Use and Trends of Diabetes Self-Management Technologies: A Correlation-Based Study.

Applications and systems for diabetes self-management are growing and involve a vast majority of factors to consider. This study was aimed at examining the integration of portable technologies for diabetes self-management, as well as benefits and issues arising of its use. From a web-based study on several groups of people with diabetes, most of them accustomed to the daily use of devices and applications for self-control, a deeper analysis based on correlations and inference was conducted considering information about the disease, technology knowledge and devices handling, use of technologies for diabetes control and management, and training with devices from a clinical and educational viewpoint. In this study, more than 70% of participants use Continuous Glucose Systems and additional devices (41.85% also use insulin pumps) which impacts positively on the knowledge of incoming technologies. The "easy to use" factor of current apps for diabetes self-management is the most valuable feature. Also, 88.98% of participants did not use gamification-based methods during the initial training sessions, although gamification is a useful technique in learning stages. An inference analysis shows how specific characteristics of diabetes devices and apps should improve. On the basis of the results, we discuss about benefits, shortcomings, and the state of these technologies and patient needs for the future.

m-Health: Lessons Learned by m-Experiences.

m-Health is an emerging area that is transforming how people take part in the control of their wellness condition. This vision is changing traditional health processes by discharging hospitals from the care of people. Important advantages of continuous monitoring can be reached but, in order to transform this vision into a reality, some factors need to be addressed. m-Health applications should be shared by patients and hospital staff to perform proper supervised health monitoring. Furthermore, the uses of smartphones for health purposes should be transformed to achieve the objectives of this vision. In this work, we analyze the m-Health features and lessons learned by the experiences of systems developed by MAmI Research Lab. We have focused on three main aspects: m-interaction, use of frameworks, and physical activity recognition. For the analysis of the previous aspects, we have developed some approaches to: (1) efficiently manage patient medical records for nursing and healthcare environments by introducing the NFC technology; (2) a framework to monitor vital signs, obesity and overweight levels, rehabilitation and frailty aspects by means of accelerometer-enabled smartphones and, finally; (3) a solution to analyze daily gait activity in the elderly, carrying a single inertial wearable close to the first thoracic vertebra.

Smart Device-Based Notifications to Promote Healthy Behavior Related to Childhood Obesity and Overweight.

Obesity is one of the most serious public health challenges of the 21st century and it is a threat to the life of people according to World Health Organization. In this scenario, family environment is important to establish healthy habits which help to reduce levels of obesity and control overweight in children. However, little efforts have been focused on helping parents to promote and have healthy lifestyles. In this paper, we present two smart device-based notification prototypes to promote healthy behavior with the aim of avoiding childhood overweight and obesity. The first prototype helps parents to follow a healthy snack routine, based on a nutritionist suggestion. Using a fridge magnet, parents receive graphical reminders of which snacks they and their children should consume. The second prototype provides a graphical reminder that prevents parents from forgetting the required equipment to practice sports. Prototypes were evaluated by nine nutritionists from three countries (Costa Rica, Mexico and Spain). Evaluations were based on anticipation of use and the ergonomics of human-system interaction according to the ISO 9241-210. Results show that the system is considered useful. Even though they might not be willing to use the system, they would recommend it to their patients. Based on the ISO 9241-210 the best ranked features were the system's comprehensibility, the perceived effectiveness and clarity. The worst ranked features were the system's suitability for learning and its discriminability.

Estimation of Temporal Gait Events from a Single Accelerometer Through the Scale-Space Filtering Idea.

The purpose of this paper is to develop an accelerometry system capable of performing gait event demarcation and calculation of temporal parameters using a single waist-mounted device. Particularly, a mobile phone positioned over the L2 vertebra is used to acquire trunk accelerations during walking. Signals from the acceleration magnitude and the vertical acceleration are smoothed through different filters. Cut-off points between filtered signals as a result of convolving with varying levels of Gaussian filters and other robust features against temporal variation and noise are used to identify peaks that correspond to gait events. Five pre-frail older adults and five young healthy adults were recruited in an experiment. Cadence, step/stride time, step/stride CV, step asymmetry and percentages of the stance/swing and single/double support phases, among the two groups of different mobility were quantified by the system.

Comparison between passive vision-based system and a wearable inertial-based system for estimating temporal gait parameters related to the GAITRite electronic walkway.

Quantitative gait analysis allows clinicians to assess the inherent gait variability over time which is a functional marker to aid in the diagnosis of disabilities or diseases such as frailty, the onset of cognitive decline and neurodegenerative diseases, among others. However, despite the accuracy achieved by the current specialized systems there are constraints that limit quantitative gait analysis, for instance, the cost of the equipment, the limited access for many people and the lack of solutions to consistently monitor gait on a continuous basis. In this paper, two low-cost systems for quantitative gait analysis are presented, a wearable inertial system that relies on two wireless acceleration sensors mounted on the ankles; and a passive vision-based system that externally estimates the measurements through a structured light sensor and 3D point-cloud processing. Both systems are compared with a reference clinical instrument using an experimental protocol focused on the feasibility of estimating temporal gait parameters over two groups of healthy adults (five elders and five young subjects) under controlled conditions. The error of each system regarding the ground truth is computed. Inter-group and intra-group analyses are also conducted to transversely compare the performance between both technologies, and of these technologies with respect to the reference system. The comparison under controlled conditions is required as a previous stage towards the adaptation of both solutions to be incorporated into Ambient Assisted Living environments and to provide continuous in-home gait monitoring as part of the future work.

Mobile Monitoring Framework to Design Parameterized and Personalized m-Health Applications According to the Patient's Diseases.

The development of personalized mobile monitoring applications is a complex work. Currently, the most of applications for patients monitoring through mobile devices, is not developed considering the particular characteristics of each patient, but these applications have been developed taking into account a general behavior depending on the diseases instead of the own patients. The diseases manifest different symptoms depending on the patient situation. Mary and John (hypothetic patients) have diabetes, but the same measurement of glucose for each one affects their health in a different way. This paper describes a framework that allows the development of mobile applications, personalized for each patient, in such a way that even if they have the same disease, the application will respond to the individual needs of each patient.

Towards Context-Aware and User-Centered Analysis in Assistive Environments: A Methodology and a Software Tool.

One of the main challenges on Ambient Assisted Living (AAL) is to reach an appropriate acceptance level of the assistive systems, as well as to analyze and monitor end user tasks in a feasible and efficient way. The development and evaluation of AAL solutions based on user-centered perspective help to achive these goals. In this work, we have designed a methodology to integrate and develop analytics user-centered tools into assistive systems. An analysis software tool gathers information of end users from adapted psychological questionnaires and naturalistic observation of their own context. The aim is to enable an in-deep analysis focused on improving the life quality of elderly people and their caregivers.

An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles.

A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

An assistive navigation system based on augmented reality and context awareness for people with mild cognitive impairments.

This paper presents a system for supplying spatial orientation and support to cognitively impaired people in their daily activities. The system is a technological solution based on external aid at a practical level (substitution-based rehabilitation). In particular, we propose a model focused on points of interest or well-known places, in which user-friendly routes to a destination are generated based on the user context rather than the conventional street names and quantitative distances. Moreover, the system offers augmented reality views that include contextual information. This philosophy of navigation more closely matches the needs of the user than do conventional navigation systems; the proposal is especially useful for users who are not accustomed to using new technologies (e.g., elderly people), people experiencing disorientation and, more generally, individuals with a slight cognitive deficit. The system also includes an application that allows the relatives of the user to establish tasks that must be performed at a specific location and to monitor the activities of the user to detect potentially risky situations.

A mobile and ubiquitous approach for supporting frailty assessment in elderly people.

BACKGROUND: Frailty is a health condition related to aging and dependence. A reduction in or delay of the frailty state can improve the quality of life of the elderly. However, providing frailty assessments can be difficult because many factors must be taken into account. Usually, measurement of these factors is performed in a noncentralized manner. Additionally, the lack of quantitative methods for analysis makes it impossible for the diagnosis to be as complete or as objective as it should be. OBJECTIVE: To develop a centralized mobile system to conduct elderly frailty assessments in an accurate and objective way using mobile phone capabilities. METHODS: The diagnosis of frailty includes two fundamental aspects: the analysis of gait activity as the main predictor of functional disorders, and the study of a set of frailty risk factors from patient records. Thus, our system has several stages including gathering information about gait using accelerometer-enabled mobile devices, collecting values of frailty factors, performing analysis through similarity comparisons with previous data, and displaying the results for frailty on the mobile devices in a formalized way. RESULTS: We developed a general mechanism to assess the frailty state of a group of elders by using mobile devices as supporting tools. In collaboration with geriatricians, two studies were carried out on a group of 20 elderly patients (10 men and 10 women), previously selected from a nursing home. Frailty risk factors for each patient were collected at three different times over the period of a year. In the first study, data from the group of patients were used to determine the frailty state of a new incoming patient. The results were valuable for determining the degree of frailty of a specific patient in relation to other patients in an elderly population. The most representative similarity degrees were between 73.4% and 71.6% considering 61 frailty factors from 64 patient instances. Additionally, from the provided results, a physician could group the elders by their degree of similarity influencing their care and treatment. In the second study, the same mobile tool was used to analyze the frailty syndrome from a nutritional viewpoint on 10 patients of the initial group during 1 year. Data were acquired at three different times, corresponding to three assessments: initial, spontaneous, and after protein supplementation. The subsequent analysis revealed a general deterioration of the subset of elders from the initial assessment to the spontaneous assessment and also an improvement of biochemical and anthropometric parameters in men and women from the spontaneous assessment to the assessment after the administration of a protein supplement. CONCLUSIONS: The problem of creating a general frailty index is still unsolved. However, in recent years, there has been an increase in the amount of research on this subject. Our studies took advantage of mobile device features (accelerometer sensors, wireless communication capabilities, and processing capacities among others) to develop a new method that achieves an objective assessment of frailty based on similarity results for an elderly population, providing an essential support for physicians.

Mobile monitoring and reasoning methods to prevent cardiovascular diseases.

With the recent technological advances, it is possible to monitor vital signs using Bluetooth-enabled biometric mobile devices such as smartphones, tablets or electric wristbands. In this manuscript, we present a system to estimate the risk of cardiovascular diseases in Ambient Assisted Living environments. Cardiovascular disease risk is obtained from the monitoring of the blood pressure by means of mobile devices in combination with other clinical factors, and applying reasoning techniques based on the Systematic Coronary Risk Evaluation Project charts. We have developed an end-to-end software application for patients and physicians and a rule-based reasoning engine. We have also proposed a conceptual module to integrate recommendations to patients in their daily activities based on information proactively inferred through reasoning techniques and context-awareness. To evaluate the platform, we carried out usability experiments and performance benchmarks.