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.

Elderly people become weak until they reach a state of frailty. At this time, their health begins to get worse and they are more likely to suffer bone fractures, disorders, and diseases, and they become dependent. Delaying or reducing frailty level is important to improve the quality of life of elderly people. There are many parameters to consider for frailty detection and diagnosis. In this sense, assessment of physical condition, through gait and other physical exercises, is the most important domain in frailty evaluation. Nowadays, geriatricians and physiotherapists use several tests and scales based on indicators to provide scores related to physical assessment. However, these scores depend on the viewpoint of the geriatrician. So, the assessment contains a level of subjectivity. Besides, frailty detection includes the study of other indicators from nutritional, cognitive, and social domains. In this paper, we propose a system to support physicians determining an accurate and centralized elderly frailty diagnosis, by using an accelerometer-enabled mobile phone. The accelerometer collects data movement from physical activity and calculates a set of measures that are combined with clinical indicators (from tests and medical instruments) providing a frailty assessment to facilitate decision-making and the subsequent treatment.

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.

This manuscript presents an infrastructure that contributes to ubiquitous information. Advances in Ambient Intelligence may help to provide us with t

A Mobile and Ubiquitous Approach for Supporting Frailty Assessment in Elderly People