Background: Diabetes is a chronic disease, with high prevalence across many nations, which is characterized by elevated level of blood glucose and risk of acute and chronic complication. The Kingdom of Saudi Arabia (KSA) has one of the highest levels of diabetes prevalence globally. It is well-known that the treatment of diabetes is complex process and requires both lifestyle change and clear pharmacologic treatment plan. To avoid the complication from diabetes, the effective behavioural change and extensive education and self-management is one of the key approaches to alleviate such complications. However, this process is lengthy and expensive. The recent studies on the user of smart phone technologies for diabetes self-management have proven to be an effective tool in controlling hemoglobin (HbA1c) levels especially in type-2 diabetic (T2D) patients. However, to date no reported study addressed the effectiveness of this approach in the in Saudi patients. This study investigates the impact of using mobile health technologies for the self-management of diabetes in Saudi Arabia. Methods: In this study, an intelligent mobile diabetes management system (SAED), tailored for T2D patients in KSA was developed. A pilot study of the SAED system was conducted in Saudi Arabia with 20 diabetic patients for 6 months duration. The patients were randomly categorized into a control group who did not use the SAED system and an intervention group whom used the SAED system for their diabetes management during this period. At the end of the follow-up period, the HbA1c levels in the patients in both groups were measure together with a diabetes knowledge test was also conducted to test the diabetes awareness of the patients. Results: The results of SAED pilot study showed that the patients in the intervention group were able to significantly decrease their HbA1c levels compared to the control group. The SAED system also enhanced the diabetes awareness amongst the patients in the intervention group during the trial period. These outcomes confirm the global studies on the effectiveness of smart phone technologies in diabetes management. The significance of the study is that this was one of the first such studies conducted on Saudi patients and of their acceptance for such technology in their diabetes self-management treatment plans. Conclusions: The pilot study of the SAED system showed that a mobile health technology can significantly improve the HbA1C levels among Saudi diabetic and improve their disease management plans. The SAED system can also be an effective and low-cost solution in improving the quality of life of diabetic patients in the Kingdom considering the high level of prevalence and the increasing economic burden of this disease.

Modern wheelchairs, with advanced and robotic technologies, could not reach the life of millions of disabled people due to their high costs, technical limitations, and safety issues. This paper proposes a gesture-controlled smart wheelchair system with an IoT-enabled fall detection mechanism to overcome these problems. It can recognize gestures using Convolutional Neural Network (CNN) model along with computer vision algorithms and can control the wheelchair automatically by utilizing these gestures. It maintains the safety of the users by performing fall detection with IoT-based emergency messaging systems. The development cost of the overall system is cheap and is lesser than USD 300. Hence, it is expected that the proposed smart wheelchair should be affordable, safe, and helpful to physically disordered people in their independent mobility.

Background: The purpose of the study is to evaluate the effectiveness of mobile health technology such as private social network (PCOS system) in creating awareness about the disease management among the women diagnosed with the polycystic ovarian syndrome. Methods: A pilot study was conducted in Tabuk, Saudi Arabia. The study was carried out for a period of three months using a private social network as an intervention. The private social network is used as an interface to educate and create awareness among the participants in the study. Fifty women diagnosed with PCOS were randomly selected and were distributed in to control group (doesn't use PCOS system) and intervention group (use the private social network). The level of the polycystic ovarian syndrome awareness was measured using a structured questionnaire at the beginning and end of the follow-up period. Results: More than 80 posts and 10 pictures contain data about PCOS were conveyed by medical staff. Also, about 120 private SMS messages between medical staff and the patients were refined. The after effects of this investigation demonstrated that the intervention had better awareness about polycystic ovary syndrome management compared to the control group (F =18.25; P<0.0001). Conclusions: This study of the private social network among the PCOS patients demonstrated that mobile health technology such as the private social network can substantially enhance the PCOS disease awareness levels among Saudi women. The PCOS System can also help in reducing the costs as most of the disease management process is handled over the application through the messages and feedbacks is provided through the application, and in saving time by avoiding hospital visits. This study is first-of-its kind conducted in Saudi Arabia.

The preponderance of obesity and being overweight among children has increased significantly during the last two decades in Saudi Arabia and United Arab Emirates (UAE) with overwhelming consequences to public health. Most recommended approaches have paid attention to a healthier diet and physical activity (PA) to reduce obesity. Recent research shows that the use of social robots could play a vital role in encouraging children to improve their skills in self-management. As children need to be surprised and feel a sense of enjoyment when involved in any activity where they can spend time and actively engage in activities, social robots could be an effective intervention for this purpose. In this context, the current project aimed to build an innovation social robot system to offer a set of activities to help obese children improve their capabilities to manage their selves properly and increase their obesity knowledge. This study aimed to determine the perceptions of obese children towards the NAO robot, a new medical technology, and analyze their responses to the robot’s advice and education-related activities. A proposed model of the intervention using the NAO robot is discussed in this study, and a pilot study was conducted to assess the performance of the proposed system. The obtained results showed an average acceptability of 89.37% for social robots to be involved in obesity management.

Objective: Chronic lung-related diseases, with asthma being the most prominent example, characterized by diverse symptoms and triggers, present significant challenges in disease management and prediction of exacerbations across patients. This research aimed to devise a practical solution by introducing a personalized alert system tailored to individual lung function and environmental conditions, offering a holistic approach for the management of a range of chronic respiratory conditions. Methods: In response to these challenges, we developed a personalized alert system based on individual lung function tests conducted in diverse environmental conditions, as determined by air-quality sensors. Our research was substantiated through an observational pilot study involving twelve healthy participants. These participants were exposed to varying air quality, temperature, and humidity conditions, and their lung function, as indicated by peak expiratory flow (PEF) values, was monitored. Results: The study revealed pronounced variability in pulmonary responses across different environments. Leveraging these findings, we proposed a design of a personalized alarm system that monitors air quality in real-time and issues alerts under potentially unfavorable environmental conditions. Additionally, we investigated the use of basic machine learning techniques to predict PEF values in these varied environmental settings. Discussion: The proposed system offers a proactive approach for individuals, particularly those with asthma, to actively manage their respiratory health. By providing real-time monitoring and personalized alerts, it aims to minimize exposure to potential asthma triggers. Ultimately, our system seeks to empower individuals with the tools for timely intervention, potentially reducing discomfort and enhancing management of asthma symptoms.