Dr. Reza Rawassizadeh performed a speech on the subject ofthe need for Paradigm shift in Mobile Health Systems” At Allied Medical Sciences School.


      There many Mobile Health (mHealth) applications, and wearable devices in the market. The consumer demand for these technologies remains very high. Even in regions, where access to robust broadband network infrastructure is limited, the use of mobile and wearables for health purposes is rapidly rising. On the other hand, mHealth applications have not been successful in delivering their initial promises of revolutionizing health care and improving patient monitoring by shifting the focus from “treatment” to “prevention”. Several recent studies have analyzed the limitations of mHealth applications. Two major challenges have been identified that affect the usability of mHealth technologies, including hardwares such as fitness tracker, smartphone and software applications. These challenges include: (i) The “validity of collected data” from wearable and mobile devices is questionable causing physicians and health care stakeholders not trusting the data collected by these systems. (ii) Existing systems generally “interact with users and present information through graph-based visualizations and numbers”. The graph is difficult to understand among different groups of users, including individuals with low numeracy, low literacy and minor visual impairments. Unfortunately, individuals from low socio-economical background have lower literacy and are more exposed to health risks, which could be mitigated by use of mobile and wearable digital devices, such as cardio vascular related risks. We believe there is a need to focus on applications and data analytical methods that can operate independently on small devices such as wearables and IoT devices, i.e. NoCloud algorithms. In this talk, I will describe two of our resource efficient data mining approaches and one information retrieval facility that could be used on wearable, mobile and IoT devices. First, I introduce two components (Natural Language Interface and Behavioral Mining Algorithm) of an ongoing framework for collecting and reflecting on Information. Then, I describe a low-cost robot that can stay on the users’ proximity and accurately collect information about users.