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Augmented reality (AR) technologies enable people to observe the world in new ways. Generally, AR uses computer-generated graphics to overlay improvements on the user's perspective of reality using big data and machine learning techniques. In this paper, we present a comprehensive survey of recent privacy-preserving big data analytics applications for the emerging applications of machine learning in the era of 5G. We highlight the fundamental features of security and privacy for 5G-based wearable device applications. We then present a study on privacy-preserving machine learning techniques. Finally, we explain the implementation details of a study case of a secure prediction service using the Convolutional Neural Network (CNN) model with the CKKS homomorphic encryption technique. We aim to anticipate how security technology will be useful for the safe processing of the collected data from wearable devices, particularly in increasing the utility and performance of privacy-preserving machine learning analytics in the era of 5G and beyond.