patterns exist within an observation period. We propose a new approach to detect irregular breathing patterns using neural networks, where the reconstruction error can be used to build the distribution model for each breathing class. The proposed irregular breathing classification used a regular ratio to decide whether or not the current breathing patterns were regular. The sensitivity, specificity, and receiver operating characteristic (ROC) curve of the proposed irregular breathing pattern detector was analyzed. The experimental results of 448 patients breathing patterns validated the proposed irregular breathing classifier.
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30
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Valenza G, Lanatà A, Scilingo EP. Oscillations of heart rate and respiration synchronize during affective visual stimulation. ACTA ACUST UNITED AC 2012; 16:683-90. [PMID: 22575693 DOI: 10.1109/titb.2012.2197632] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The objective of this study is to investigate the synchronization between breathing patterns and heart rate during emotional visual elicitation, that is, using sets of images gathered from the international affective picture system having five levels of arousal and five levels of valence, including a neutral reference level. Thirty-five healthy volunteers were emotionally elicited in agreement with a bidimensional spatial localization of affective states, i.e., arousal/valence plane, while two peripheral physiological signals, ECG and Respiration activity, were acquired simultaneously. The synchronization was then quantified by applying the concept of phase synchronization of chaotic oscillators, i.e., the cardio-respiratory synchrogram. This technique allowed us to estimate the synchronization ratio m:n as the attendance of n heartbeats in each m respiratory cycle, even for noisy and nonstationary data. We found a stronger evidence of cardiorespiratory synchronization during arousal than during neutral states.
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Affiliation(s)
- Gaetano Valenza
- Department of Information Engineering and Interdepartmental Research Center E. Piaggio, University of Pisa, Pisa, Italy.
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Patel S, Park H, Bonato P, Chan L, Rodgers M. A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabil 2012; 9:21. [PMID: 22520559 PMCID: PMC3354997 DOI: 10.1186/1743-0003-9-21] [Citation(s) in RCA: 661] [Impact Index Per Article: 55.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2011] [Accepted: 04/20/2012] [Indexed: 12/15/2022] Open
Abstract
The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.
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Affiliation(s)
- Shyamal Patel
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Boston, MA, USA
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| | - Hyung Park
- Rehabilitation Medicine Department Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Paolo Bonato
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Leighton Chan
- Rehabilitation Medicine Department Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Mary Rodgers
- Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine, Baltimore, MD, USA
- National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
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Curone D, Secco EL, Caldani L, Lanatà A, Paradiso R, Tognetti A, Magenes G. Assessment of sensing fire fighters uniforms for physiological parameter measurement in harsh environment. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE : A PUBLICATION OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY 2012; 16:501-11. [PMID: 22231710 DOI: 10.1109/titb.2011.2182615] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
In the last few years, much effort has been devoted to the development of wearable sensing systems able to monitor physiological, behavioral, and environmental parameters. Less has been done on the accurate testing and assessment of this instrumentation, especially when considering devices thought to be used in harsh environments by subjects or operators performing intense physical activities. This paper presents methodology and results of the evaluation of wearable physiological sensors under these conditions. The methodology has been applied to a specific textile-based prototype, aimed at the real-time monitoring of rescuers in emergency contexts, which has been developed within a European funded project called ProeTEX. Wearable sensor measurements have been compared with the ones of suitable gold standards through Bland-Altman statistical analysis; tests were realized in controlled environments simulating typical intervention conditions, with temperatures ranging from 20 °C to 45 °C and subjects performing mild to very intense activities. This evaluation methodology demonstrated to be effective for the definition of the limits of use of wearable sensors. Furthermore, the ProeTEX prototype demonstrated to be reliable, since it produced negligible errors when used for up to 1 h in normal environmental temperature (20 °C and 35 °C) and up to 30 min in harsher environment (45 °C).
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Affiliation(s)
- Davide Curone
- European Centre for Training and Research in Earthquake Engineering, Pavia, Italy.
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Videlier B, Fontecave-Jallon J, Calabrese P, Baconnier P, Gumery PY. Empirical mode decomposition of respiratory inductive plethysmographic signals for stroke volume variations monitoring: respiratory protocol and comparison with impedance cardiography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2012; 2012:2607-2610. [PMID: 23366459 DOI: 10.1109/embc.2012.6346498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
We investigate Respiratory Inductive Plethysmography (RIP) to estimate cardiac activity from thoracic volume variations and study cardio-respiratory interactions. The objective of the present study is to evaluate the ability of RIP to monitor stroke volume (SV) variations, with reference to impedance cardiography (IMP). Five healthy volunteers in seated and supine positions were asked to blow into a manometer in order to induce significant SV decreases. Time-scale analysis was applied on calibrated RIP signals to extract cardiac volume signals. Averaged SV values, in quasi-stationary states at rest and during the respiratory maneuvers, were then estimated from these cardiac signals and from IMP signals simultaneously acquired. SV variations between rest and maneuvers were finally evaluated for both techniques. We show that SV values as well as SV variations are correlated between RIP and IMP estimations, suggesting that RIP could be used for SV variations monitoring.
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Affiliation(s)
- Benjamin Videlier
- UJF-Grenoble 1, CNRS, TIMC-IMAG UMR 5525, PRETA Team, Grenoble, F-38041, France
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Zito D, Pepe D, Mincica M, Zito F, Tognetti A, Lanata A, De Rossi D. SoC CMOS UWB Pulse Radar Sensor for Contactless Respiratory Rate Monitoring. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2011; 5:503-510. [PMID: 23852548 DOI: 10.1109/tbcas.2011.2176937] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
An ultra wideband (UWB) system-on-chip radar sensor for respiratory rate monitoring has been realized in 90 nm CMOS technology and characterized experimentally. The radar testchip has been applied to the contactless detection of the respiration activity of adult and baby. The field operational tests demonstrate that the UWB radar sensor detects the respiratory rate of person under test (adult and baby) associated with sub-centimeter chest movements, allowing the continuous-time non-invasive monitoring of hospital patients and other people at risk of obstructive apneas such as babies in cot beds, or other respiratory diseases.
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Maglaveras N, Bonato P, Tamura T. Guest editorial. Special section on personal health systems. ACTA ACUST UNITED AC 2010; 14:360-3. [PMID: 20684048 DOI: 10.1109/titb.2010.2044110] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
This special section on personal health systems (PHSs) features 13 papers in three main areas: new-micro-nano instrumentation, sensors, and sensor-based systems; new information processing technology via embedding intelligence in PHS; and PHS platforms to address specific clinical applications.
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