A self-training program for sensory substitution devices.

PLoS One

The Baruch Ivcher Institute For Brain, Cognition & Technology, The Baruch Ivcher School of Psychology, Interdisciplinary Center (IDC), Herzeliya, Israel.

Published: September 2021

Sensory Substitution Devices (SSDs) convey visual information through audition or touch, targeting blind and visually impaired individuals. One bottleneck towards adopting SSDs in everyday life by blind users, is the constant dependency on sighted instructors throughout the learning process. Here, we present a proof-of-concept for the efficacy of an online self-training program developed for learning the basics of the EyeMusic visual-to-auditory SSD tested on sighted blindfolded participants. Additionally, aiming to identify the best training strategy to be later re-adapted for the blind, we compared multisensory vs. unisensory as well as perceptual vs. descriptive feedback approaches. To these aims, sighted participants performed identical SSD-stimuli identification tests before and after ~75 minutes of self-training on the EyeMusic algorithm. Participants were divided into five groups, differing by the feedback delivered during training: auditory-descriptive, audio-visual textual description, audio-visual perceptual simultaneous and interleaved, and a control group which had no training. At baseline, before any EyeMusic training, participants SSD objects' identification was significantly above chance, highlighting the algorithm's intuitiveness. Furthermore, self-training led to a significant improvement in accuracy between pre- and post-training tests in each of the four feedback groups versus control, though no significant difference emerged among those groups. Nonetheless, significant correlations between individual post-training success rates and various learning measures acquired during training, suggest a trend for an advantage of multisensory vs. unisensory feedback strategies, while no trend emerged for perceptual vs. descriptive strategies. The success at baseline strengthens the conclusion that cross-modal correspondences facilitate learning, given SSD algorithms are based on such correspondences. Additionally, and crucially, the results highlight the feasibility of self-training for the first stages of SSD learning, and suggest that for these initial stages, unisensory training, easily implemented also for blind and visually impaired individuals, may suffice. Together, these findings will potentially boost the use of SSDs for rehabilitation.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078811PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0250281PLOS

Publication Analysis

Top Keywords

self-training program
8
sensory substitution
8
substitution devices
8
blind visually
8
visually impaired
8
impaired individuals
8
multisensory unisensory
8
perceptual descriptive
8
training
6
self-training
5

Similar Publications

With the development of electronic technology, triboelectric-based sensors have been widely researched in fields such as healthcare, rehabilitation training, and sports assistance due to their manufacturing convenience and self-powering advantages. Among them, 3D fabric-based triboelectric sensors not only possess advantages such as easy mechanized production, good breathability, and ease of wearing but also their unique 3D structure enhances the specific surface area, thereby amplifying the sensitivity. This study proposes a 3D bristle-structured fabric made by a digital knitting technology that has not been studied widely for triboelectric devices.

View Article and Find Full Text PDF

Uncovering fine-grained phenotypes of live cell dynamics is pivotal for a comprehensive understanding of the heterogeneity in healthy and diseased biological processes. However, this endeavor poses significant technical challenges for unsupervised machine learning, requiring the extraction of features that not only faithfully preserve this heterogeneity but also effectively discriminate between established biological states, all while remaining interpretable. To tackle these challenges, a self-training deep learning framework designed for fine-grained and interpretable phenotyping is presented.

View Article and Find Full Text PDF

Effectiveness of mixed reality-based rehabilitation on hands and fingers by individual finger-movement tracking in patients with stroke.

J Neuroeng Rehabil

August 2024

Department of Rehabilitation Medicine, National Rehabilitation Center, Ministry of Health and Welfare, 58, Samgaksan-ro, Gangbuk-gu, Seoul, 01022, Republic of Korea.

Background: Mixed reality (MR) is helpful in hand training for patients with stroke, allowing them to fully submerge in a virtual space while interacting with real objects. The recognition of individual finger movements is required for MR rehabilitation. This study aimed to assess the effectiveness of updated MR-board 2, adding finger training for patients with stroke.

View Article and Find Full Text PDF

Background: Ultrasound (US) has become integral to obstetrics and gynecology (Ob/Gyn), necessitating proficient training during residency. Despite its clinical importance, there is a perceived gap in the quality and structure of postgraduate ultrasound education in Germany.

Methods: A cross-sectional survey was conducted among Ob/Gyn residents in Germany from October 2023 to March 2024, using the LimeSurvey platform.

View Article and Find Full Text PDF

Women veterans are exposed to high rates of trauma, including military sexual trauma (MST), and face unique barriers to posttraumatic stress disorder (PTSD) treatment. Telehealth interventions that are tailored to women veterans' unique lived experiences may improve treatment engagement and outcomes. It is important to ascertain how beneficial new telehealth interventions are in the context of different patient characteristics and trauma types, particularly for lower-intensity telehealth interventions (e.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!