In remote healthcare applications, continuous monitoring of patient’s electrocardiogram (ECG) is provided as it is popularly used for cardiovascular disease diagnosis. Patient’s ECG signal and other physiological recordings are collected and sent to the hospital server through the Internet. The ECG signal carries confidential health information in addition to the personal identification details and it requires to be secured before transmission through unsecured public networks in accordance with HIPAA for protection of healthcare privacy. In this chapter, a secure and robust electrocardiogram steganography approach is proposed to assure secure transmission of patient confidential data. First, an input ECG signal is converted into frequency domain by applying fractional Fourier transform. Patients’ secret information is embedded in fractional Fourier transform coefficients using the least significant bit embedding approach. In this approach, patients’ secret data is encrypted using the encryption technique before concealing in transform coefficients. Incorporating encryption techniques are permitted only to authorised individuals to extract and read patients confidential medical records and history. Additionally, in order to enhance robustness of the method and to reduce the bit error rate, Hamming error correction coding is employed. To validate the proposed approach, eight different performance measures are computed including: mean squared error, mean absolute error, signal to noise ratio, peak signal to noise ratio, percentage residual difference, bit error rate, relative root mean squared error and fractional Fourier percentage residual difference. The method is evaluated using two different databases: (a) normal MITBIH ECG and (b) Arrhythmia MIT-BIH ECG. The proposed ECG steganography technique introduces minimum distortion in the stego ECG. The scheme achieves a zero bit error rate, high security, and the stego ECG signal can be used for diagnosis. Architecture of an ECG steganography based eHealthcare system is also presented.