Driven by the development of biomedical sensors and the availability of high mobile bandwidth, mobile health (mHealth) systems are now offering a wider range of new services. This revolution makes the idea of in-home health monitoring practical and provides the opportunity for assessment in "real-world" environments producing more ecologically valid data. In the field of insomnia diagnosis, for example, it is now possible to offer patients wearable sleep monitoring systems which can be used in the comfort of their homes over long periods of time. The recorded data collected from body sensors can be sent to a remote clinical back-end system for analysis and assessment. Most of the research on sleep reported in the literature mainly looks into how to automate the analysis of the sleep data and does not address the problem of the efficient encoding and secure transmissions of the collected health data. This article reviews the key enabling communication technologies and research challenges for the design of efficient mHealth systems. An end-to-end mHealth system architecture enabling the remote assessment and monitoring of patient's sleep disorders is then proposed and described as a case study. Finally, various mHealth data serialization formats and machine-to-machine (M2M) communication protocols are evaluated and compared under realistic operating conditions.