1
|
Chen ST, Ye RJ, Wu TH, Cheng CW, Zhan PY, Chen KM, Zhong WY. Patient Confidential Data Hiding and Transmission System Using Amplitude Quantization in the Frequency Domain of ECG Signals. SENSORS (BASEL, SWITZERLAND) 2023; 23:9199. [PMID: 38005585 PMCID: PMC10675253 DOI: 10.3390/s23229199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/31/2023] [Accepted: 10/31/2023] [Indexed: 11/26/2023]
Abstract
The transform domain provides a useful tool in the field of confidential data hiding and protection. In order to protect and transmit patients' information and competence, this study develops an amplitude quantization system in a transform domain by hiding patients' information in an electrocardiogram (ECG). In this system, we first consider a non-linear model with a hiding state switch to enhance the quality of the hidden ECG signals. Next, we utilize particle swarm optimization (PSO) to solve the non-linear model so as to have a good signal-to-noise ratio (SNR), root mean square error (RMSE), and relative root mean square error (rRMSE). Accordingly, the distortion of the shape in each ECG signal is tiny, while the hidden information can fulfill the needs of physiological diagnostics. The extraction of hidden information is reversely similar to a hiding procedure without primary ECG signals. Preliminary outcomes confirm the effectiveness of our proposed method, especially an Amplitude Similarity of almost 1, an Interval RMSE of almost 0, and SNRs all above 30.
Collapse
Affiliation(s)
- Shuo-Tsung Chen
- Department of Medical Informatics, Chung Shan Medical University, Taichung 40201, Taiwan; (S.-T.C.); (C.-W.C.); (P.-Y.Z.); (K.-M.C.); (W.-Y.Z.)
- Department of Information Center, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
| | - Ren-Jie Ye
- Graduate School of Applied Chinese Studies, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan
| | - Tsung-Hsien Wu
- Bachelor’s Program in Business Management, Fu Jen Catholic University, New Taipei City 242062, Taiwan
| | - Chun-Wen Cheng
- Department of Medical Informatics, Chung Shan Medical University, Taichung 40201, Taiwan; (S.-T.C.); (C.-W.C.); (P.-Y.Z.); (K.-M.C.); (W.-Y.Z.)
| | - Po-You Zhan
- Department of Medical Informatics, Chung Shan Medical University, Taichung 40201, Taiwan; (S.-T.C.); (C.-W.C.); (P.-Y.Z.); (K.-M.C.); (W.-Y.Z.)
| | - Kuan-Ming Chen
- Department of Medical Informatics, Chung Shan Medical University, Taichung 40201, Taiwan; (S.-T.C.); (C.-W.C.); (P.-Y.Z.); (K.-M.C.); (W.-Y.Z.)
| | - Wan-Yu Zhong
- Department of Medical Informatics, Chung Shan Medical University, Taichung 40201, Taiwan; (S.-T.C.); (C.-W.C.); (P.-Y.Z.); (K.-M.C.); (W.-Y.Z.)
| |
Collapse
|
2
|
Hsu CY, Chen CC, Liu CY, Chen ST, Tu SY. Intelligent Healthcare System Using Mathematical Model and Simulated Annealing to Hide Patients Data in the Low-Frequency Amplitude of ECG Signals. SENSORS (BASEL, SWITZERLAND) 2022; 22:8341. [PMID: 36366039 PMCID: PMC9654878 DOI: 10.3390/s22218341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/21/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Healthcare is an important medical topic in recent years. In this study, the novelty we propose is the intelligent healthcare system using an inequality-type optimization mathematical model with signal-to-noise ratio (SNR) and wavelet-domain low-frequency amplitude adjustment techniques to hide patients' confidential data in their electrocardiogram (ECG) signals. The extraction of the hidden patient information also utilizes the low-frequency amplitude adjustment. The detailed steps of establishing the system are as follows. To integrate confidential patient data into ECG signals, we first propose a nonlinear model to optimize the quality of ECG signals with the embedded patients' confidential data including patient name, patient birthdate, date of medical treatment, and medical history. Then, we apply Simulated Annealing (SA) to solve the nonlinear model such that the ECG signals with embedded patients' confidential data have good SNR, good root mean square error (RMSE), and high similarity. In other words, the distortion of the PQRST complexes and the ECG shape caused by the embedded patients' confidential data is very small, and thus the quality of the embedded ECG signals meets the requirements of physiological diagnostics. In the terminals, one can receive the ECG signals with the embedded patients' confidential data. In addition, the embedded patients' confidential data can be received and extracted without the original ECG signals. The experimental results confirm the efficiency that our method maintains a high quality of each ECG signal with the embedded patient confidential data. Moreover, the embedded confidential data shows a good robustness against common attacks.
Collapse
Affiliation(s)
- Chih-Yu Hsu
- School of Transportation, Fujian University of Technology, Fuzhou 350118, China
| | - Chih-Cheng Chen
- Department of Automatic Control Engineering, Feng Chia University, Taichung 40724, Taiwan
- Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan
| | - Chun-You Liu
- Department of Automatic Control Engineering, Feng Chia University, Taichung 40724, Taiwan
- Ph.D. Program of Electrical and Communications Engineering, Feng Chia University, Taichung 40724, Taiwan
| | - Shuo-Tsung Chen
- Department of Applied Mathematics, Tunghai University, Taichung 40704, Taiwan
| | - Shu-Yi Tu
- Department of Mathematics, University of Michigan, Flint, MI 48502, USA
| |
Collapse
|
3
|
Zhao M, Chen ST, Chen TL, Tu SY, Yeh CT, Lin FY, Lu HC. Intelligent Healthcare System Using Patients Confidential Data Communication in Electrocardiogram Signals. Front Aging Neurosci 2022; 14:870844. [PMID: 35527738 PMCID: PMC9069238 DOI: 10.3389/fnagi.2022.870844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 02/28/2022] [Indexed: 11/22/2022] Open
Abstract
With the advent of the aging era, healthcare and elderly care have become the focus of medical care, especially the care of the elderly with dementia. Patients' confidential data hiding is a useful technology for healthcare and patient information privacy. In this study, we implement an intelligent healthcare system using the multiple-coefficient quantization technology in transform domain to hide patients' confidential data into electrocardiogram (ECG) signals obtained by ECG sensor module. In embedding patients' confidential data, we first consider a non-linear model for optimizing the quality of the embedded ECG signals. Next, we apply simulated annealing (SA) to solve the non-linear model so as to have good signal-to-noise ratio (SNR), root mean square error (RMSE), and relative RMSE (rRMSE). Accordingly, the distortion of the PQRST complexes and the ECG amplitude is very small so that the embedded confidential data can satisfy the requirements of physiological diagnostics. In end devices, one can receive the ECG signals with the embedded confidential data and without the original ECG signals. Experimental results confirm the effectiveness of our method, which remains high quality for each ECG signal with the embedded confidential data no matter how the quantization size Q is increased.
Collapse
Affiliation(s)
- Ming Zhao
- School of Computer Science, Yangtze University, Jingzhou, China
| | - Shuo-Tsung Chen
- Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan
| | - Tzu-Li Chen
- Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan
| | - Shu-Yi Tu
- Department of Mathematics, University of Michigan-Flint, Flint, MI, United States
| | - Cheng-Ta Yeh
- Department of Information Management, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Fang-Yu Lin
- Graduate Institute of Business Administration, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Hao-Chun Lu
- Department of Cardiology, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Department of Industrial and Business Management, Chang Gung University, Taoyuan, Taiwan
| |
Collapse
|
4
|
Sharma N, Anand A, Singh AK. Bio-signal data sharing security through watermarking: a technical survey. COMPUTING 2021; 103:1883-1917. [PMCID: PMC7786322 DOI: 10.1007/s00607-020-00881-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 11/23/2020] [Indexed: 06/13/2023]
Abstract
Due to smart healthcare systems highly connected information and communications technologies, sensitive medical information and records are easily transmitted over the networks. However, stealing of healthcare data is increasing crime every day to greatly impact on financial loss. In order to this, researchers are developing various cost-effective bio-signal based data hiding techniques for smart healthcare applications. In this paper, we first introduce various aspects of data hiding along with major properties, generic embedding and extraction process, and recent applications. This survey provides a comprehensive survey on data hiding techniques, and their new trends for solving new challenges in real-world applications. Then, we survey the various notable bio-signal based data hiding techniques. The summary of some notable techniques in terms of their objective, type of data hiding, methodology and database used, performance metrics, important features, and limitations are also presented in tabular form. At the end, we discuss the major issues and research directions to explore the promising areas for future research.
Collapse
Affiliation(s)
- N. Sharma
- Department of CSE, NIT Patna, Patna, Bihar India
| | - A. Anand
- Department of CSE, NIT Patna, Patna, Bihar India
| | - A. K. Singh
- Department of CSE, NIT Patna, Patna, Bihar India
| |
Collapse
|
5
|
Augustyniak P. Differential Watermarking of Multilead ECG Baseline. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:5681-5684. [PMID: 31947142 DOI: 10.1109/embc.2019.8856684] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Digital watermarking has been widely recognized as an effective tool for embedment of auxiliary data in the host record. This paper presents a new method of watermarking using lead-to-lead difference of values in the baseline of the host electrocardiogram. The method starts with delineation of the baseline and uses Kirchoff voltage law or interpolation to predict any selected lead from the remaining ones. Next, the difference between the predicted and actual value is considered as noise and subjects to measurement of level and distribution in the time frame of baseline. The watermark with patient data or results of accompanying measurements is coded accordingly to mimic the noise. Replacement of the baseline noise with the watermark data ends the process. With 12-lead CSE files and respective reference borders of PQ and TP segments, the capacity of watermark achieved 3875 bits per second, while the diagnostic value of the ECG remains untouched.
Collapse
|