Synthetic 3D full-body skeletal motion from 2D paths using RNN with LSTM cells and linear networks.

Gait analysis has proven to be a key process in the functional assessment of people involving many fields, such as diagnosis of diseases or rehabilitation, and has increased in relevance lately. Gait analysis often requires gathering data, although this can be very expensive and time consuming. One of the main solutions applied in fields when data acquisition is a problem is augmentation of datasets with artificial data. There are two main approaches for doing that: simulation and synthetic data generation. In this article, we propose a parametrizable generative system of synthetic walking simplified human skeletons. For achieving that, a data gathering experiment with up to 26 individuals was conducted. The system consists of two artificial neural networks: a recurrent neural network for the generation of the movement and a multilayer perceptron for determining the size of the segments of the skeletons. The system has been evaluated through four processes: (i) an observational appraisal by researchers in gait analysis, (ii) a visual representation of the distribution of the generated data, (iii) a numerical analysis using the normalized cross-correlation coefficient, and (iv) an angular evaluation to check the kinematic validity of the data. The evaluation concluded that the system is able to generate realistic and accurate gait data. These results reveal a promising path for this research field, which can be further improved through increasing the variety of movements and the user sample.

Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries.

This paper aims to improve activity recognition systems based on skeletal tracking through the study of two different strategies (and its combination): (a) specialized body parts analysis and (b) stricter restrictions for the most easily detectable activities. The study was performed using the Extended Body-Angles Algorithm, which is able to analyze activities using only a single key sample. This system allows to select, for each considered activity, which are its relevant joints, which makes it possible to monitor the body of the user selecting only a subset of the same. But this feature of the system has both advantages and disadvantages. As a consequence, in the past we had some difficulties with the recognition of activities that only have a small subset of the joints of the body as relevant. The goal of this work, therefore, is to analyze the effect produced by the application of several strategies on the results of an activity recognition system based on skeletal tracking joint oriented devices. Strategies that we applied with the purpose of improve the recognition rates of the activities with a small subset of relevant joints. Through the results of this work, we aim to give the scientific community some first indications about which considered strategy is better.

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.

Assessing empathy and managing emotions through interactions with an affective avatar.

Assistive technologies can improve the quality of life of people diagnosed with different forms of social communication disorders. We report on the design and evaluation of an affective avatar aimed at engaging the user in a social interaction with the purpose of assisting in communication therapies. A human-avatar taxonomy is proposed to assist the design of affective avatars aimed at addressing social communication disorder. The avatar was evaluated with 30 subjects to assess how effectively it conveys the desired emotion and elicits empathy from the user. Results provide evidence that users become used to the avatar after a number of interactions, and they perceive the defined behavior as being logical. The users' interactions with the avatar entail affective reactions, including the mimic emotions that users felt, and establish a preliminary ground truth about prototypic empathic interactions with avatars that is being used to train learning algorithms to support social communication disorder evaluation.

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.

Correlation between videogame mechanics and executive functions through EEG analysis.

This paper addresses a different point of view of videogames, specifically serious games for health. This paper contributes to that area with a multidisciplinary perspective focus on neurosciences and computation. The experiment population has been pre-adolescents between the ages of 8 and 12 without any cognitive issues. The experiment consisted in users playing videogames as well as performing traditional psychological assessments; during these tasks the frontal brain activity was evaluated. The main goal was to analyse how the frontal lobe of the brain (executive function) works in terms of prominent cognitive skills during five types of game mechanics widely used in commercial videogames. The analysis was made by collecting brain signals during the two phases of the experiment, where the signals were analysed with an electroencephalogram neuroheadset. The validated hypotheses were whether videogames can develop executive functioning and if it was possible to identify which kind of cognitive skills are developed during each kind of typical videogame mechanic. The results contribute to the design of serious games for health purposes on a conceptual level, particularly in support of the diagnosis and treatment of cognitive-related pathologies.

A Systematic Review for Mobile Monitoring Solutions in M-Health.

A systematic review allows us to identify, assess, and interpret all possible relevant work associated with a question in particular or the subject of an area. Different authors can use several methodologies to learn about research related to their own research in different fields. The main objective of this review is to identify work, research and publications made in the field of the mobile monitoring of patients through some application or commercial or non-commercial solutions in m-Health. Next, we compare the different solutions with our solution, MoMo (Mobile Monitoring) Framework. MoMo is a solution that allows for patient mobile monitoring through mobile phones and biometric devices (blood pressure meter, glucometer and others). Our systematic review is based on the methodology of B. Kitchenham. She proposed specific guidelines for carrying out a systematic review in software engineering. We prepare our systematic review base in the selection of primary and secondary research related to mobile monitoring solutions following criteria with a specific weight to compare with each part of our research.

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.

Using a communication model to collect measurement data through mobile devices.

Wireless systems and services have undergone remarkable development since the first mobile phone system was introduced in the early 1980s. The use of sensors in an Ambient Intelligence approach is a great solution in a medical environment. We define a communication architecture to facilitate the information transfer between all connected devices. This model is based in layers to allow the collection of measurement data to be used in our framework monitoring architecture. An overlay-based solution is built between network elements in order to provide an efficient and highly functional communication platform that allows the connection of a wide variety of devices and technologies, and serves also to perform additional functions such as the possibility to perform some processing in the network that may help to improve overall performance.