| 51. |
- Rahman, Hamidur, et al.
(författare)
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Non-contact heart rate monitoring using lab color space
- 2016
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Ingår i: Studies in Health Technology and Informatics. - 9781614996521 ; , s. 46-53
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Konferensbidrag (refereegranskat)abstract
- Research progressing during the last decade focuses more on non-contact based systems to monitor Heart Rate (HR) which are simple, low-cost and comfortable to use. Most of the non-contact based systems are using RGB videos which is suitable for lab environment. However, it needs to progress considerably before they can be applied in real life applications. As luminance (light) has significance contribution on RGB videos HR monitoring using RGB videos are not efficient enough in real life applications in outdoor environment. This paper presents a HR monitoring method using Lab color facial video captured by a webcam of a laptop computer. Lab color space is device independent and HR can be extracted through facial skin color variation caused by blood circulation considering variable environmental light. Here, three different signal processing methods i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA) have been applied on the color channels in video recordings and blood volume pulse (BVP) has been extracted from the facial regions. In this study, HR is subsequently quantified and compare with a reference measurement. The result shows that high degrees of accuracy have been achieved compared to the reference measurements. Thus, this technology has significant potential for advancing personal health care, telemedicine and many real life applications such as driver monitoring.
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| 52. |
- Rahman, Hamidur, et al.
(författare)
-
Non-Contact Physiological Parameters Extraction Using Camera
- 2016
-
Ingår i: Internet of Things. IoT Infrastructures. - Cham : Springer International Publishing. - 9783319470627 ; , s. 448-453
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Konferensbidrag (refereegranskat)abstract
- Physiological parameters such as Heart Rate (HR), Beat-to-Beat Interval (IBI) and Respiration Rate (RR) are vital indicators of people’s physiological state and important to monitor. However, most of the measurements methods are connection based, i.e. sensors are connected to the body which is often complicated and requires personal assistance. This paper proposed a simple, low-cost and non-contact approach for measuring multiple physiological parameters using a web camera in real time. Here, the heart rate and respiration rate are obtained through facial skin colour variation caused by body blood circulation. Three different signal processing methods such as Fast Fourier Transform (FFT), independent component analysis (ICA) and Principal component analysis (PCA) have been applied on the colour channels in video recordings and the blood volume pulse (BVP) is extracted from the facial regions. HR, IBI and RR are subsequently quantified and compared to corresponding reference measurements. High degrees of agreement are achieved between the measurements across all physiological parameters. This technology has significant potential for advancing personal health care and telemedicine.
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| 53. |
- Rahman, Hamidur, et al.
(författare)
-
Real Time Heart Rate Monitoring from Facial RGB Color Video using Webcam
- 2016
-
Ingår i: The 29th Annual Workshop of the Swedish Artificial Intelligence Society SAIS 2016. - Malmö, Sweden.
-
Konferensbidrag (refereegranskat)abstract
- Heart Rate (HR) is one of the most important Physiological parameter and a vital indicator of people’s physiological state and is therefore important to monitor. Monitoring of HR often involves high costs and complex application of sensors and sensor systems. Research progressing during last decade focuses more on noncontact based systems which are simple, low-cost and comfortable to use. Still most of the noncontact based systems are fit for lab environments in offline situation but needs to progress considerably before they can be applied in real time applications. This paper presents a real time HR monitoring method using a webcam of a laptop computer. The heart rate is obtained through facial skin color variation caused by blood circulation. Three different signal processing methods such as Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA) have been applied on the color channels in video recordings and the blood volume pulse (BVP) is extracted from the facial regions. HR is subsequently quantified and compared to corresponding reference measurements. The obtained results show that there is a high degrees of agreement between the proposed experiments and reference measurements. This technology has significant potential for advancing personal health care and telemedicine. Further improvements of the proposed algorithm considering environmental illumination and movement can be very useful in many real time applications such as driver monitoring.
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| 54. |
- Rahman, Hamidur, et al.
(författare)
-
SmartMirror : An Embedded Non-contact System for Health Monitoring at Home
- 2016
-
Konferensbidrag (refereegranskat)abstract
- The ‘Smart Mirror’ project introduces non-contact based technological innovations at our homes where its usage can be as ubiquitous as ‘looking at a mirror’ while providing critical actionable insights thereby leading to improved care and outcomes. The key objectives is to detect key physiological markers like Heart Rate (HR), Respiration Rate (RR), Inter-beat-interval (IBI) and Blood Pressure (BP) and also drowsiness using the video input of the individual standing in front of the mirror and display the results in real-time. A satisfactory level of accuracy has been attained with respect to the reference sensors signal.
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| 55. |
- Rahman, Hamidur, et al.
(författare)
-
Vision-Based Remote Heart Rate Variability Monitoring using Camera
- 2018
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Ingår i: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225. - Cham : Springer International Publishing. - 9783319762128 ; , s. 10-18
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Konferensbidrag (refereegranskat)abstract
- Heart Rate Variability (HRV) is one of the important physiological parameter which is used to early detect many fatal disease. In this paper a non-contact remote Heart Rate Variability (HRV) monitoring system is developed using the facial video based on color variation of facial skin caused by cardiac pulse. The lab color space of the facial video is used to extract color values of skin and signal processing algorithms i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA), Principle Component Analysis (PCA) are applied to monitor HRV. First, R peak is detected from the color variation of skin and then Inter-Beat-Interval (IBI) is calculated for every consecutive R-R peak. HRV features are then calculated based on IBI both in time and frequency domain. MySQL and PHP programming language is used to store, monitor and display HRV parameters remotely. In this study, HRV is quantified and compared with a reference measurement where a high degree of similarities is achieved. This technology has significant potential for advancing personal health care especially for telemedicine.
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| 56. |
- Tsiftes, Nicolas, et al.
(författare)
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The E-Care@Home Infrastructure for IoT-Enabled Healthcare
- 2016. - 8
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Ingår i: Internet of Things Technologies for HealthCare. - Cham : Springer. - 9783319512334 - 9783319512341 ; , s. 138-140
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Konferensbidrag (refereegranskat)abstract
- The E-Care@Home Project aims at providing a comprehensive IoT-based healthcare system, including state-of-the-art communication protocols and high-level analysis of data from various types of sensors. With this poster, we present its novel technical infrastructure, consisting of low-power IPv6 networking, sensors for health monitoring, and resource-efficient software, that is used to gather data from elderly patients and their surrounding environment.
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