Rehabilitative devices for a top-down approach

In recent years, neurorehabilitation has moved from a "bottom-up" to a "top down" approach. This change has also involved the technological devices developed for motor and cognitive rehabilitation. It implies that during a task or during therapeutic exercises, new "top-down" approaches are being used to stimulate the brain in a more direct way to elicit plasticity-mediated motor re-learning. This is opposed to "Bottom up" approaches, which act at the physical level and attempt to bring about changes at the level of the central neural system. Areas covered: In the present unsystematic review, we present the most promising innovative technological devices that can effectively support rehabilitation based on a top-down approach, according to the most recent neuroscientific and neurocognitive findings. In particular, we explore if and how the use of new technological devices comprising serious exergames, virtual reality, robots, brain computer interfaces, rhythmic music and biofeedback devices might provide a top-down based approach. Expert commentary: Motor and cognitive systems are strongly harnessed in humans and thus cannot be separated in neurorehabilitation. Recently developed technologies in motor-cognitive rehabilitation might have a greater positive effect than conventional therapies

Immersive Composition for Sensory Rehabilitation: 3D Visualisation, Surround Sound, and Synthesised Music to Provoke Catharsis and Healing

There is a wide range of sensory therapies using sound, music and visual stimuli. Some focus on soothing or distracting stimuli such as natural sounds or classical music as analgesic, while other approaches emphasize the active performance of producing music as therapy. This paper proposes an immersive multi-sensory Exposure Therapy for people suffering from anxiety disorders, based on a rich, detailed surround-soundscape. This soundscape is composed to include the users’ own idiosyncratic anxiety triggers as a form of habituation, and to provoke psychological catharsis, as a non-verbal, visceral and enveloping exposure. To accurately pinpoint the most effective sounds and to optimally compose the soundscape we will monitor the participants’ physiological responses such as electroencephalography, respiration, electromyography, and heart rate during exposure. We hypothesize that such physiologically optimized sensory landscapes will aid the development of future immersive therapies for various psychological conditions, Sound is a major trigger of anxiety, and auditory hypersensitivity is an extremely problematic symptom. Exposure to stress-inducing sounds can free anxiety sufferers from entrenched avoidance behaviors, teaching physiological coping strategies and encouraging resolution of the psychological issues agitated by the sound

Exploring Effects of Background Music in A Serious Game on Attention by Means of EEG Signals in Children

Music and Serious Games are separately useful alternative therapy methods for helping people with a cognitive disorder, including Attention Deficit Hyperactivity Disorder (ADHD). The goal of this thesis is to explore the effect of background music on children with and without ADHD. In this study, a simple Tetris game is designed with Beethoven, Mozart music, and no-music. There are different brainwave techniques for recording; among others, the electroencephalography (EEG) allows for the most efficient use of BCI. We recorded the EEG brain signals of the regular and ADHD subjects who played the Tetris we designed according to our protocol that consists of three trials with three different background music. Attention related Alpha and Beta waves of EEG signals analyzed based on time and time-frequency domain features. The changes in the data over the 1-minute Tetris game sections are investigated with the Short-time Fourier Transform (STFT) method. The results showed that music has a considerable impact on attention of children. When it comes to music types, in general, Mozart music increases Beta waves while decreasing the Alpha band waves for subjects without ADHD. On the other hand, Beethoven music increased both Alpha and Beta band values for children with ADHD

Recent and upcoming BCI progress: overview, analysis, and recommendations

Brain–computer interfaces (BCIs) are finally moving out of the laboratory and beginning to gain acceptance in real-world situations. As BCIs gain attention with broader groups of users, including persons with different disabilities and healthy users, numerous practical questions gain importance. What are the most practical ways to detect and analyze brain activity in field settings? Which devices and applications are most useful for different people? How can we make BCIs more natural and sensitive, and how can BCI technologies improve usability? What are some general trends and issues, such as combining different BCIs or assessing and comparing performance? This book chapter provides an overview of the different sections of this book, providing a summary of how authors address these and other questions. We also present some predictions and recommendations that ensue from our experience from discussing these and other issues with our authors and other researchers and developers within the BCI community. We conclude that, although some directions are hard to predict, the field is definitely growing and changing rapidly, and will continue doing so in the next several years

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

A Hardware/Software Platform to Acquire Bioelectrical Signals. A Case Study: Characterizing Computer Access through Attention

This paper describes a hardware/software platform to acquire human body signals. In the field of physiological computing it is desirable to have a system that allows the synchronized acquisition of signals coming from different sources. Here is described how to unify the whole process of acquiring signals from both customized hardware and low cost commercial devices such as Neurosky’s mindwave. A case study using this platform is also shown: studying the feasibility of using sustained attention to access a computer. In order to do that brain activity was measured using Neurosky’s mindwave. The participants in this study were asked to keep their attention high/low for as long as possible during several trials. Experimentation was performed by 7 normally developed subjects and 3 people with cerebral palsy (CP). Our preliminary work shows that 60% of participants might be potential users of this technology. Eventually, modulating the attention to access a communication board needs a scanning period greater than 5.76s