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With the increase in point of care services, communication of digital patient records through open network has multi-folded. This digital data is used to obtain the remote medical assistance from the smart healthcare centres. Protecting this data during transmission is a very big challenge. One of the most important medical data is electrocardiogram (ECG) signal which detects the cardiovascular diseases and any alteration in the signal may affect the diagnosis. In this work, an ECG watermarking based on redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD) is developed. First, the ECG signal is converted into 2-D matrix using pan-tompkins algorithm. Then, we use the hybrid of RDWT and SVD to conceal the patient data and logo image into the 2-D ECG image. We also use hybrid of optimization scheme to improve the robustness of the watermark. Preliminary experimental results indicate the optimal invisibility and robustness result is more effective up to 97.89% than the traditional schemes respectively, which makes it suitable for ownership authentication of ECG signal.

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.

The smart healthcare system is an electronic patient records (EPR) sharing system, which significantly helps sharing of EPR data and provides appropriate medical assistance for the patients and a more suitable platform for the potential researchers. However, the security of EPR data is still a major issue in such systems. In this paper, we develop a compression-then-encryption-based dual watermarking to protect the EPR data for the healthcare system, which produces several significant features. Experiments conducted on a large set of medical data indicate the capability of our proposed method for smart healthcare. Finally, when compared with the existing technique, the proposed work offers better performance in terms of robustness and security.

Maintaining electronic patient records is the primary role for the fruitful implementation of the telehealth services in urban areas to enhance the quality of healthcare. These records frequently shared in-between professionals and healthcare centers so as to develop efficient tool(s) for accurate diagnosis purpose. However, protection of these records is a challenging task in the current era. In this article, we develop a joint watermarking-encryption- error correcting code (ECC) technique for the purpose of securing patient records. The suggested method involves three major steps as follows: 1) watermarks generation and scrambling, 2) encryption of cover and generated watermark via Paillier cryptosystem, and 3) imperceptibly embedding and robustly recovery/extraction of the watermarks. Experimental results indicate that the proposed technique offers high robustness and fulfills all watermarking needs for telehealth applications in terms of imperceptibility, robustness, capacity, and security. Furthermore, the proposed method achieves better robustness against varying attacks, and outperforms former techniques.

With the widespread growth of medical images and improved communication and computer technologies in recent years, authenticity of the images has been a serious issue for E-health applications. In order to this, various notable watermarking techniques are developed by potential researchers. However, those techniques are unable to solve many issues that are necessary to be measured in future investigations. This paper surveys various watermarking techniques in medical domain. Along with the survey, general concepts of watermarking, major characteristics, recent applications, concepts of embedding and recovery process of watermark, and the summary of various techniques (in tabular form) are highlighted in brief. Further, major issues associated with medical image watermarking are also discussed to find out research directions for fledgling researchers and developers.

Exchange of patient record over network required a technique to guarantee security and privacy for tele-health services. This paper presents an improved watermarking technique capable of providing protection of patient data by embedding multi-watermarks in medical cover image using DWT-SVD domain. Prior to embedding, Hamming code is applied to text watermark in order to reduce channel noise distortion for the sensitive data. After embedding, the watermarked medical image is encrypted then compressed. Out of two encryption method and three compression scheme tested, combination of Chaotic-LZW shows the best performance. However, HyperChaotic-LZW combination is more robust against Gaussian, JPEG compression, speckle noise and histogram equalization attacks. We illustrate the good results in terms of objective and subjective evaluation, and verify its robustness for various attacks while maintaining imperceptibility, security and compression ratio. Experimental results demonstrate that the suggested technique archives high robustness against attacks in comparison to the other scheme for medical images.

Medical data transmission and sharing, especially during this COVID-19 pandemic period, on the open channel have become more important for remote diagnosis and treatment purpose. However, the alteration and unauthorized distribution of image data has become easier, and thus the big issue of copy-protection and ownership conflicts has attracted more attention for healthcare research community. Further, large amount of confidential and personal medical records is often stored on cloud environments. However, outsourcing medical data possibly brings the great security and privacy issue, since the confidential records are shared to the third party. In this paper, a robust X-Ray image watermarking is proposed by using Non-Subsampled Contourlet Transform (NSCT) and Multiresolution Singular Value Decomposition (MSVD). For watermark embedding, the maximum entropy component of X-Ray carrier image is firstly decomposed using NSCT. Then, low and high frequency details of carrier and mark image is obtained using MSVD. Further, conceal the watermark detail through modifying the detail of carrier image via the suitable factor. Finally, Shamir's (k, n) secret sharing algorithm is employed to obtain secure marked carrier image. Objective evaluations on 200 X-Ray images of COVID-19 patients demonstrate that the proposed algorithm has not only an excellent invisibility but a strong robustness against the various attacks. The results also show that our algorithm outperforms the related image watermarking algorithms, since it is also suitable for applications in the multi-cloud.

Respiratory reflexes arising from stimulating juxtapulmonary capillary (J) receptors by increasing doses of phenyl diguanide (PDG) were examined in 18 spontaneously breathing cats. In 60% an immediate and four-fold increase in breathing frequency (fR) was produced by doses as small as 5.1 ± μg/kg (range: 3.5–7.5) thus establishing that a significant increase in fR is produced by J receptors by stimulating them with minimal or threshold doses of PDG. In response to similar minimal doses of PDG J receptor afferent activity increased accompanied by acceleration of breathing rate. The response to supra threshold doses was either an apnoea followed by rapid shallow breathing (rsb) or to an apnoea preceded by rsb or only to rsb. Respiratory excursions counted from high-speed run records of intrapleural pressure revealed that the apnoeic response obtained in some cases was a phase of high-frequency breathing and not its suspension. These findings using a chemical stimulus demonstrate that J receptors, with some variability, have a very low threshold for stimulation resulting in notable respiratory acceleration. Thus their afferent output could increase significantly at low intensities of their physiological stimuli such as rise in cardiac output and incipient pulmonary congestion that are generated with mild exercise, to give rise to augmented breathing which is consequently seen.

In order to improve the security of medical data, this paper uses a robust and secure dual watermarking technique in RDWT-SVD domain. Dual watermarking is achieved by embedding text watermark in medical watermark image using DWT, generating the final watermark. Before embedding, turbo code is used to encode the text watermark. Further, trade-off between imperceptibility and robustness is controlled in our scheme through firefly optimization. Experimental results indicate the proposed method offers high imperceptibility and robustness, and have superior overall performance.

The healthcare records include personal and sensitive information about the patient. These records are easily distributed via different platform for clinical diagnosis purpose. Presently, large volumes of medical data are stored on cloud platform. However, outsourcing medical data to these popular platforms may introduce security issues. Thus, a secure watermarking algorithm based on integer wavelet transform (IWT)-Schur-Randomized Singular Value Decomposition (RSVD) is put forward for medical records sharing in the cloud environment. To ensure high level of authentication, discrete wavelet transform (DWT) based embedding is conducted to achieve dual watermarking by concealing system MAC address in the logo image. Prior to this, the system address is encoded via turbo code to reduce /eliminate the channel noise, if any. Further, both invisibility and robustness are achieved by fuzzy inference system (FIS), and the marked image is encrypted using chaotic encryption scheme to further improve the security. Furthermore, experimental results is reported and compared with the existing works which demonstrated promising outcomes, indicating its potential towards realization of a value-added tool for smart healthcare applications.