Miguel A. Estudillo-Valderrama

Design and Implementation of a Distributed Fall Detection System—Personal Server

In this paper, the main results related to a fall detection system are shown by means of a personal server for the control and processing of the data acquired from multiple intelligent biomedical sensors. This server is designed in the context of a telehealthcare system for the elderly, to whom falls represent a high-risk cause of serious injuries, and its architecture can be extended to patients suffering from chronic diseases. The main design issues and developments in terms of the server hardware and software are presented with the aim of providing a real-time analysis of the processed biosignals. As a result, the evaluation study of the implemented algorithm for fall detection through a set of laboratory experiments is presented, together with some important issues in terms of the devices consumption. The proposed algorithm exhibits excellent outcomes in fall detection.

SoM: A Smart Sensor for Human Activity Monitoring and Assisted Healthy Ageing

This paper presents the hardware and software design and implementation of a low-cost, wearable, and unobstructive intelligent accelerometer sensor for the monitoring of human physical activities. In order to promote healthy lifestyles to elders for an active, independent, and healthy ageing, as well as for the early detection of psychomotor abnormalities, the activity monitoring is performed in a holistic manner in the same device through different approaches: 1) a classification of the level of activity that allows to establish patterns of behavior; 2) a daily activity living classifier that is able to distinguish activities such as climbing or descending stairs using a simple method to decouple the gravitational acceleration components of the motion components; and 3) an estimation of metabolic expenditure independent of the activity performed and the anthropometric characteristics of the user. Experimental results have demonstrated the feasibility of the prototype and the proposed algorithms.

Ambient Assisted Living: A methodological approach

In this paper, the most important challenges and trends related to the application of Ambient Assisted Living (AAL) methods and techniques to the social/healthcare context are discussed. In order to find out technical solutions to these challenges, the main methodological issues concerning the design of open and distributed architectures are analyzed. The objective is to improve the efficiency/cost ratio in the provision of social and healthcare services to citizens with special needs, through the application of new paradigms in the context of AAL environments. Finally, some results and conclusions regarding the proposed open architecture are illustrated for the case of a distributed biomedical sensor network designed by the authors following this methodology.

A Machine-to-Machine protocol benchmark for eHealth applications - Use case

BACKGROUND M2M (Machine-to-Machine) communications represent one of the main pillars of the new paradigm of the Internet of Things (IoT), and is making possible new opportunities for the eHealth business. Nevertheless, the large number of M2M protocols currently available hinders the election of a suitable solution that satisfies the requirements that can demand eHealth applications. OBJECTIVES In the first place, to develop a tool that provides a benchmarking analysis in order to objectively select among the most relevant M2M protocols for eHealth solutions. In the second place, to validate the tool with a particular use case: the respiratory rehabilitation. METHODS A software tool, called Distributed Computing Framework (DFC), has been designed and developed to execute the benchmarking tests and facilitate the deployment in environments with a large number of machines, with independence of the protocol and performance metrics selected. RESULTS DDS, MQTT, CoAP, JMS, AMQP and XMPP protocols were evaluated considering different specific performance metrics, including CPU usage, memory usage, bandwidth consumption, latency and jitter. The results obtained allowed to validate a case of use: respiratory rehabilitation of chronic obstructive pulmonary disease (COPD) patients in two scenarios with different types of requirement: Home-Based and Ambulatory. CONCLUSIONS The results of the benchmark comparison can guide eHealth developers in the choice of M2M technologies. In this regard, the framework presented is a simple and powerful tool for the deployment of benchmark tests under specific environments and conditions.

A proposal of a fall detection algorithm for a Multidevice Personal Intelligent Platform

In this paper methodological and design issues about the development of a personal platform for the control and processing of data acquired from intelligent biomedical sensors are presented. This platform is designed in the context of a telehealthcare system for the elderly with chronic diseases, and one of its objectives is to monitor and detect fall events. The main feature of the device is its on-line personalization to the patient through adaptive knowledge generation in real-time, which will result in special time execution requirements. As a result a fall detection algorithm proposal is described and analyzed.

Distributed processing methodology for biomedical sensor networks: An optimal approach

In this paper, the major advantages of a distributed processing methodology developed in the context of biomedical sensor networks (BSN) are compared to the most usual wireless communication topology architectures developed in the literature. These advantages are highlighted in the context of a distributed fall detection system developed by the authors in terms of more facilities for system personalization to the end user and multimodal functionality in order to extend the biomedical application domain of the system. As the main result, a lower power consumption of the devices pertaining to the system is shown.

Low-Power platform and communications for the development of wireless body sensor networks

Although the roles of body sensor networks (BSNs) are similar to those carried out by the generic wireless sensor networks (WSNs), new solutions must be established to optimize communications for true pervasive biomedical monitoring transparent to the user. In this paper, a proposal of a hardware and software platform for biomedical sensors is performed, which is specially designed to minimize energy consumption in BSNs through a modular processing scheme based on the detection of events and information abstraction. The data flow is implemented through a novel communications protocol that enhances the performances of consumption and time delay of the platform. A novel aspect of the protocol is the explicit incorporation of an additional level of communications to support the distributed processing architecture that allows the execution of multiple applications in parallel within the smart sensors. The results obtained with an implementation of a smart sensor for fall detection demonstrate its feasibility as well as the viability of the communication protocol for the development of energy-efficient BSNs.

A Distributed Approach to Alarm Management in Chronic Kidney Disease

This paper presents the feasibility study of using a distributed approach for the management of alarms from chronic kidney disease patients. In a first place, the key issues regarding alarm definition, classification, and prioritization according to available normalization efforts are analyzed for the main scenarios addressed in hemodialysis. Then, the middleware proposed for alarm management is described, which follows the publish/subscribe pattern, and supports the Object Management Group data distribution service (DDS) standard. This standard facilitates the real-time monitoring of the exchanged information, as well as the scalability and interoperability of the solution developed regarding the different stakeholders and resources involved. Finally, the results section shows, through the proof of concept studied, the viability of DDS for the activation of emergency protocols in terms of alarm prioritization and personalization, as well as some remarks about security, privacy, and real-time communication performance.

A Distributed Middleware for the Assistance on the Prevention of Peritonitis in CKD

This paper presents the feasibility study of using a distributed middleware for the management of infections from Chronic Kidney Disease (CKD) patients. The middleware follows the publish-subscribe pattern, and supports the OMG DDS (Data Distribution Service) standard, which facilitates the real-time monitoring of the distributed information, as well as the scalability and interoperability of the solution developed regarding the different stakeholders and resources involved. The proof of concept studied shows DDS viability for the activation of emergency protocols in real-time to manage alarms among the stakeholders subscribed to the information published by the infection detection system at patient’s home.

Remote Programming of Biomedical Smart Sensors

This paper proposes a processing architecture and a programming framework for the remote and seamless update of the algorithms used in the context of biomedical smart sensors. The generic processing architecture provides, among others, the following facilities to a Body Sensor Network in a seamless way to the user beyond functional modularity: 1) direct and immediate update with new and improved versions of the algorithms, 2) personalization of algorithms, 3) adaptability to the user context, 4) remote test of algorithms, 5) hardware reusability and sustainability, 6) parallel execution of several monitoring applications in one device, 7) structural modularity. Due to its simplicity, the proposed technique takes advantage over other solutions employed in applications that impose severe limitations on hardware/software resources of the devices, which may result in lower cost and size of them. The results obtained on two heart monitoring applications shows the viability of the proposed scheme.