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Zhang B, Dong L, Kong L, Liu M, Zhao Y, Hui M, Chu X. Prediction of Impulsive Aggression Based on Video Images. Bioengineering (Basel) 2023; 10:942. [PMID: 37627827 PMCID: PMC10451168 DOI: 10.3390/bioengineering10080942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 08/27/2023] Open
Abstract
In response to the subjectivity, low accuracy, and high concealment of existing attack behavior prediction methods, a video-based impulsive aggression prediction method that integrates physiological parameters and facial expression information is proposed. This method uses imaging equipment to capture video and facial expression information containing the subject's face and uses imaging photoplethysmography (IPPG) technology to obtain the subject's heart rate variability parameters. Meanwhile, the ResNet-34 expression recognition model was constructed to obtain the subject's facial expression information. Based on the random forest classification model, the physiological parameters and facial expression information obtained are used to predict individual impulsive aggression. Finally, an impulsive aggression induction experiment was designed to verify the method. The experimental results show that the accuracy of this method for predicting the presence or absence of impulsive aggression was 89.39%. This method proves the feasibility of applying physiological parameters and facial expression information to predict impulsive aggression. This article has important theoretical and practical value for exploring new impulsive aggression prediction methods. It also has significance in safety monitoring in special and public places such as prisons and rehabilitation centers.
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Affiliation(s)
- Borui Zhang
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China
| | - Liquan Dong
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China
| | - Lingqin Kong
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China
| | - Ming Liu
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China
| | - Yuejin Zhao
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China
| | - Mei Hui
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China
| | - Xuhong Chu
- School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
- Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, Beijing 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China
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Shukla P, Akanbi O, Atuah AS, Aljaedi A, Bouye M, Sharma S. Cryptography-Based Medical Signal Securing Using Improved Variation Mode Decomposition with Machine Learning Techniques. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:7307552. [PMID: 36131899 PMCID: PMC9484937 DOI: 10.1155/2022/7307552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/16/2022] [Accepted: 07/21/2022] [Indexed: 11/20/2022]
Abstract
There is no question about the value that digital signal processing brings to the area of biomedical research. DSP processors are used to sample and process the analog inputs that are received from a human organ. These inputs come from the organ itself. DSP processors, because of their multidimensional data processing nature, are the electrical components that take up the greatest space and use the most power. In this age of digital technology and electronic gizmos, portable biomedical devices represent an essential step forward in technological advancement. Electrocardiogram (ECG) units are among the most common types of biomedical equipment, and their functions are absolutely necessary to the process of saving human life. In the latter part of the 1990s, portable electrocardiogram (ECG) devices began to appear on the market, and research into their signal processing and electronics design capabilities continues today. System-on-chip (SoC) design refers to the process through which the separate computing components of a DSP unit are combined onto a single chip in order to achieve greater power and space efficiency. In the design of biomedical DSP devices, this body of research presents a number of different solutions for reducing power consumption and space requirements. Using serial or parallel data buses, which are often the region that consumes the most power, it is possible to send data between the system-on-chip (SoC) and other components. To cut down on the number of needless switching operations that take place during data transmission, a hybrid solution that makes use of the shift invert bus encoding scheme has been developed. Using a phase-encoded shift invert bus encoding approach, which embeds the two-bit indication lines into a single-bit encoded line, is one way to solve the issue of having two distinct indicator bits. This method reduces the problem. The PESHINV approach is compared to the SHINV method that already exists, and the comparison reveals that the suggested PESHINV method reduces the total power consumption of the encoding circuit by around 30 percent. The computing unit of the DSP processor is the target of further optimization efforts. Virtually, all signal processing methods need memory and multiplier circuits to function properly.
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Affiliation(s)
| | - Oluwatobi Akanbi
- Computer Science Department, University of Colorado, Colorado Springs, CO 80918, USA
| | - Asakipaam Simon Atuah
- Department of Telecommunication Engineering, KNUST (Kwame Nkrumah University of Science and Technology), Ghana
| | - Amer Aljaedi
- College of Computing and Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia
| | - Mohamed Bouye
- Department of Mathematics, College of Science, King Khalid University, Abha, Saudi Arabia
| | - Shakti Sharma
- School of Computer Science Engineering & Technology, Bennett University, India
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Ding X, Wang W, Chen Y, Yang Y, Zhao Y, Kong D. Feasibility Study of Pulse Width at Half Amplitude of Camera PPG for Contactless Blood Pressure Estimation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:365-368. [PMID: 34891310 DOI: 10.1109/embc46164.2021.9630964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Non-contact blood pressure (BP) estimation with imaging photoplethysmogram (PPG) that can be acquired by camera is a promising alternative to cuff-based technology because of its nature of pervasive, low-cost, and being continuous. Most of the non-contact BP estimation methods are based on the principle of pulse transit time (PTT) as being used for wearable cuffless BP measurement. However, PTT-based method on the one hand requires simultaneous capture of images of multiple skin sites with the sites being at a distance from each other; and on the other hand, it can only partially reflect BP changes according to previous studies. In this paper, we propose to use a different camera PPG feature that has not yet been fully studied - pulse width at half amplitude (PWHA) for the evaluation of BP in a non-contact way. PWHA can be obtained from a single-site camera PPG, and it can indicate BP changes. The relationship of PWHA and BP was analyzed on 16 healthy subjects with BP changes induced by deep breathing and stepping exercise. The results showed that beat-to-beat PWHA can well track dynamic BP changes, and it is inversely related to BP across the sampled population and within each individual with about 80% individuals having high correlations. The findings suggest that PWHA can reflect the dynamic changes in cardiovascular characteristics and thereby BP changes, demonstrating the feasibility of imaging PWHA for non-contact BP estimation beyond the PTT method.Clinical Relevance- This provides a potential new method for non-contact BP, which allows BP monitoring at home, clinical setting, and public places in a pervasive manner. It reduces contacts between persons during a pandemic and offers an ever-present way to monitor BP.
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