Achintya Das

Optimisation of scaling factors in electrocardiogram signal watermarking using cuckoo search

Authentication is very important in validating a medical content in the domain of telemedicine; however, there are many challenges. Accurate verification is paramount, and any misuse of personal information may have serious consequences. Many authentication processes tried to design various methods to minimise such discrepancies. In this current work, we propose a new approach to design a robust biomedical content authentication system by embedding logo of the hospital within the electrocardiogram signal by means of both discrete wavelet transformation and cuckoo search CS. An adaptive meta-heuristic cuckoo search is used to find the optimal scaling factor settings for logo embedding. Results show that the proposed method can serve as a secure and accurate authentication system.

Feature analysis for the blind-watermarked electroencephalogram signal in wireless telemonitoring using Alattar's method

The present medical era has seen quite a considerable amount of work been done in tele-monitoring that involves transmission of biomedical signals through wireless media. Exchange of information amongst various hospital systems and medical centers require high level of reliability and security. Signal integrity can be verified, authenticity and achieved control over the copy process can be proved by adding watermark in the original information as multimedia content. Electroencephalography (EEG) is a medical test that records the electrical activity originating from the brain. In this present work, Alattars Method is used for watermark insertion and extraction in an EEG signal without devalorizing its diagnostic parameters. In the second part of the paper, different features in the time domain and the spatial domain are obtained from the original EEG signal, watermarked EEG signal, and the recovered EEG signal.

Feature analysis for the reversible watermarked electrooculography signal using Low distortion Prediction-error Expansion

At present, most of the hospitals and diagnostic centers globally, have started using wireless media for exchange of biomedical information (Electronic Patient Report or hospital logo) for mutual availability of therapeutic case studies. Exchange of information amongst various hospital and medical centers require high level of reliability and security. Signal integrity can be verified, authenticity and achieved control over the copy process can be proved by adding watermark in the original information as multimedia content. Electrooculography (EOG) is a medical test that records the movements and position of the eyes. In this present work, Low distortion Prediction-error Expansion technique is used for watermark insertion and extraction in an EOG signal without devalorizing its diagnostic parameters. It can be seen that in this approach the correlation value of the original watermark and the extracted watermark is quite high. The Signal-to-Noise ratio (SNR) between the original EOG signal and the recovered EOG signal markedly improves which claims the robustness of the method. In the second part of the present work different features of the original EOG signal, watermarked EOG signal and recovered EOG signal are analysed.

DWT-DCT-SVD based blind watermarking technique of gray image in electrooculogram signal

At present most of the hospitals and diagnostic centers globally, use wireless media to exchange biomedical information for mutual availability of therapeutic case studies. The required level of security and authenticity for transmitting biomedical information through the internet is quite high. Level of security can be increased; authenticity of the information can be verified and control over the copy process can be ascertained by adding watermark as “ownership” information in multimedia content. In this proposed method different types of gray scale biomedical images can be used as added ownership (watermark) data. Electrooculography is a medical test used by the ophthalmologists for monitoring eyeball movement in Rapid Eye Movement (REM) and non-REM sleep, to detect the disorders of human eyes and to measure the resting potential of the eye. In this present work 1-D EOG signal is transformed into 2-D signal. DWT, DCT, SVD are applied on the transformed 2D signal to embed watermark in it. Extraction of watermark image is done by applying inverse DWT, inverse DCT and SVD. The Peak Signal to Noise Ratio (PSNR) of the original EOG signal vs. watermarked signal and the correlation value between the original and extracted watermark image are calculated to prove the efficacy of the proposed method.

Tamper detection of electrocardiographic signal using watermarked bio–hash code in wireless cardiology

The current globalised era is marked with a rapid increase in the use of wireless media to exchange information over globally distributed locations. This advancement and growth of technologically mediated information helps to provide medical care from a distant location by exchanging biomedical information amongst various hospitals and diagnostic centres across the world. However, while transmitting, the medical information becomes highly vulnerable to miscellaneous attacks like tampering and hacking. A watermark is added in the Electrocardiographic (ECG) signal to increase the level of security to help protect the integrity of the data and decrease the chances of wrong diagnosis. In this current work, a technique is proposed to detect undesirable modifications, if present, in a transmitted biomedical ECG signal. The proposed method is based on bio–hashing and reversible watermarking techniques.

A hybrid reversible watermarking technique for color biomedical images

In the field of medical diagnosis, exchange of information amongst various hospitals and diagnostic centres for mutual availability of diagnostic and therapeutic case studies is quite common. During digital image transportation, some information needs to be added or hidden in order to identify the owner of the data in multimedia content. EPR (electronic patient record) or hospital logo can be hidden within a bio medical image for high security instead of transferring the EPR/logo through the internet. In this present work a reversible watermarking method (Odd-Even Method) is used for watermark insertion and extraction in a bio medical image with large data hiding capacity, security as well as high watermarked quality. It can be seen that in this approach the correlation value of the original watermark and the extracted watermark is 1 and the experimental results demonstrate that, no matter how much secret data is embedded, Peak Signal-to-Noise Ratio (PSNR) is high enough which clams the robustness of the method.

Wavelet based watermarked normal and abnormal heart sound identification using spectrogram analysis

Present work proposes a computer-aided identification of watermarked normal or abnormal heart sound based on Wavelet Transformation for tele-diagnosing of heart diseases. In this proposed method, the heart sound is converted into 2-D square matrix form. The 2-D signal is decomposed into four sub bands using Stationary Wavelet Transformation. HH1 sub band is further decomposed using Stationary Wavelet Transformation. Watermark image is embedded within the generated HH2 sub band. During embedding, watermark image is dispersed within the selected sub-band using a random sequence and a Session key. After embedding the watermark, that 2-D signal is taken as an input of spectrogram analysis. Due to the presence of Cumulative Frequency components in the spectrogram, DWT is applied on the spectrogram up to n level to extract the features from the individual approximation components. One dimensional feature vector is obtained by evaluating the Row Mean of the approximation component of the spectrogram. Watermark image is retrieved from the de-noised Watermarked Heart Test Sound. Instead of considering the heart sound samples, the present approach recognizes the set of spectrograms as the database. Thereafter 1-D feature vectors are attained by evaluating the Row Mean of the spectrogram approximation components obtained from the trained samples. Subsequently, minimum Euclidean distance between the Feature vector of the test heart sound and the Feature vectors of the trained heart sound samples is determined to identify the heart sound. By applying this algorithm, almost 78% of accuracy is achieved whereas without watermarking the accuracy is almost 82%.

Electrocardiogram Feature Based Inter-human Biometric Authentication System

Biometrics integrates various technologies to identify an individual by exploiting their physiological and behavioral characteristics, which are unique and measurable. This paper proposes a novel technique for the development of a robust and secure biometric authentication system. In this current work, an interhuman ECG-Hash code is generated by performing an inner product between the Electrocardiogram (ECG) feature matrices of two different individuals located remotely. The individuals will have each others ECG features, stored in their database. The accuracy of the system increases as the authentication mechanism requires traits from both the individuals, amongst whom the transmission is taking place. Moreover, the use of ECG features as a biometric trait enhances the security aspects of the system as traits like fingerprints or facial features maybe compromised with age or otherwise.

Stationary Wavelet Transformation Based Self-recovery of Blind-Watermark from Electrocardiogram Signal in Wireless Telecardiology

At present, considerable amount of work has been done in tele-monitoring that involves transmission of biomedical signals through wireless media. Exchange of bio-signals between hospitals requires efficient and reliable transmission. Watermarking is added “ownership” information in multimedia content to prove authenticity, verify signal integrity, and achieve control over the copy process. The ECG signal is a sensitive diagnostic tool that is used to detect various cardio-vascular diseases by measuring and recording the electrical activity of the heart in exquisite detail. This paper proposes a method of binary watermark embedding into the Electrocardiogram (ECG) signal and a self recovery based watermark extraction mechanism using Stationary Wavelet Transformation (SWT), Spread-Spectrum and quantization. In this approach, the generated watermarked signal having an acceptable level of imperceptibility and distortion is compared to the original ECG signal. Finally, a comparative study of detected P-QRS-T components is done to measure the diagnostic value change as an effect of watermarking. In this approach the generated watermarked ECG signal having an acceptable level of imperceptibility and distortion is compared to the Original ECG signal based on Peak Signal to Noise Ratio (PSNR) and correlation value.

Optical cup to disc ratio measurement for glaucoma diagnosis using harris corner

In medical study, retinal image processing plays a vital role in detecting the abnormalities of eye or ocular diseases like Glaucoma and diabetic retinopathy. Glaucoma is one of the two major causes of blindness worldwide, accounting for approximately 13% of visually impaired people. Glaucoma is physiologically described as the deterioration of optic nerve cells, and is characterized by alterations in the optic nerve head and visual field. The measurement of neuro-retinal optic cup-to-disc ratio (CDR) is an important index of Glaucoma, as the increased excavation of the optic cup occurs because of Glaucomatous neuropathy increasing the CDR. Currently, CDR evaluation is manually performed by ophthalmologists. Due to the interweavement of blood vessels with the surrounding tissues around the cup, automatic calculation of optic cup boundary thus being challenging. In this paper, an automatic method for CDR determination using Harris Corner is proposed.