Atif Ali Khan

Chao Zhang, Hanxin Zhang, Atif Khan et al.

Importance: Lower-resource areas in Africa and Asia face a unique set of healthcare challenges: the dual high burden of communicable and non-communicable diseases; a paucity of highly trained primary healthcare providers in both rural and densely populated urban areas; and a lack of reliable, inexpensive internet connections. Objective: To address these challenges, we designed an artificial intelligence assistant to help primary healthcare providers in lower-resource areas document demographic and medical sign/symptom data and to record and share diagnostic data in real-time with a centralized database. Design: We trained our system using multiple data sets, including US-based electronic medical records (EMRs) and open-source medical literature and developed an adaptive, general medical assistant system based on machine learning algorithms. Main outcomes and Measure: The application collects basic information from patients and provides primary care providers with diagnoses and prescriptions suggestions. The application is unique from existing systems in that it covers a wide range of common diseases, signs, and medication typical in lower-resource countries; the application works with or without an active internet connection. Results: We have built and implemented an adaptive learning system that assists trained primary care professionals by means of an Android smartphone application, which interacts with a central database and collects real-time data. The application has been tested by dozens of primary care providers. Conclusions and Relevance: Our application would provide primary healthcare providers in lower-resource areas with a tool that enables faster and more accurate documentation of medical encounters. This application could be leveraged to automatically populate local or national EMR systems.

Atif Ali Khan, Oumair Naseer, Daciana Iliescu et al.

One of the defining characteristic of human being is their ability to walk upright. Loss or restriction of such ability whether due to the accident, spine problem, stroke or other neurological injuries can cause tremendous stress on the patients and hence will contribute negatively to their quality of life. Modern research shows that physical exercise is very important for maintaining physical fitness and adopting a healthier life style. In modern days treadmill is widely used for physical exercises and training which enables the user to set up an exercise regime that can be adhered to irrespective of the weather conditions. Among the users of treadmills today are medical facilities such as hospitals, rehabilitation centres, medical and physiotherapy clinics etc. The process of assisted training or doing rehabilitation exercise through treadmill is referred to as treadmill therapy. A modern treadmill is an automated machine having built in functions and predefined features. Most of the treadmills used today are one dimensional and user can only walk in one direction. This paper presents the idea of using omnidirectional treadmills which will be more appealing to the patients as they can walk in any direction, hence encouraging them to do exercises more frequently. This paper proposes a fuzzy control design and possible implementation strategy to assist patients in treadmill therapy. By intelligently controlling the safety belt attached to the treadmill user, one can help them steering left, right or in any direction. The use of intelligent treadmill therapy can help patients to improve their walking ability without being continuously supervised by the specialists. The patients can walk freely within a limited space and the support system will provide continuous evaluation of their position and can adjust the control parameters of treadmill accordingly to provide best possible assistance.

Oumair Naseer, Atif Ali Khan

Use of Control theory within process control industries has changed rapidly due to the increase complexity of instrumentation, real time requirements, minimization of operating costs and highly nonlinear characteristics of chemical process. Previously developed process control technologies which are mostly based on a single controller are not efficient in terms of signal transmission delays, processing power for computational needs and signal to noise ratio. Hybrid controller with efficient system modelling is essential to cope with the current challenges of process control in terms of control performance. This paper presents an optimized mathematical modelling and advance hybrid controller (Fuzzy Logic and PID) design along with practical implementation and validation of pH neutralization pilot plant. This procedure is particularly important for control design and automation of Physico-chemical systems for process control industry.