Access Technologies for Children and Youth with Severe Motor Disabilities

2016 ◽  
pp. 59-98
Keyword(s):  
Children And Youth ◽  
Motor Disabilities ◽  
Severe Motor

An Overview on the Use of Serious Games in Physical Therapy and Rehabilitation

2012 ◽  
pp. 1175-1187 ◽  
Author(s):  
Tiago Martins ◽  
Vítor Carvalho ◽  
Filomena Soares
Keyword(s):  
Physical Therapy ◽  
Serious Games ◽  
Rehabilitation Program ◽  
Motor Disabilities ◽  
Interactive Games ◽  
Healthcare Settings ◽  
Study Results ◽  
Severe Motor ◽  
Number Of Individuals

As a significant number of individuals have severe motor disabilities due to neurological and musculoskeletal conditions, it is important to provide them with an appropriate rehabilitation program in order to improve their quality of life. Several study results suggest that many elements of the interactive games have tremendous potential as rehabilitation tools. Serious games can entertain the players, while rewarding and reinforcing healthy movements. As these technologies create a pleasant environment, they motivate the patients to perform the necessary exercises with satisfaction and total relaxation, even forgetting that they are conducting therapy. In this sense, various serious games are being applied in healthcare settings, namely in many physical therapy and rehabilitation situations. This chapter discusses the different potentialities of several serious games when used in physical therapy and rehabilitation of patients with problems in motor skills.

Noninvasive Brain–Machine Interfaces for Robotic Devices

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Luca Tonin ◽  
José del R. Millán
Keyword(s):  
Autonomous Systems ◽  
Discrete Control ◽  
Annual Review ◽  
Publication Date ◽  
User Centered Design ◽  
Brain Machine Interfaces ◽  
Motor Disabilities ◽  
Severe Motor ◽  
Robotic Devices ◽  
And Robotics

The last decade has seen a flowering of applications driven by brain–machine interfaces (BMIs), particularly brain-actuated robotic devices designed to restore the independence of people suffering from severe motor disabilities. This review provides an overview of the state of the art of noninvasive BMI-driven devices based on 86 studies published in the last 15 years, with an emphasis on the interactions among the user, the BMI system, and the robot. We found that BMIs are used mostly to drive devices for navigation (e.g., telepresence mobile robots), with BMI paradigms based mainly on exogenous stimulation, and the majority of brain-actuated robots adopt a discrete control strategy. Most critically, in only a few works have disabled people evaluated a brain-actuated robot. The review highlights the most urgent challenges in the field, from the integration between BMI and robotics to the need for a user-centered design to boost the translational impact of BMIs. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 3, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Towards Independence: A BCI Telepresence Robot for People With Severe Motor Disabilities

2015 ◽  
Vol 103 (6) ◽  
pp. 969-982 ◽  
Author(s):  
Robert Leeb ◽  
Luca Tonin ◽  
Martin Rohm ◽  
Lorenzo Desideri ◽  
Tom Carlson ◽  
...  
Keyword(s):  
Motor Disabilities ◽  
Telepresence Robot ◽  
Severe Motor

scholarly journals Design and Development of One-Switch Video Games for Children with Severe Motor Disabilities

2017 ◽  
Vol 10 (4) ◽  
pp. 1-42 ◽  
Author(s):  
Sebastián Aced López ◽  
Fulvio Corno ◽  
Luigi De Russis
Keyword(s):  
Video Games ◽  
Design And Development ◽  
Motor Disabilities ◽  
Severe Motor

scholarly journals Usability, occupational performance and satisfaction evaluation of a smart environment controlled by infrared oculography by people with severe motor disabilities

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256062
Author(s):  
Mariana Midori Sime ◽  
Alexandre Luís Cardoso Bissoli ◽  
Daniel Lavino-Júnior ◽  
Teodiano Freire Bastos-Filho
Keyword(s):  
Assistive Technology ◽  
Functional Independence Measure ◽  
Functional Independence ◽  
Performance Measure ◽  
Smart Environment ◽  
Occupational Performance ◽  
Structured Interviews ◽  
Motor Disabilities ◽  
Canadian Occupational Performance Measure ◽  
Severe Motor

A smart environment is an assistive technology space that can enable people with motor disabilities to control their equipment (TV, radio, fan, etc.) through a human-machine interface activated by different inputs. However, assistive technology resources are not always considered useful, reaching quite high abandonment rate. This study aims to evaluate the effectiveness of a smart environment controlled through infrared oculography by people with severe motor disabilities. The study sample was composed of six individuals with motor disabilities. Initially, sociodemographic data forms, the Functional Independence Measure (FIMTM), and the Canadian Occupational Performance Measure (COPM) were applied. The participants used the system in their domestic environment for a week. Afterwards, they were reevaluated with regards to occupational performance (COPM), satisfaction with the use of the assistive technology resource (QUEST 2.0), psychosocial impact (PIADS) and usability of the system (SUS), as well as through semi-structured interviews for suggestions or complaints. The most common demand from the participants of this research was ‘control of the TV’. Two participants did not use the system. All participants who used the system (four) presented positive results in all assessment protocols, evidencing greater independence in the control of the smart environment equipment. In addition, they evaluated the system as useful and with good usability. Non-acceptance of disability and lack of social support may have influenced the results.

scholarly journals Integrating Behavior of Children with Profound Intellectual, Multiple, or Severe Motor Disabilities With Location and Environment Data Sensors for Independent Communication and Mobility: App Development and Pilot Testing (Preprint)

2021 ◽  
Author(s):  
Von Ralph Dane Marquez Herbuela ◽  
Tomonori Karita ◽  
Yoshiya Furukawa ◽  
Yoshinori Wada ◽  
Yoshihiro Yagi ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
Environmental Data ◽  
Data Sources ◽  
Single Subject ◽  
Body Parts ◽  
Cross Sectional ◽  
Motor Disabilities ◽  
Severe Motor ◽  
Outdoor Location ◽  
Child Caregiver

BACKGROUND Children with profound intellectual and multiple disabilities (PIMD) or severe motor and intellectual disabilities (SMID) only communicate through movements, vocalizations, body postures, muscle tensions, or facial expressions on a pre- or protosymbolic level. Yet, to the best of our knowledge, there are few systems developed to specifically aid in categorizing and interpreting behaviors of children with PIMD or SMID to facilitate independent communication and mobility. Further, environmental data such as weather variables were found to have associations with human affects and behaviors among typically developing children; however, studies involving children with neurological functioning impairments that affect communication or those who have physical and/or motor disabilities are unexpectedly scarce. OBJECTIVE This paper describes the design and development of the ChildSIDE app, which collects and transmits data associated with children’s behaviors, and linked location and environment information collected from data sources (GPS, iBeacon device, ALPS Sensor, and OpenWeatherMap application programming interface [API]) to the database. The aims of this study were to measure and compare the server/API performance of the app in detecting and transmitting environment data from the data sources to the database, and to categorize the movements associated with each behavior data as the basis for future development and analyses. METHODS This study utilized a cross-sectional observational design by performing multiple single-subject face-to-face and video-recorded sessions among purposively sampled child-caregiver dyads (children diagnosed with PIMD/SMID, or severe or profound intellectual disability and their primary caregivers) from September 2019 to February 2020. To measure the server/API performance of the app in detecting and transmitting data from data sources to the database, frequency distribution and percentages of 31 location and environment data parameters were computed and compared. To categorize which body parts or movements were involved in each behavior, the interrater agreement κ statistic was used. RESULTS The study comprised 150 sessions involving 20 child-caregiver dyads. The app collected 371 individual behavior data, 327 of which had associated location and environment data from data collection sources. The analyses revealed that ChildSIDE had a server/API performance >93% in detecting and transmitting outdoor location (GPS) and environment data (ALPS sensors, OpenWeatherMap API), whereas the performance with iBeacon data was lower (82.3%). Behaviors were manifested mainly through hand (22.8%) and body movements (27.7%), and vocalizations (21.6%). CONCLUSIONS The ChildSIDE app is an effective tool in collecting the behavior data of children with PIMD/SMID. The app showed high server/API performance in detecting outdoor location and environment data from sensors and an online API to the database with a performance rate above 93%. The results of the analysis and categorization of behaviors suggest a need for a system that uses motion capture and trajectory analyses for developing machine- or deep-learning algorithms to predict the needs of children with PIMD/SMID in the future.

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