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Open AccessEditorial

Sensor Technologies for Caring People with Disabilities

by Francisco José García-Peñalvo and Manuel Franco-Martín

Sensors 2019, 19(22), 4914; https://doi.org/10.3390/s19224914 - 11 Nov 2019

Cited by 7 | Viewed by 2983

Abstract

Today, the population uses technology for every daily activity involving business, education, communication, entertainment, etc. Technology may also help us to take care of people who suffer some kind of disability. Complex technological ecosystems with pervasive and intelligent capabilities get along with us, [...] Read more.

Today, the population uses technology for every daily activity involving business, education, communication, entertainment, etc. Technology may also help us to take care of people who suffer some kind of disability. Complex technological ecosystems with pervasive and intelligent capabilities get along with us, facilitating the vigilance of those who need special attention or assisted living cares due to their health limitations. The advances in sensor research have enriched the powerful of these ecosystems to achieve more sophisticated monitoring and alarm systems, also taking into account the balance between the level of assistance and the people’s privacy. The Special Issue on “Sensor Technologies for Caring People with Disabilities” aims to present recent developments on sensor technologies for caring people with disabilities, focusing on the different configurations that can be used and novel applications in the field. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

Research

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21 pages, 10401 KiB

Open AccessArticle

Hand Rehabilitation and Telemonitoring through Smart Toys

by N. Alberto Borghese, Jacopo Essenziale, Renato Mainetti, Elena Mancon, Rossella Pagliaro and Giorgio Pajardi

Sensors 2019, 19(24), 5517; https://doi.org/10.3390/s19245517 - 13 Dec 2019

Cited by 11 | Viewed by 4489

Abstract

We describe here a platform for autonomous hand rehabilitation and telemonitoring of young patients. A toy embedding the electronics required to sense fingers pressure in different grasping modalities is the core element of this platform. The system has been realized following the user-centered [...] Read more.

We describe here a platform for autonomous hand rehabilitation and telemonitoring of young patients. A toy embedding the electronics required to sense fingers pressure in different grasping modalities is the core element of this platform. The system has been realized following the user-centered design methodology taking into account stakeholder needs from start: clinicians require reliable measurements and the ability to get a picture remotely on rehabilitation progression; children have asked to interact with a pleasant and comfortable object that is easy to use, safe, and rewarding. These requirements are not antithetic, and considering both since the design phase has allowed the realization of a platform reliable to clinicians and keen to be used by young children. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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18 pages, 2503 KiB

Open AccessArticle

An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease

by Giovanni Albani, Claudia Ferraris, Roberto Nerino, Antonio Chimienti, Giuseppe Pettiti, Federico Parisi, Gianluigi Ferrari, Nicola Cau, Veronica Cimolin, Corrado Azzaro, Lorenzo Priano and Alessandro Mauro

Sensors 2019, 19(21), 4764; https://doi.org/10.3390/s19214764 - 02 Nov 2019

Cited by 23 | Viewed by 3951

Abstract

The increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson’s disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of [...] Read more.

The increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson’s disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of decentralized cost-effective solutions. In this context, a system suitable for the remote monitoring of PD subjects is presented. It consists of the integration of two approaches investigated in our previous works, each one appropriate for the movement analysis of specific parts of the body: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson’s disease rating scale, and it is equipped with a gesture-based human machine interface designed to facilitate the user interaction and the system management. The usability of the system has been evaluated by means of standard questionnaires, and the accuracy of the automated assessment has been verified experimentally. The results demonstrate that the proposed solution represents a substantial improvement in PD assessment respect to the former two approaches treated separately, and a new example of an accurate, feasible and cost-effective mean for the decentralized management of PD. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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20 pages, 2502 KiB

Open AccessArticle

Improving Cognitive Visual-Motor Abilities in Individuals with Down Syndrome

by Pablo V. Torres-Carrión, Carina S. González-González, Pedro A. Toledo-Delgado, Vanesa Muñoz-Cruz, Rosa Gil-Iranzo, Nuria Reyes-Alonso and Selene Hernández-Morales

Sensors 2019, 19(18), 3984; https://doi.org/10.3390/s19183984 - 14 Sep 2019

Cited by 12 | Viewed by 5644

Abstract

Down syndrome causes a reduction in cognitive abilities, with visual-motor skills being particularly affected. In this work, we have focused on this skill in order to stimulate better learning. The proposal relies on stimulating the cognitive visual-motor skills of individuals with Down Syndrome [...] Read more.

Down syndrome causes a reduction in cognitive abilities, with visual-motor skills being particularly affected. In this work, we have focused on this skill in order to stimulate better learning. The proposal relies on stimulating the cognitive visual-motor skills of individuals with Down Syndrome (DS) using exercises with a gestural interaction platform based on the KINECT sensor named TANGO:H, the goal being to improve them. To validate the proposal, an experimental single-case study method was designed using two groups: a control group and an experimental one, with similar cognitive ages. Didactic exercises were provided to the experimental group using visual cognitive stimulation. These exercises were created on the TANGO:H Designer, a platform that was designed for gestural interaction using the KINECT sensor. As a result, TANGO:H allows for visual-motor cognitive stimulation through the movement of hands, arms, feet and head. The “Illinois Test of Psycholinguistic Abilities (ITPA)” was applied to both groups as a pre-test and post-test in its four reference sections: visual comprehension, visual-motor sequential memory, visual association, and visual integration. Two checks were made, one using the longitudinal comparison of the pre-test/post-test of the experimental group, and another that relied on comparing the difference of the means of the pre-test/post-test. We also used an observational methodology for the working sessions from the experimental group. Although the statistical results do not show significant differences between the two groups, the results of the observations exhibited an improvement in visual-motor cognitive skills. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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25 pages, 10683 KiB

Open AccessArticle

Empirical Insights of Individual Website Adjustments for People with Dyslexia

by Katja Kous and Gregor Polančič

Sensors 2019, 19(10), 2235; https://doi.org/10.3390/s19102235 - 14 May 2019

Cited by 6 | Viewed by 4344

Abstract

The existing body of knowledge reveals that customisable websites may lead to an increase in accessibility and usability for people with disabilities. In this way, the main goal of this research was to investigate how people with dyslexia respond to a customised version [...] Read more.

The existing body of knowledge reveals that customisable websites may lead to an increase in accessibility and usability for people with disabilities. In this way, the main goal of this research was to investigate how people with dyslexia respond to a customised version of a website in terms of its effectiveness, efficiency, satisfaction and suitability when compared to the default version of the website. The customisation of the investigated website was enabled with the aid of integrated assistive technology that offers people with dyslexia the opportunity to adjust a website themselves in accordance with their individual needs, demands and preferences. They can do this by changing the parameters, such as font size, font type and contrast between the background and text. The answers to the research questions were obtained with complementary research methods and techniques, including formal usability testing, thinking aloud protocol, log analyses, questionnaires and interviews. The empirical results show that participants experienced more issues when interacting with the default website, and they enjoyed more benefits when using the customised website. Too much information on the screen, not enough graphic elements, issues with visual appearance and inappropriately presented information were identified as the most common issues when interacting with the default website. When using the customised website, all participants agreed on a better user experience and, as the majority of them reported, this was due to appropriate contrast and font size. Additionally, the majority of participants also expressed desire to use the individual website adjustments regularly in the future. The conclusions of this investigation are that the individual website adjustments used in this research can not only help to minimise issues, but also eliminate challenges that people with dyslexia have when interacting with a website. Therefore, the primary contributions of this research are the empirical insights of interaction with both the default and customised version of the website for people with dyslexia. Furthermore, this research also has three secondary contributions: (1) detailed presentation and application the general usability evaluation procedure to a specific target group (people with dyslexia); (2) recommendations to adapt the usability evaluation methods for people with dyslexia; and (3) the usage of quantitative measurement instruments for the evaluation of a website’s usability and suitability for people with dyslexia. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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26 pages, 10581 KiB

Open AccessArticle

System for Face Recognition under Different Facial Expressions Using a New Associative Hybrid Model Amαβ-KNN for People with Visual Impairment or Prosopagnosia

by Moisés Márquez-Olivera, Antonio-Gustavo Juárez-Gracia, Viridiana Hernández-Herrera, Amadeo-José Argüelles-Cruz and Itzamá López-Yáñez

Sensors 2019, 19(3), 578; https://doi.org/10.3390/s19030578 - 30 Jan 2019

Cited by 7 | Viewed by 4916

Abstract

Face recognition is a natural skill that a child performs from the first days of life; unfortunately, there are people with visual or neurological problems that prevent the individual from performing the process visually. This work describes a system that integrates Artificial Intelligence [...] Read more.

Face recognition is a natural skill that a child performs from the first days of life; unfortunately, there are people with visual or neurological problems that prevent the individual from performing the process visually. This work describes a system that integrates Artificial Intelligence which learns the face of the people with whom the user interacts daily. During the study we propose a new hybrid model of Alpha-Beta Associative memories (Amαβ) with Correlation Matrix (CM) and K-Nearest Neighbors (KNN), where the Amαβ-CMKNN was trained with characteristic biometric vectors generated from images of faces from people who present different facial expressions such as happiness, surprise, anger and sadness. To test the performance of the hybrid model, two experiments that differ in the selection of parameters that characterize the face are conducted. The performance of the proposed model was tested in the databases CK+, CAS-PEAL-R1 and Face-MECS (own), which test the Amαβ-CMKNN with faces of subjects of both sexes, different races, facial expressions, poses and environmental conditions. The hybrid model was able to remember 100% of all the faces learned during their training, while in the test in which faces are presented that have variations with respect to those learned the results range from 95.05% in controlled environments and 86.48% in real environments using the proposed integrated system. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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18 pages, 604 KiB

Open AccessArticle

Hand Movement Classification Using Burg Reflection Coefficients

by Daniel Ramírez-Martínez, Mariel Alfaro-Ponce, Oleksiy Pogrebnyak, Mario Aldape-Pérez and Amadeo-José Argüelles-Cruz

Sensors 2019, 19(3), 475; https://doi.org/10.3390/s19030475 - 24 Jan 2019

Cited by 15 | Viewed by 4098

Abstract

Classification of electromyographic signals has a wide range of applications, from clinical diagnosis of different muscular diseases to biomedical engineering, where their use as input for the control of prosthetic devices has become a hot topic of research. The challenge of classifying these [...] Read more.

Classification of electromyographic signals has a wide range of applications, from clinical diagnosis of different muscular diseases to biomedical engineering, where their use as input for the control of prosthetic devices has become a hot topic of research. The challenge of classifying these signals relies on the accuracy of the proposed algorithm and the possibility of its implementation in hardware. This paper considers the problem of electromyography signal classification, solved with the proposed signal processing and feature extraction stages, with the focus lying on the signal model and time domain characteristics for better classification accuracy. The proposal considers a simple preprocessing technique that produces signals suitable for feature extraction and the Burg reflection coefficients to form learning and classification patterns. These coefficients yield a competitive classification rate compared to the time domain features used. Sometimes, the feature extraction from electromyographic signals has shown that the procedure can omit less useful traits for machine learning models. Using feature selection algorithms provides a higher classification performance with as few traits as possible. The algorithms achieved a high classification rate up to 100% with low pattern dimensionality, with other kinds of uncorrelated attributes for hand movement identification. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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15 pages, 1467 KiB

Open AccessArticle

HUSP: A Smart Haptic Probe for Reliable Training in Musculoskeletal Evaluation Using Motion Sensors

by Vidal Moreno, Belén Curto, Juan A. Garcia-Esteban, Felipe Hernández Zaballos, Pablo Alonso Hernández and F. Javier Serrano

Sensors 2019, 19(1), 101; https://doi.org/10.3390/s19010101 - 29 Dec 2018

Cited by 6 | Viewed by 3937

Abstract

As a consequence of the huge development of IMU (Inertial Measurement Unit) sensors based on MEMS (Micro-Electromechanical Systems), innovative applications related to the analysis of human motion are now possible. In this paper, we present one of these applications: a portable platform for [...] Read more.

As a consequence of the huge development of IMU (Inertial Measurement Unit) sensors based on MEMS (Micro-Electromechanical Systems), innovative applications related to the analysis of human motion are now possible. In this paper, we present one of these applications: a portable platform for training in Ultrasound Imaging-based musculoskeletal (MSK) exploration in rehabilitation settings. Ultrasound Imaging (USI) in the diagnostic and treatment of MSK pathologies offers various advantages, but it is a strongly operator-dependent technique, so training and experience become of fundamental relevance for rehabilitation specialists. The key element of our platform is a replica of a real transducer (HUSP—Haptic US Probe), equipped with MEMS based IMU sensors, an embedded computing board to calculate its 3D orientation and a mouse board to obtain its relative position in the 2D plane. The sensor fusion algorithm used to resolve in real-time the 3D orientation (roll, pitch and yaw angles) of the probe from accelerometer, gyroscope and magnetometer data will be presented. Thanks to the results obtained, the integration of the probe into the learning platform allows a haptic sensation to be recreated in the rehabilitation trainee, with an attractive performance/cost ratio. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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39 pages, 15338 KiB

Open AccessArticle

Web Page Design Recommendations for People with Down Syndrome Based on Users’ Experiences

by Lucía Alonso-Virgós, Luís Rodríguez Baena, Jordán Pascual Espada and Rubén González Crespo

Sensors 2018, 18(11), 4047; https://doi.org/10.3390/s18114047 - 20 Nov 2018

Cited by 12 | Viewed by 6121

Abstract

At present, there is a high number of people with Down syndrome interested and trained to be an active part of society. According to the data extracted by our surveys we know that only 6% of the population with Down syndrome feels isolated [...] Read more.

At present, there is a high number of people with Down syndrome interested and trained to be an active part of society. According to the data extracted by our surveys we know that only 6% of the population with Down syndrome feels isolated in daily activities. However, when the activity requires the use of a computer, the percentage of people who feel isolated increases to 18%. This means that there are obvious website accessibility barriers that make it difficult for users with Down syndrome. To solve this problem, it is considered necessary to make an exhaustive study about Down syndrome. We know that the trisomy of chromosome 21 causes a series of symptoms that directly affect ones Internet browsing capabilities. For example, speech disturbances make communication and speed difficult. This guide is based on a neurological study of Down syndrome. Alterations in listening make understanding audio, retention of audio concepts and speed difficult. The alterations in the physiognomy of movement make it difficult for them to act quickly. Many of these alterations are caused by cognitive disability. After assessing the needs, the benefits of Web Content Accessibility Guidelines 2.0 (WCAG 2.0), and the existing usability guidelines are analyzed and those that may be useful for this profile are extracted. User tests are carried out through two websites developed specifically for this study with the aim of demonstrating the level of effectiveness of each of the planned guidelines. Considering the neurological characteristics of this intellectual disability, research is developed that seeks to extract a list of useful accessibility and usability guidelines for web developers. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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14 pages, 8736 KiB

Open AccessArticle

Support for Employees with ASD in the Workplace Using a Bluetooth Skin Resistance Sensor–A Preliminary Study

by Michał T. Tomczak, Marek Wójcikowski, Paulina Listewnik, Bogdan Pankiewicz, Daria Majchrowicz and Małgorzata Jędrzejewska-Szczerska

Sensors 2018, 18(10), 3530; https://doi.org/10.3390/s18103530 - 19 Oct 2018

Cited by 20 | Viewed by 4337

Abstract

The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the [...] Read more.

The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the sensor, on the body, to gain the most accurate readings of user stress levels, under various conditions. Trial tests were performed on a group of sixteen people to verify the correct functioning of the device. Resistance levels were compared to those from the reference system. The placement of the sensor has also been determined, based on wearer convenience. With the Bluetooth Low Energy block, users can be notified immediately about their abnormal stress levels via a smartphone application. This can help people with ASD, and those who work with them, to facilitate stress control and make necessary adjustments to their work environment. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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27 pages, 14560 KiB

Open AccessArticle

Visual Localizer: Outdoor Localization Based on ConvNet Descriptor and Global Optimization for Visually Impaired Pedestrians

by Shufei Lin, Ruiqi Cheng, Kaiwei Wang and Kailun Yang

Sensors 2018, 18(8), 2476; https://doi.org/10.3390/s18082476 - 31 Jul 2018

Cited by 34 | Viewed by 6055

Abstract

Localization systems play an important role in assisted navigation. Precise localization renders visually impaired people aware of ambient environments and prevents them from coming across potential hazards. The majority of visual localization algorithms, which are applied to autonomous vehicles, are not adaptable completely [...] Read more.

Localization systems play an important role in assisted navigation. Precise localization renders visually impaired people aware of ambient environments and prevents them from coming across potential hazards. The majority of visual localization algorithms, which are applied to autonomous vehicles, are not adaptable completely to the scenarios of assisted navigation. Those vehicle-based approaches are vulnerable to viewpoint, appearance and route changes (between database and query images) caused by wearable cameras of assistive devices. Facing these practical challenges, we propose Visual Localizer, which is composed of ConvNet descriptor and global optimization, to achieve robust visual localization for assisted navigation. The performance of five prevailing ConvNets are comprehensively compared, and GoogLeNet is found to feature the best performance on environmental invariance. By concatenating two compressed convolutional layers of GoogLeNet, we use only thousands of bytes to represent image efficiently. To further improve the robustness of image matching, we utilize the network flow model as a global optimization of image matching. The extensive experiments using images captured by visually impaired volunteers illustrate that the system performs well in the context of assisted navigation. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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Review

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20 pages, 3438 KiB

Open AccessReview

Navigation Systems for the Blind and Visually Impaired: Past Work, Challenges, and Open Problems

by Santiago Real and Alvaro Araujo

Sensors 2019, 19(15), 3404; https://doi.org/10.3390/s19153404 - 02 Aug 2019

Cited by 114 | Viewed by 18794

Abstract

Over the last decades, the development of navigation devices capable of guiding the blind through indoor and/or outdoor scenarios has remained a challenge. In this context, this paper’s objective is to provide an updated, holistic view of this research, in order to enable [...] Read more.

Over the last decades, the development of navigation devices capable of guiding the blind through indoor and/or outdoor scenarios has remained a challenge. In this context, this paper’s objective is to provide an updated, holistic view of this research, in order to enable developers to exploit the different aspects of its multidisciplinary nature. To that end, previous solutions will be briefly described and analyzed from a historical perspective, from the first “Electronic Travel Aids” and early research on sensory substitution or indoor/outdoor positioning, to recent systems based on artificial vision. Thereafter, user-centered design fundamentals are addressed, including the main points of criticism of previous approaches. Finally, several technological achievements are highlighted as they could underpin future feasible designs. In line with this, smartphones and wearables with built-in cameras will then be indicated as potentially feasible options with which to support state-of-art computer vision solutions, thus allowing for both the positioning and monitoring of the user’s surrounding area. These functionalities could then be further boosted by means of remote resources, leading to cloud computing schemas or even remote sensing via urban infrastructure. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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46 pages, 1357 KiB

Open AccessReview

Technological Ecosystems in Care and Assistance: A Systematic Literature Review

by Samuel Marcos-Pablos and Francisco José García-Peñalvo

Sensors 2019, 19(3), 708; https://doi.org/10.3390/s19030708 - 09 Feb 2019

Cited by 31 | Viewed by 5395

Abstract

Applying the concepts of technological ecosystems to the care and assistance domain is an emerging field that has gained interest during the last years, as they allow to describe the complex relationships between actors in a technologically boosted care domain. In that context, [...] Read more.

Applying the concepts of technological ecosystems to the care and assistance domain is an emerging field that has gained interest during the last years, as they allow to describe the complex relationships between actors in a technologically boosted care domain. In that context, this paper presents a systematic review and mapping of the literature to identify, analyse and classify the published research carried out to provide care and assistance services under a technological ecosystems’ perspective. Thirty-seven papers were identified in the literature as relevant and analysed in detail (between 2003–2018). The main findings show that it is indeed an emerging field, as few of the found ecosystem proposals have been developed in the real world nor have they been tested with real users. In addition, a lot of research to date reports the proposal of platform-centric architectures developed over existing platforms not specifically developed for care and services provision. Employed sensor technologies for providing services have very diverse natures depending on the intended services to be provided. However, many of these technologies do not take into account medical standards. The degree of the ecosystems’ openness to adding new devices greatly depends on the approach followed, such as the type of middleware considered. Thus, there is still much work to be done in order to equate other more established ecosystems such as business or software ecosystems. Full article

(This article belongs to the Special Issue Sensor Technologies for Caring People with Disabilities)

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