Unobtrusive and Continuous BCG-Based Human Identification Using a Microbend Fiber Sensor

Zhang, Yi; Chen, Zhihao; Chen, Weijuan; Li, Hui

doi:10.1109/access.2019.2919407

Cited by 15 publications

(9 citation statements)

References 25 publications

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“…By using the USS, HR and BR were monitored. In addition, BCG signals and blood pressure were also monitored [ 84 ]. In this review, 12 studies were identified that monitored only physiological states, whereas some studies monitored behaviors from physiological states, such as vital signs to monitor cognitive load, emotional state, and sleeping behavior [ 60 , 65 , 80 , 85 ].…”

Section: Resultsmentioning

confidence: 99%

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Implementation of Unobtrusive Sensing Systems for Older Adult Care: Scoping Review

Sharma¹,

Brinke²,

Gemert-Pijnen³

et al. 2021

JMIR Aging

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Background The continuous growth of the older adult population will have implications for the organization of health and social care. Potentially, in-home monitoring unobtrusive sensing systems (USSs) can be used to support formal or informal caregivers of older adults, as they can monitor deviant physical and physiological behavior changes. Most existing USSs are not specific to older adult care. Hence, to facilitate the implementation of existing USSs in older adult care, it is important to know which USSs would be more suitable for older adults. Objective This scoping review aims to examine the literature to identify current USSs for monitoring human activities and behaviors and assess their implementation readiness for older adult care. Methods We conducted a structured search in the Scopus, Web of Science, and ACM Digital Library databases. Predefined inclusion criteria included studies on unobtrusive sensor-based technology; experimental in nature; aimed at monitoring human social, emotional, physical, and physiological behavior; having the potential to be scalable in in-home care; and having at least 5 adults as participants. Using these criteria, we screened studies by title, abstract, and full text. A deductive thematic analysis based on the Proctor implementation framework along with an additional outcome of external validity was applied to the included studies to identify the factors contributing to successful implementation. Finally, the identified factors were used to report the implementation readiness of the included studies for older adult care. Results In this review, 52 studies were included. Deductive analysis using the implementation framework by Proctor resulted in six factors that can contribute to the successful implementation of USSs in older adult care: study settings, age of participants, activities monitored, sensor setup, sensing technology used, and usefulness of USSs. These factors were associated with the implementation outcomes as follows: study settings and age of participants contributed to external validity, sensor setup contributed to acceptability, usefulness of USSs contributed to adoption, activities monitored contributed to appropriateness, and sensing technology used contributed to implementation cost. Furthermore, the implementation assessment of the included 52 studies showed that none of the studies addressed all the identified factors. This assessment was useful in highlighting studies that have addressed multiple factors; thus, these studies represent a step ahead in the implementation process. Conclusions This review is the first to scope state-of-the-art USSs suitable for older adult care. Although the included 52 USS studies fulfilled the basic criteria to be suitable for older adult care, systems leveraging radio frequency technology in a no-contact sensor setup for monitoring life risk or health wellness activities are more suitable for older adult care. Finally, this review has extended the discussion about unobtrusiveness as a property of systems that cannot be measured in binary because it varies greatly with user perception and context.

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Section: Resultsmentioning

confidence: 99%

“…Biomedical sensors require contact with the user, as they measure biological and/or chemical processes in the human body (eg, electrocardiogram and ballistocardiograph [ 84 ]). Contact is often achieved by including them in objects that participants hold close to themselves, for example, a blanket [ 73 ], pillow, or mattress [ 63 ].…”

Section: Resultsmentioning

confidence: 99%

Implementation of Unobtrusive Sensing Systems for Older Adult Care: Scoping Review

Sharma¹,

Brinke²,

Gemert-Pijnen³

et al. 2021

JMIR Aging

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“…As such, it is suitable for use in highly controlled environments such as nuclear or chemical plants [7]. Currently, optical fiberbased sensors are used to monitor various physical and chemical properties such as humidity [8], microbends [9], [10], electric field [11], [12], temperature [13], [14], pressure [ 15], magnetic field [16], gas [17], [18], corrosion [19]- [21] among others.…”

Section: Corrosion Sensor Using Metallic Doublementioning

confidence: 99%

Corrosion Sensor Using Metallic Double Layer in Optical Fiber

Oliveira

Silva

Alves

et al. 2021

J. Microw. Optoelectron. Electromagn. Appl.

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In this paper, a new optical fiber corrosion sensor based on metallic bilayers is described. The detection region is located at a fiber end facet and we present simulations as well as experimental results in controlled lab conditions for Ti(10 nm)/Al(10 nm) and Ni(5 nm)/Al(5 nm) bilayers. We perform the characterization of the device by numerical simulations using the COMSOL Multiphysics software, and with an analytical model, which makes use of the Fresnel equations. According to the simulations, the change in the reflected optical signal over time is related to variations in the thickness of the metallic films by the corrosive process and, consequently, the corrosion rate in each metal of the bilayer can be obtained. Upon the simulation results, sensor devices were fabricated by depositing thin metallic films on the cleaved facet of the optical fiber using the sputtering method. We show that the use of a metallic bilayer as a transducer, instead of a monolayer, improves the sensor measuring interval (20 ± 1 nm) and provides information about the corrosion rate along the corrosion process.

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“…With the advantage of universality, uniqueness, permanence and robustness, biometric technologies are rapidly evolving and spreading throughout our daily life [1,2], in which ECG biometric recognition has attracted increasing research interest, just like continuous recognition systems [3]. [4][5][6] utilized all detected fiducials of each heartbeat to determine individual.…”

Section: Introductionmentioning

confidence: 99%

Label-Guided Dictionary Pair Learning for ECG Biometric Recognition

Yang

Wang

et al. 2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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ECG biometric recognition has received plenty of attention in biometrics area. In recent years, various classical sparse representation and dictionary learning methods have been utilized in ECG biometric recognition. However, to produce better classification results, l P -norm is used to regularize the representation coefficients, which undoubtedly brings time cost problem. To overcome this limitation, our method, namely label-guided dictionary pair learning, aims to learn a projective dictionary and reconstructed dictionary jointly, which achieves signal representation and reconstruction simultaneously. Introduction of label information with each dictionary item and Fisher-like regularization on projective dictionary enforce discriminability during the dictionary learning process. Alternating direction method of multipliers is then exploited to optimize the corresponding objective function. Extensive experiments on two databases demonstrate that our method can achieve better performance compared with stateof-the-art ECG biometric recognition methods.

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Unobtrusive and Continuous BCG-Based Human Identification Using a Microbend Fiber Sensor

Cited by 15 publications

References 25 publications

Implementation of Unobtrusive Sensing Systems for Older Adult Care: Scoping Review

Implementation of Unobtrusive Sensing Systems for Older Adult Care: Scoping Review

Corrosion Sensor Using Metallic Double Layer in Optical Fiber

Label-Guided Dictionary Pair Learning for ECG Biometric Recognition

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