Alexander V. Borodin

Architectural approach to the multisource health monitoring application design

Forward-looking personalized health care services tend to utilize benefits of smart spaces. Particularly, a smartphone app can be used as a hub for collecting and preprocessing of the vital health parameters provided by various sensors. Thus, the IoT-enabled mHealth apps should be designed to be easy extendable for the new kinds of data sources and processing units. In this paper, the architecture of mobile app supporting several data sources is described. Also, implementation issues related to Android and Windows Phone platforms are discussed.

Digital assistance services for emergency situations in personalized mobile healthcare: Smart space based approach

Recent progress in technologies of the Internet of Things (IoT) enables advanced scenarios for mobile healthcare (m-Health). In this paper, we consider the service intelligence in m-Health (so called smart services). On the one hand, such a service utilizes the telemedicine approach when existing healthcare services (located in hospital) are delivered to remote patients (out of hospital). On the other hand, construction and delivery of a smart service benefit from additional intelligence attributes, beyond a fixed set of healthcare services of a given medical information system. For this promising class of m-Health services, we introduce reference scenarios of personalized assistance for a mobile patient with focus on emergency cases. Our development employs the smart spaces paradigm: patients, medical personnel, healthcare services, and other participants operate within a common networked computing environment and interact by sharing information and its semantics. We contribute design solutions to construct services as smart m-Health spaces.

Smart Spaces Enabled Mobile Healthcare Services in Internet of Things Environments

The article studies the smart spaces approach applied for development of mobile healthcare m-Health services deploying in Internet of Things IoT environments. The authors consider a reference architecture model of the service ecosystem with focus on intelligent utilization of multi-source data originated from the IoT environment. Based on the architecture the authors introduce two reference scenarios: assistance in providing the first aid and communication with the hospital information system. For the architectural model and the scenarios pilot implementations are developed on the open source Smart-M3 platform.

The cross-platform application for arrhythmia detection

The Cross-platform application for arrhythmia detection is an application for monitoring of patients cardiac abnomalities. If a patient has some kind of arrhythmia, the application provides a connection between the patient and doctor. The application is originally developed and tested for smartphones with Symbian OS, but it designed to be cross-platform. It is used with cardiac monitor Alive Heart Monitor and Activity Monitor. Alive Heart Monitor transmits cardio and auxiliary data by bluetooth to a smartphone. Then the application processes this data and says what happens to the cardiac rhythm.

Overview of algorithms for electrocardiograms analysis

Long-term monitoring of heart function can prevent the number of the sudden deaths caused by heart diseases. There are a good chances that the help is rendered in time. Since in long-term heart examination huge amounts of data are generated it is needed an effective electrocardiogram (ECG) analysis algorithm. There are many ways to detect QRS-comlexes and other components. So in this paper major algorithms are presented. And it is described how it can be applied in real-time ECG analysis system.

An ontology-based semantic design of the survey questionnaires

Questionnaire is the most common tool of data collection for the purposes of either assessment of the trend of observed parameter of the individual, or statistical survey. Due to the prevalence of mobile devices, the cost of questionnaire-based data gathering from the respondents became extremely low, and thus, collecting of the information can be easily reiterated, providing the deep insight of the studied phenomenon. From the other hand, regular questionnaire-based data collection inevitably leads to the significant growth of the recorded information and to the necessity of automatic processing, e.g., the reasoning on the data to take a decisions. In this paper, the generic ontology for representing questionnaires in machine-readable form is proposed. The presented ontology is intended to use in decision support systems and in personalized smart environments.

Mobile health service is promising to detect the blood pressure and HRV fluctuations across the menstrual and the lunar cycle

Here we report on experimental feasibility and preliminary results on mobile health services to detect enigmatic effect of the lunar cycle (LC) on heart rate variability (HRV) parameters and blood pressure (BP) in young females, with respect to the menstrual cycle (MC). We found that the MC exerted strong effect on varied HRV parameters specifically in the ovulation phase. Unlike the MC, the LC presented only tiny and non-significant, though still notable, effect on BP and HRV seen primarily in the full moon phase. We hypothesize on potential usability of e-medicine services, such as mobile-nested on-line day-to-day monitoring of electrocardiogram (ECG) for HRV, as a research tool for a longitudinal experiment with ultimate goal to detect the LC impact on human circulation system. Would such hypothetic effect experimentally been found, a mobile medicine services could be invented which allows user synchronizing the MC with the LC for better awareness on current physiological status and planning of daily activities and reproductive behavior.

On mobile personalized healthcare services for human involvement into prevention, therapy, mutual support, and social rehabilitation

Many digital healthcare services now follow the cybermedicine approach. The Internet is used to deliver such services as medical consultations, diagnosis, and prescriptions. Mobile services provide end-users (patients) with online and personalized access to consultations and treatment with other end-users (medical professionals). Services become social, taking into account the activity of patients and their collaborative work (in participation with medical professionals and other interested parties). In this paper, we discuss the opportunities that Internet of Things (IoT) provides to the cybermedicine development. Parkinsons disease (PD) serves as a case study, which we use to motivate the effective IoT use for human involvement into healthcare processes such as disease progress prevention, therapy, people mutual support, and social patient rehabilitation. We define several research problems for developing new models, algorithms, and methods within overlapping domains of healthcare, data engineering, and IoT technology.

A System for Hypertension Management Assistance Based on the Technologies of the Smart Spaces

Affecting up to 40% of the world’s population, arterial hypertension results in high economic and social burden. Long-term treatment period along with the necessity of personal lifestyle changes lead to the low adherence to the treatment among the patients. As a consequence, the hypertension-related complications can be gradually developed between visits to the doctor, among them are heart attack, heart failures, strokes and even sudden cardiac death. In the proposed integrated approach, the mobile personal monitoring system, constructed on the principles of smart spaces, is used to address the problem of low adherence. Both continuous monitoring of the vital signs and the questionnaire-based regular health status audit are used for the assessment of the complication risk. Health parameters and evaluated risk markers are published in the semantic-driven information storage, and the personalized recommendation service, aimed at the increasing the adherence to the treatment among hypertensive patients, is constructed based on cooperation of distributed software agents.