European Resuscitation Council Guidelines for Resuscitation.

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An Introduction To The Event Related Potential Technique

THE JOURNAL OF BIOLOGICAL CHEMISTRY: The Biochemical Behavior of LeadL I. Influence of Calcium, Phosphorus, and Vitamin D on Lead in Blood and Bone

In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of `ambient-assisted living” (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges.

A Survey on Ambient-Assisted Living Tools for Older Adults

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive, and anticipatory communications. Such innovative interaction paradigms make AmI technology a suitable candidate for developing various real life solutions, including in the healthcare domain. This survey will discuss the emergence of AmI techniques in the healthcare domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of AmI, such as smart environments and wearable medical devices. We will summarize the state-of-the-art artificial intelligence (AI) methodologies used for developing AmI system in the healthcare domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions), and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.

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A Survey on Ambient Intelligence in Healthcare

Since the Topic Map standard describes a prospective knowledge-structuring model that can be used in a huge variety of knowledge domains the amount of applications utilizing this standard grew enormously. Anyhow, as far as we know, there is no distributed editor of Topic Maps available on the market, that supports an intuitive possibility to manipulate or visualize Topic Maps in the World Wide Web environment. Therefore, TMNet intends to close this gap. As a result, a high performing distributed editor is achieved, with which web-based e-learning environments as well as knowledge environments can be enhanced by supporting semantic data descriptions of their knowledge structure. Additionally TMNet enables the user to extend the structures in an easy way and gives the web developer an opportunity to integrate it into websites easily.

TMNet - Distributed viewing and editing of Topic Maps in the World Wide Web Environment

Functional near-infrared spectroscopy (fNIRS) is an optical non-invasive neuroimaging technique that allows participants to move relatively freely. However, head movements frequently cause optode movements relative to the head, leading to motion artifacts (MA) in the measured signal. Here, we propose an improved algorithmic approach for MA correction that combines wavelet and correlation-based signal improvement (WCBSI). We compare its MA correction accuracy to multiple established correction approaches (spline interpolation, spline-Savitzky–Golay filter, principal component analysis, targeted principal component analysis, robust locally weighted regression smoothing filter, wavelet filter, and correlation-based signal improvement) on real data. Therefore, we measured brain activity in 20 participants performing a hand-tapping task and simultaneously moving their head to produce MAs at different levels of severity. In order to obtain a “ground truth” brain activation, we added a condition in which only the tapping task was performed. We compared the MA correction performance among the algorithms on four predefined metrics (R, RMSE, MAPE, and ΔAUC) and ranked the performances. The suggested WCBSI algorithm was the only one exceeding average performance (p < 0.001), and it had the highest probability to be the best ranked algorithm (78.8% probability). Together, our results indicate that among all algorithms tested, our suggested WCBSI approach performed consistently favorably across all measures.

/pdf/improved-motion-artifact-correction-in-fnirs-data-by-3vilv5vq.pdf

Improved Motion Artifact Correction in fNIRS Data by Combining Wavelet and Correlation-Based Signal Improvement

Almost all Western societies are facing the challenge that their population structure is changing very dynamically. Already in 2019, ten countries had a population share of at least 20 percent in the age group of 64 years and older. Today's society aims to improve population health and help older people live active and independent lives by developing, establishing, and promoting safe and effective interventions. Modern technological approaches offer tremendous opportunities but pose challenges when preventing functional decline. As part of the AEQUIPA Prevention Research Network, the use of technology to promote physical activity in older people over 65 years of age was investigated in different settings and from various interdisciplinary perspectives, including technology development and evaluation for older adults. We present our findings in three main areas: (a) design processes for developing technology interventions, (b) older adults as a user group, and (c) implications for the use of technology in interventions. We find that cross-cutting issues such as time and project management, supervision of participants, ethics, and interdisciplinary collaboration are of vital importance to the success of the work. The lessons learned are discussed based on the experiences gained in the overall AEQUIPA network while building, particularly on the experiences from the AEQUIPA sub-projects TECHNOLOGY and PROMOTE. Our experiences can help researchers of all disciplines, industries, and practices design, study and implement novel technology-based interventions for older adults to avoid pitfalls and create compelling and meaningful solutions.

/pdf/designing-and-applying-technology-for-prevention-lessons-1e94ewg9.pdf

Designing and applying technology for prevention—Lessons learned in AEQUIPA and its implications for future research and practice

BACKGROUND
Although digital approaches for disease prevention in older people have a high potential and are being used more often, there are still inequalities in access and use. One reason could be that in technology development future users are insufficiently taken into consideration, or involved very late in the process using inappropriate methods. The aim of this work was to analyze the motivation of older people participating, and their perceptions of future participation in the research and development process of health technologies aimed at health care for older people.


METHODOLOGY
Quantitative and qualitative data from one needs assessment and two evaluation studies were analyzed. The quantitative data were analyzed descriptively and the qualitative data were analyzed content-analytically with inductive-deductive category formation.


RESULTS
The median age of the 103 participants (50 female) was 75 years (64-90), most of whom were interested in using technology and had prior experience of study participation. Nine categories for participation motivation were derived. A common motivation for participation was to promote and support their own health. Respondents were able to envision participation both at the beginning of the research process and at its end. In terms of technique development, different ideas were expressed, but there was a general interest in technological development. Methods that would enable exchange with others were favored most.


CONCLUSIONS
Differences in motivation to participate and ideas about participation were identified. The results provide important information from the perspective of older people and complement the existing state of research.

[Motivational Reasons and Perceptions about Future Participation of Older People in the Research and Development Process of Health Technologies: a Mixed Methods Study].

Cardiopulmonary resuscitation (CPR) is the most important emergency intervention for sudden cardiac arrest. In this paper, a robust sinusoidal model fitting method based on a modified Genetic Algorithm for CPR quality parameters - naming chest compression frequency and depth - as measured by an inertial sensor placed at the wrist is presented. Once included into a smartphone or smartwatch app, the proposed algorithm will enable bystanders to improve CPR (as part of a continuous closed-loop support-system). By evaluating the precision of the model with both, simulated data and data recorded by a Laerdal Resusci Anne mannequin as reference standard, a variance for compression frequency of +-3.7 cpm has been found for the sensor placed at the wrist. Thereby, this previously unconsidered position and consequently the use of smartwatches was shown to be a suitable alternative to the typical placement of phones in the hand for CPR training.

Sebastian Fudickar

Papers

TMNet - Distributed viewing and editing of Topic Maps in the World Wide Web Environment

Improved Motion Artifact Correction in fNIRS Data by Combining Wavelet and Correlation-Based Signal Improvement

Designing and applying technology for prevention—Lessons learned in AEQUIPA and its implications for future research and practice

[Motivational Reasons and Perceptions about Future Participation of Older People in the Research and Development Process of Health Technologies: a Mixed Methods Study].

A modified Genetic Algorithm for continuous estimation of CPR quality parameters from wrist-worn inertial sensor data.