Technology in health and social care: a critical reflection from across two continents

An ageing population, with pressure on health care and social care capacity, is driving demand for innovative solutions to support independence at home. Digital technologies have been proposed as a way to respond to these challenges, and as a consequence, the delivery of care is being transformed. However, in spite of technology being positioned as a panacea to meet the current challenges facing health and social care, a lack of critical discourse around technology use in this context is of concern. Issues regarding user acceptance, role of care technology and setting realistic expectations on what technology can contribute to these challenges have yet to be addressed

Dictionary memory based software architecture for distributed bluetooth low energy host controllers enabling high coverage in consumer residential healthcare environments

Technology has been seen as a possible solution to the increasing costs of healthcare and the globally aging population. It is known that many elderly people prefer to stay in their homes for as long as possible and remote monitoring can be a solution, but often such systems lack useful information or are prohibitive due to cost, ease of use/deployment and wireless coverage. This work presents a novel gateway software architecture based on threads being managed by dictionary memory. The architecture has been deployed in a distributed interconnected set of low-cost consumer grade gateway devices using Bluetooth Low Energy (BLE) that are positioned around the home. The gateway devices can then be used to listen, monitor or connect to BLE based healthcare sensors to continually reveal information about the user with full residential coverage. A further novelty of this work is the ability to maintain handover connections between many sensors and many gateways as a user moves throughout their home, thus the gateways can route information to/from sensors across the consumer’s home network. The system has been tested in an experimental house and is now poised to be initially deployed to 100 homes for residential healthcare monitoring before any public mass consumer deployment

An intelligent information forwarder for healthcare big data systems with distributed wearable sensors

© 2016 IEEE. An increasing number of the elderly population wish to live an independent lifestyle, rather than rely on intrusive care programmes. A big data solution is presented using wearable sensors capable of carrying out continuous monitoring of the elderly, alerting the relevant caregivers when necessary and forwarding pertinent information to a big data system for analysis. A challenge for such a solution is the development of context-awareness through the multidimensional, dynamic and nonlinear sensor readings that have a weak correlation with observable human behaviours and health conditions. To address this challenge, a wearable sensor system with an intelligent data forwarder is discussed in this paper. The forwarder adopts a Hidden Markov Model for human behaviour recognition. Locality sensitive hashing is proposed as an efficient mechanism to learn sensor patterns. A prototype solution is implemented to monitor health conditions of dispersed users. It is shown that the intelligent forwarders can provide the remote sensors with context-awareness. They transmit only important information to the big data server for analytics when certain behaviours happen and avoid overwhelming communication and data storage. The system functions unobtrusively, whilst giving the users peace of mind in the knowledge that their safety is being monitored and analysed

Review of state-of-the-art wireless technologies and applications in smart cities

There are increasing preferences to employ wireless communication technologies for high mobility, high scalability and low-cost applications in smart city development. This paper gives a brief synopsis of typical wireless technologies in smart city applications and the comparison analysis between them. The trend for smart city wireless technology is also presented. Examples, for several key applications within smart city development (healthcare, smart grid, localization) are studied and current advanced solutions supporting these applications are summarized with futuristic trends and demands are presented

An experimental study of ZigBee for body sensor networks

We present an experimental performance evaluation of ZigBee networks in the context of data-intensive body sensor networks (BSNs). IEEE 802.15.4/ZigBee devices were mainly developed for use in wireless sensors network (WSN) applications; however, due to characteristics such as low power and small form factor, they are also being widely used in BSN applications, making it necessary to evaluate their suitability in this context. The delivery ratio and end-to-end delay were evaluated, under contention, for both star and tree topologies. The reliability of the ZigBee network in a star topology without hidden nodes was very good (delivery ratio close to 100%), provided the acknowledgement mechanism was enabled. On the other hand, the performance in a tree topology was degraded due to router overload and the activation of the route maintenance protocol triggered by periods of high traffic load. The effect of the devices’ clock drift and hidden nodes on the reliability of the star network was modeled and validated through experimental tests. In these tests, the worst-case delivery ratio when the acknowledgment is used decreased to 90% with two sensor nodes, while for the non-acknowledged mode the result was of 13%. These results show that a mechanism for distributing the nodes’ traffic over the time is required to avoid BSN performance degradation caused by router overload, clock drift and hidden node issues.Fundação para a Ciência e Tecnologi

Proactive Highly Ambulatory Sensor Routing (PHASeR) protocol for mobile wireless sensor networks

This paper presents a novel multihop routing protocol for mobile wireless sensor networks called PHASeR (Proactive Highly Ambulatory Sensor Routing). The proposed protocol uses a simple hop-count metric to enable the dynamic and robust routing of data towards the sink in mobile environments. It is motivated by the application of radiation mapping by unmanned vehicles, which requires the reliable and timely delivery of regular measurements to the sink. PHASeR maintains a gradient metric in mobile environments by using a global TDMA MAC layer. It also uses the technique of blind forwarding to pass messages through the network in a multipath manner. PHASeR is analysed mathematically based on packet delivery ratio, average packet delay, throughput and overhead. It is then simulated with varying mobility, scalability and traffic loads. The protocol gives good results over all measures, which suggests that it may also be suitable for a wider array of emerging applications

An enhanced fall detection system for elderly person monitoring using consumer home networks

Various fall-detection solutions have been previously proposed to create a reliable surveillance system for elderly people with high requirements on accuracy, sensitivity and specificity. In this paper, an enhanced fall detection system is proposed for elderly person monitoring that is based on smart sensors worn on the body and operating through consumer home networks. With treble thresholds, accidental falls can be detected in the home healthcare environment. By utilizing information gathered from an accelerometer, cardiotachometer and smart sensors, the impacts of falls can be logged and distinguished from normal daily activities. The proposed system has been deployed in a prototype system as detailed in this paper. From a test group of 30 healthy participants, it was found that the proposed fall detection system can achieve a high detection accuracy of 97.5%, while the sensitivity and specificity are 96.8% and 98.1% respectively. Therefore, this system can reliably be developed and deployed into a consumer product for use as an elderly person monitoring device with high accuracy and a low false positive rate

Mobile clinical decision support systems and applications: a literature and commercial review

The final publication is available at Springer via http://dx.doi.org/10.1007/s10916-013-0004-y[EN] Background: The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. Objective: The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Methods: Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Results: 92 relevant papers and 192 commercial apps were found. 44 papers were focused only on mobile clinical decision support systems. 171 apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. Conclusions: The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.This research has been partially supported by Ministerio de Economía y Competitividad, Spain. This research has been partially supported by the ICT-248765 EU-FP7 Project. 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Developing residential wireless sensor networks for ECG healthcare monitoring

Wireless technology development has increased rapidly due to it’s convenience and cost effectiveness compared to wired applications, particularly considering the advantages offered by Wireless Sensor Network (WSN) based applications. Such applications exist in several domains including healthcare, medical, industrial and home automation. In the present study, a home-based wireless ECG monitoring system using Zigbee technology is considered. Such systems can be useful for monitoring people in their own home as well as for periodic monitoring by physicians for appropriate healthcare, allowing people to live in their home for longer. Health monitoring systems can continuously monitor many physiological signals and offer further analysis and interpretation. The characteristics and drawbacks of these systems may affect the wearer’s mobility during monitoring the vital signs. Real-time monitoring systems record, measure, and monitor the heart electrical activity while maintaining the consumer’s comfort. Zigbee devices can offer low-power, small size, and a low-cost suitable solution for monitoring the ECG signal in the home, but such systems are often designed in isolation, with no consideration of existing home control networks and smart home solutions. The present study offers a state of the art review and then introduces the main concepts and contents of the wireless ECG monitoring systems. In addition, models of the ECG signal and the power consumption formulas are highlighted. Challenges and future perspectives are also reported. The paper concludes that such mass-market health monitoring systems will only be prevalent when implemented together with home environmental monitoring and control systems