Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

The Efficacy of Biofeedback and Its Use Towards ADHD

Attention deficit hyperactivity disorder (ADHD) is a psychopathology commonly characterized by general inattentiveness and/or a lack of impulse control resulting in hyperactive tendencies. ADHD is estimated to cost the United States roughly $266 billion every year. ADHD is currently treated via medications, cognitive behavioral therapy, or more recently, neurofeedback. Neurofeedback – and biofeedback in general – is the process of providing a patient with information about autonomic bodily functions so that they may control said autonomic function. In the case of ADHD, neurofeedback focuses on reinforcing the behaviors and sensations associated with attentiveness. Currently however, neurofeedback systems are large and require a patient to travel to a clinic. Furthermore, the current offering of portable neuro/biofeedback devices do not have the technological capabilities to provide effective neurofeedback therapy. Current wearable tech devices – such as the Apple Watch and Samsung Gear – possess the technological capabilities to measure important bodily functions, and provide appropriate biofeedback therapy while remaining discrete and most importantly, portable

Ambulatory assessment in neuropsychology : applications in multiple sclerosis research

Peer reviewedPostprin

Information system for monitoring and assessing stress among medical students

Author ProofThe severe or prolonged exposure to stress-inducing factors in occupational and academic settings is a growing concern. The literature describes several potentially stressful moments experienced by medical students throughout the course, affecting cognitive functioning and learning. In this paper, we introduce the EUSTRESS Solution, that aims to create an Information System to monitor and assess, continuously and in real-time, the stress levels of the individuals in order to predict chronic stress. The Information System will use a measuring instrument based on wearable devices and machine learning techniques to collect and process stress-related data from the individual without his/her explicit interaction. A big database has been built through physiological, psychological, and behavioral assessments of medical students. In this paper, we focus on heart rate and heart rate variability indices, by comparing baseline and stress condition. In order to develop a predictive model of stress, we performed different statistical tests. Preliminary results showed the neural network had the better model fit. As future work, we will integrate salivary samples and self-report questionnaires in order to develop a more complex and intelligent model.QVida+ project (Estimação Contínua de Qualidade de Vida para Auxílio Eficaz à Decisão Clínica), funded by European Structural funds (FEDER-003446), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement

Rim-to-Rim Wearables at the Canyon for Health (R2R WATCH): Physiological, Cognitive, and Biological Markers of Performance Decline in an Extreme Environment

Success in extreme environments comes with a cost of subtle performance decrements that if not mitigated properly can lead to lifethreatening consequences. Identification and prediction of performance decline could alleviate deleterious consequences and enhance success in challenging and high-risk operations. The Rim-to-Rim Wearables at the Canyon for Health (R2R WATCH) project was designed to examine the cognitive, physiological, and biological markers of performance decline in the extreme environment of the Grand Canyon Rim-to-Rim (R2R) hike. The study utilized commercial off-the-shelf cognitive and physiological monitoring techniques, along with subjective self-assessments and hematologic measurements to determine subject performance and changes across the hike. The multiyear effort collected these multiple data streams in parallel on a large sample of participants hiking the R2R, leading to a rich and complex data set. This article describes the methodology and its evolution as devices and measurements were assessed after each data collection event. It also highlights a subset of the patterns of results found across the data streams. Subsequent work will draw on this data set to focus on building more sophisticated, predictive statistical models and dive deeper into specific analyses (such as the physiological and biological profiles of hikers who were left behind by their hiking partners)

Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Developing Digital Tools for Remote Clinical Research:How to Evaluate the Validity and Practicality of Active Assessments in Field Settings

The ability of remote research tools to collect granular, high-frequency data on symptoms and digital biomarkers is an important strength because it circumvents many limitations of traditional clinical trials and improves the ability to capture clinically relevant data. This approach allows researchers to capture more robust baselines and derive novel phenotypes for improved precision in diagnosis and accuracy in outcomes. The process for developing these tools however is complex because data need to be collected at a frequency that is meaningful but not burdensome for the participant or patient. Furthermore, traditional techniques, which rely on fixed conditions to validate assessments, may be inappropriate for validating tools that are designed to capture data under flexible conditions. This paper discusses the process for determining whether a digital assessment is suitable for remote research and offers suggestions on how to validate these novel tools

IoT-Based Applications in Healthcare Devices

The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic

Emotional self-regulation of individuals with autism spectrum disorders: smartwatches for monitoring and interaction

In this paper, we analyze the needs of individuals with Autism Spectrum Disorders (ASD) to have a pervasive, feasible and non-stigmatizing form of assistance in their emotional self-regulation, in order to ease certain behavioral issues that undermine their mental health throughout their life. We argue the potential of recent widespread wearables, and more specifically smartwatches, to achieve this goal. Then, a smartwatch system that implements a wide range of self-regulation strategies and infers outburst patterns from physiological signals and movement is presented, along with an authoring tool for smartphones that is to be used by caregivers or family members to create and edit these strategies, in an adaptive way. We conducted an intensive experiment with two individuals with ASD who showed varied, representative behavioral responses to their emotional dysregulation. Both users were able to employ effective, customized emotional self-regulation strategies by means of the system, recovering from the majority of mild stress episodes and temper tantrums experienced in the nine days of experiment in their classroomThis work has been partially funded by the projects “e-Training y e-Coaching para la integración socio—laboral” (TIN2013-44586-R) and “eMadrid-CM: Investigación y Desarrollo de Tecnologías Educativas en la Comunidad de Madrid” (S2013/ICE-2715). It has been also funded by Fundación Orange during the early stages of the project “Tic-Tac-TEA: Sistema de asistencia para la autorregulación emocional en momentos de crisis para personas con TEA mediante smartwatches