Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Heart rate (HR) observation by using photoplethysmography (PPG) signals during intense physical activity is a crucial task because of the fact that PPG signals are affected by the noise due to movement artifacts by the user’s hand movements. This paper addresses the discriminating assessment of a novel encapsulation for wearable PPG sensor during the severe physical activity. In this work, we plan the HR estimation issue, and utilization of proposed algorithm to find high-determination power spectra of PPG signals, from which heart rates are evaluated by selecting and comparing the peaks. The proposed system was applied on PPG recordings obtained from 10 subjects who were quick runners at the top velocity of 15km/hour on a treadmill. Utilizing correlation and HR investigation with the assistance of peak detection, we assessed the simulation of the proposed framework against the existing works. The outcome demonstrated that the average absolute estimation error achieved using proposed method is lesser contrasted with ground truth heart rates obtained at the same time through the recording of electrocardiogram (ECG).
Jayadevappa B.M. 2015. \u201cAn Estimation Technique using FFT for Heart Rate Derived from PPG Signal\u201d. Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 15 (GJRE Volume 15 Issue F7): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: India
Subject: Global Journal of Research in Engineering - F: Electrical & Electronic
Authors: Jayadevappa B.M, Mallikarjun S. Holi (PhD/Dr. count: 0)
View Count (all-time): 210
Total Views (Real + Logic): 4042
Total Downloads (simulated): 2023
Publish Date: 2015 10, Sat
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Heart rate (HR) observation by using photoplethysmography (PPG) signals during intense physical activity is a crucial task because of the fact that PPG signals are affected by the noise due to movement artifacts by the user’s hand movements. This paper addresses the discriminating assessment of a novel encapsulation for wearable PPG sensor during the severe physical activity. In this work, we plan the HR estimation issue, and utilization of proposed algorithm to find high-determination power spectra of PPG signals, from which heart rates are evaluated by selecting and comparing the peaks. The proposed system was applied on PPG recordings obtained from 10 subjects who were quick runners at the top velocity of 15km/hour on a treadmill. Utilizing correlation and HR investigation with the assistance of peak detection, we assessed the simulation of the proposed framework against the existing works. The outcome demonstrated that the average absolute estimation error achieved using proposed method is lesser contrasted with ground truth heart rates obtained at the same time through the recording of electrocardiogram (ECG).
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