Background: With the continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth. While eHealth is broadly focused on information and communication technologies, mHealth seeks to explore more into mobile devices and wireless communication. Since mobile phone penetration has exceeded other infrastructure in low and middle-income countries (LMICs), mHealth is seen as a promising component to provide pervasive and patient-centered care. Objectives: The aim of our research work for this paper is to examine the mHealth literature to identify application areas, target diseases, and mHealth service and technology types that are most appropriate for LMICs. Methods: Based on the 2011 WHO mHealth report, a combination of search terms, all including the word “mHealth”, was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Articles were included if they were published in English, covered an mHealth solution/ intervention, involved the use of a mobile communication device, and included a pilot evaluation study. Articles were excluded if they did not provide sufficient detail on the solution covered or did not focus on clinical efficacy/effectiveness. Cross-referencing was also performed on included articles. Results: 842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the highest number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternal and child’s health (MCH) (n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), telemedicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short study durations. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence. Conclusions: SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in high income countries. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. Remaining application areas are rarely addressed. Diabetes is the most commonly targeted medical condition, yet remains deficient in LMICs.

/pdf/mhealth-application-areas-and-technology-combinations-a-4bmtpjlm43.pdf

mHealth Application Areas and Technology Combinations*. A Comparison of Literature from High and Low/Middle Income Countries.

Internet of Things is a system where appliances are embedded with software, sensors and actuators. The devices are able to transfer data over a network and also communicate with each other [1]. The literature reports that many systems based on single mode of monitoring, power or lighting are not integrated into one control system, so there are complex control cumbersome, high operating costs. To solve this problem, we propose a Modbus protocol design for intelligent building security, All these perception-control-management are integrated into one system. This system adopts the Modbus protocol format for the data communication, the hardware system with processor as ARM5708 industry as the core development board development and design, Using Linux operating system, JavaWeb development and database management technology to achieve data interaction, display, storage, identification and other functions, Completed an embedded network communication protocol gateway and industrial design, and connects the traditional serial connection Modbus fieldbus and Ethernet communication, and finally the application is realized through Modbus TCP protocol. Compared with the previous building security design, we adopted Modbus bus control, which saved the resources of the core development board and effectively applied the Modbus TCP protocol and Modbus RTU protocol. The webpage control end realizes the collection of the temperature and humidity gas concentration of the intelligent building and the detection of the human body infrared. For the purpose of verification and testing, a three-story building prototype was built.

Design and Implementation of Modbus Protocol for Intelligent Building Security

Most medical centers in Taiwan implement the reduction of “D2B” time, which is defined as the time interval between an Acute Myocardial Infarction (AMI) patient arrives at hospital and he/she receives primary percutaneous coronary intervention. The patient’s Electrocardiogram (ECG) must be confirmed by a cardiologist and made sure the patient really has AMI. For the confirmation, the cardiologists must access a PC, connect it to the intranet of the hospital and employ the special PACS (Picture Archiving and Communication System) image browser before he/she can diagnose the ECG. But this will prolong the D2B time since PC, the browser and/or network may be currently unavailable. In this paper, we introduce a system with which cardiologists can directly utilize their smart phones to browse the patient’s ECG after receiving the short message service (SMS) text issued by his/her hospital so as to avoid the mentioned problem and shorten the D2B time.

Healthcare-based on Cloud Electrocardiogram System: A Medical Center Experience in Middle Taiwan.

In mobile Internet of Things, there are many challenges, including sensing technology of sensors, how and when to join cooperative transmission, and how to select the cooperative sensors. To address these problems, we studied the combination forecasting based on the multilevel sensing technology of sensors, building upon which we proposed the adaptive opportunistic cooperative control mechanism based on the threshold values such as activity probability, distance, transmitting power, and number of relay sensors, in consideration of signal to noise ratio and outage probability. More importantly, the relay sensors would do self-test real time in order to judge whether to join the cooperative transmission, for maintaining the optimal cooperative transmission state with high performance. The mathematical analyses results show that the proposed adaptive opportunistic cooperative control approach could perform better in terms of throughput ratio, packet error rate and delay, and energy efficiency, compared with the direct transmission and opportunistic cooperative approaches.

/pdf/adaptive-opportunistic-cooperative-control-mechanism-based-24s5qhzah2.pdf

Adaptive Opportunistic Cooperative Control Mechanism Based on Combination Forecasting and Multilevel Sensing Technology of Sensors for Mobile Internet of Things

The American Heart Association (AHA) has demonstrated that involvement in Cardiac Rehabilitation (CR) can reduce Myocardial Infarction (MI) or heart attack recurrence. However, CR participation in Indonesia was found to be minimal after hospital discharge. Understaffing and lack of availability and access are some of the reasons. An efficient Internet of Things (loT) system could overcome inadequate staffing and improve the overall outcome of CR. The proposed loT system consists of multiple loT technologies and a wearable device (E4 wristband). This paper focuses on building a framework with the aim in developing an loT system for post-MI patients during CR in Indonesia and the development of a Convolutional Neural Network (CNN) based neural network model to classify human activity (HAR) based on labelled accelerometer data taken from the chosen E4 loT device. This paper also explains the process of training and testing of 2-dimensional Convolutional Neural Network and the development of selecting the wearable device. This paper also explains the medical and ethical guidelines for developing our framework. At the end of the study, it was observed that the proposed model had recorded a high classification accuracy. The CNN model had a classification accuracy of 96% of all six activities.

An IoT System For Post-Myocardial Infarction Patients During Cardiac Rehabilitation (CR) In Indonesia

We established a regional cooperative emergency care system of ST-elevation myocardial infarction patients based on the internet of things. In this article, the current status and problems of ST-elevation myocardial infarction patient emergency care have been studied and key influence factors are found. As the results, a shorter time from symptom onset to reperfusion is achieved with improved outcomes for patients with ST-segment elevation myocardial infarction (STEMI). Primary percutaneous coronary intervention (PCI) in patients with STEMI significantly reduces mortality and morbidity, particularly when door-to-balloon (D2B) time is &#60; 90 min. An expedited pre-hospital diagnosis and transfer pathway was developed, with rapid reperfusion times and favorable outcomes.

A study of regional cooperative emergency care system for ST-elevation myocardial infarction patients based on the internet of things

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A study of regional cooperative emergency care system for ST-elevation myocardial infarction patients based on the internet of things