Mobile-Health Systems Use Diagnostically Driven Medical Video Technologies [Life Sciences

Mobile-health (m-health) systems and services are expected to undergo significant growth in the near future [1]–[4]. Based on recent advances in signal and video processing and communications technologies, m-health systems and services are driven by greater socioeconomic aspects aiming to bridge society’s demands for specialized health-care delivery.

Figure 1 depicts typical application scenarios of m-health systems and services. This comprises m-health medical video communication systems, remote monitoring for personal health based on body area networks, disaster crisis management, electronic health records, m-health cloud-based services, and smartphone applications.

Medical video communication is a key bandwidth-demanding component of m-health applications ranging from emergency incidents response, to home monitoring, and medical education. Inambulance video (trauma and ultrasound) communication for remote diagnosis and care can provide significant time savings that in turn can prove decisive for the patient’s survival. Similarly, emergency scenery video can assist in better triage and preparatory hospital processes. Remote diagnosis allows access to specialized care for people residing in remote areas, but also for the elderly, and people with chronic diseases and mobility problems. Moreover, it can support mass population screening and second opinion provision, especially in developing countries. Medical education also benefits from real-time surgery video transmission as well as ultrasound examinations.

Overall, wireless medical video communication poses significant challenges that stem from limited bandwidths over noisy channels. In terms of both bandwidth and processing requirements, medical videos dominate over other biomedical signals. Clearly, the wider application of future m-health systems will depend and also benefit from the development of effective medical video communication systems, extending current systems that support real-time and continuous monitoring of biosignals.