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Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: The pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track the activities that people perform at home. Machine learning techniques can perform this task, but the software algorithms rely upon large amounts of sample data that is correctly labeled with the corresponding activity. Labeling, or annotating, sensor data with the corresponding activity can be time consuming, may require input from the smart home resident, and…is often inaccurate. Therefore, in this paper we investigate four alternative mechanisms for annotating sensor data with a corresponding activity label. We evaluate the alternative methods along the dimensions of annotation time, resident burden, and accuracy using sensor data collected in a real smart apartment.
Keywords: Activities of daily living, smart homes, activity recognition, health monitoring, machine learning, data annotation
Abstract: Smart Homes offer potential solutions for various forms of independent living for the elderly. The assistive and protective environment afforded by smart homes offer a safe, relatively inexpensive, dependable and viable alternative to vulnerable inhabitants. Nevertheless, the success of a smart home rests upon the quality of information its decision support system receives and this in turn places great importance on the issue of correct sensor deployment. In this article we present a software tool that has been developed to address the elusive issue of sensor distribution within smart homes. Details of the tool will be presented and it will…be shown how it can be used to emulate any real world environment whereby virtual sensor distributions can be rapidly implemented and assessed without the requirement for physical deployment for evaluation. As such, this approach offers the potential of tailoring sensor distributions to the specific needs of a patient in a non-evasive manner. The heuristics based tool presented here has been developed as the first part of a three stage project.
Abstract: To address an aging population, we have been investigating sensor networks for monitoring older adults in their homes. In this paper, we report ongoing work in which passive sensor networks have been installed in 17 apartments in an aging in place eldercare facility. The network under development includes simple motion sensors, video sensors, and a bed sensor that captures sleep restlessness and pulse and respiration levels. Data collection has been ongoing for over two years in some apartments. This longevity in sensor data collection is allowing us to study the data and develop algorithms for identifying alert conditions such as…falls, as well as extracting typical daily activity patterns for an individual. The goal is to capture patterns representing physical and cognitive health conditions and then recognize when activity patterns begin to deviate from the norm. In doing so, we strive to provide early detection of potential problems which may lead to serious health events if left unattended. We describe the components of the network and show examples of logged sensor data with correlated references to health events. A summary is also included on the challenges encountered and the lessons learned as a result of our experiences in monitoring aging adults in their homes.
Keywords: Sensor networks, passive monitoring, eldercare technology, video sensor network, smart home
Abstract: This paper outlines an approach that we are taking for elder-care applications in the smart home, involving cognitive errors and their compensation. Our approach involves high level modeling of daily activities of the elderly by breaking down these activities into smaller units, which can then be automatically recognized at a low level by collections of sensors placed in the homes of the elderly. This separation allows us to employ plan recognition algorithms and systems at a high level, while developing stand-alone activity recognition algorithms and systems at a low level. It also allows the mixing and matching of multi-modality sensors…of various kinds that go to support the same high level requirement. Currently our plan recognition algorithms are still at a conceptual stage, whereas a number of low level activity recognition algorithms and systems have been developed. Herein we present our model for plan recognition, providing a brief survey of the background literature. We also present some concrete results that we have achieved for activity recognition, emphasizing how these results are incorporated into the overall plan recognition system.
Keywords: Cognitive error, plan recognition, information quality, sensor network, activity recognition, monitoring of elderly
Abstract: With the obvious eldercare capabilities of smart environments it is a question of “when”, rather than “if”, these technologies will be routinely integrated into the design of future houses. In the meantime, health monitoring applications must be integrated into already complete home environments. However, there is significant effort involved in installing the hardware necessary to monitor the movements of an elder throughout an environment. Our work seeks to address the high infrastructure requirements of traditional location-based smart home systems by developing an extremely low infrastructure localisation technique. A study of the most efficient method of obtaining calibration data for an…environment is conducted and different mobile devices are compared for localisation accuracy and cost trade-off. It is believed that these developments will contribute towards more efficiently deployed location-based smart home systems.
Abstract: Topographical Disorientation (TD) is the lack or loss of orientation and navigation abilities. People living with TD face functional challenges in everyday situations. Smart mediated reality environments present potential solutions for cognitive conditions like TD. In this article, we introduce a novel mediated reality location aware environment. It was hypothesized that tools which offer different positional information affect the navigation performance of a user. The objective of this study was to investigate preferred assistive tools for indoor navigation for use in a proposed mediated reality wayfinding system. These tools may eventually be used to assist patients with TD.…To this purpose, we designed a novel wayfinding metric that can be used in the assessment of navigation tasks similar to a scavenger hunt. This novel metric is based on a relative energy expenditure ratio and is independent of navigation route complexity. We investigated four sets of tools (minimap, locator, coordinate display and routing compass) that can be used in a smart mediated reality environment to provide relevant wayfinding information. These tools were designed using different combinations of spatial knowledge (landmark, route or survey), graphical presentation (compass, text, icon, top/side view) and reference frames (egocentric or allocentric). Each tool was evaluated objectively and subjectively. The locator and minimap tools emerged as preferred interfaces, providing the most relevant wayfinding information while minimizing energy expenditure during navigation tasks.
Abstract: In accordance with the global trend, in The Netherlands approximately 45% of the population is overweight. Existing studies show that patient self-management can reduce these figures, but medical non-adherence is a persistent problem. eHealth can potentially increase adherence to self-management. Consequently, we designed a persuasive computer assistant and evaluated its influence on self-management, i.e., the use of an online lifestyle diary called DieetInzicht.nl. The assistant is represented by an animated iCat, which shows different facial expressions and provides cooperative feedback following principles from the motivational interviewing method. We conducted a randomized controlled trial with 118 overweight people over a period…of four weeks and studied the difference between diary use with and without computer assistant feedback. Results show that the computer assistant contributed to filling in the diary more frequently, reduced the decline in motivation to perform self-management, lowered the (reported) BMI, and improved the ease of use. Furthermore, diary use increased knowledge of maintaining a healthy lifestyle. Finally, personal characteristics, i.e., locus of control, vocabulary, computer experience, age, gender, education level and initial BMI, explained the variance in the diary use and its outcome. Of the 118 participants 35 filled in the closing survey, covering motivation, BMI, lifestyle knowledge and ease of use, which implies that the findings based on these results are mainly representative for motivated participants. In general, this study shows that the Dieetinzicht eHealth service, including a personal computer assistant, is likely to support motivated overweight people and lifestyle related diseases to get a better insight in and adhere to their self-management.
Abstract: The population is aging and with this, the incidence of age related diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) are increasing. Assistive Technology (AT) is viewed as one of the possible solutions which can be used to meet the needs of persons suffering from PD. AT can enable a person to carry out a task which otherwise they would be unable to undertake independently. An AT can have many functions which range from helping people to use a computer, to monitoring someone's condition. Within this paper we attempt to categorise the different types of AT for persons…with PD. Each of the technologies will be compared and contrasted and an overview of what is currently available presented. The paper concludes with some visionary comments on how the current levels of AT may change in the future.
Keywords: Assistive technology, Parkinson's disease, mobile phone, personal computer, touch screen device