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This study explored in-service educators' experience of using the Wisconsin Assistive Technology Initiative (WATI) for assistive technology (AT) decision-making within Singapore schools.

The study adopted a qualitative design. Eight educators across both mainstream and special education schools were introduced to the WATI framework which they subsequently employed as a trial experience for a student under their care. Written feedback gathered from participants was analysed to identify common issues and themes regarding the use of the WATI framework for AT decision-making.

The comprehensive consideration of a broad scope of different factors, provision of a structured process for AT decision-making, as well as a common language for use by different stakeholders emerged as key benefits of implementing the WATI. Challenges encountered include administrative struggles in gathering different stakeholders together, time and resource constraints and difficulties in loaning AT devices for trial use.

Based on educators' feedback, recommendations to facilitate the adoption of the WATI for AT decision-making within Singapore schools are discussed and considered. This study also highlights the need for greater AT instruction within both preservice and in-service teacher preparation programmes in Singapore.

Schools in Singapore currently rarely adopt any frameworks in place to guide educators through a systematic process of AT consideration. It is anticipated that this study will spearhead and drive the adoption of systematic frameworks such as the WATI for better AT decision-making within Singapore schools.

The peer review history for this article is available at: https://publons.com/publon 10.1108/JET-03-2021-0015

This chapter describes assistive technology (AT) and inclusive education and examines the juncture where AT works to support the inclusion of students with disabilities in mainstream settings, including classrooms, home and community settings. AT consists of a range of devices and services which work to support students to augment existing abilities, compensate for or bypass difficulties they may experience. Some AT has been specifically developed for functional use, while other, particularly emerging technology, can be adapted for, or used, in an assistive capacity. Where the AT promotes social interaction, curriculum access and the ability to express understanding, there is the potential for heightened inclusion in the classroom.

Traumatic brain injury (TBI) can significantly affect academic performance in a wide range of areas including, working memory, language processing, attention, and internalizing and externalizing behaviors. This chapter will discuss characteristics associated with TBI, and provide a series of high- and low-tech strategies teachers can implement in their classrooms to help students who have experienced brain trauma to succeed through academic challenges. In addition, the benefits and weaknesses of certain technologies used by students with TBI in school and at home will be discussed.

Students with learning disabilities are ever-present in schools today and so is the technology to support these students. Assistive technology supports students with learning disabilities (LD) in terms of access and success in general education and special education settings. This chapter will discuss the challenges students with learning disabilities may face in school and the assistive technology educators can use to help address these challenges. Specifically, this chapter pays particular attention to assistive technology to support core content areas (e.g., literacy and mathematics) as well as organization and self-management.

Currently there is a lack of evidence existing on technology specifically to support students with emotional-behavior disorder (EBD) in schools (Fitzpatrick & Knowlton, 2009). However, assistive technology (AT) considerations for all students with an Individualized Education Program (IEP) must still occur. Evidence exists that technology can compensate for students with other identified disabilities and while the specific research of students with EBD is lacking, students with disabilities, in general, appear to benefit from the support of technology. This chapter discusses how technology supports access to the general education curriculum for student with EBD in the academic areas of reading, writing, and math as well as supports self-management. Resources for free AT are also highlighted.

United Nations’ World Population Ageing Report states that falls are one of the most common problems in the elderly around the world. Falls are a leading cause of morbidity and mortality among mature adults, and the second leading cause of accidental or unintentional injury/death after road traffic injuries. The rates are higher in hospitalized patients and nursing home residents. Major contributing reasons for falling are loss of footing or traction, balance problem in carpets and rugs, reduced muscle strength, poor vision, mobility/gait, cognitive impairment: in other words lack of balance. Balance can be improved by the practice of yoga which helps to balance both body and mind through a series of physical postures called asanas, breathing control and meditation. Elders, especially women, are often unable to practice yoga regularly, largely brought on by a feeling of discomfort at having to do so in full public view, preferring instead to have private sessions at home, and at leisure. A computer-assisted self-learning system can be developed to help such elders, though improper training and the postures associated with it may harm the body’s muscles and ligaments. To have a flawless system it is essential to classify asanas, and identify the one the practitioner is currently practicing, following which the system can offer the guidance necessary. The purpose of this paper is to propose a posture recognition system, especially of sitting and standing postures. Asanas are chiefly classified into two: sitting and standing postures. This study helps to decide the values of the parameters for classification, which involve the hip and joint angles.

To model human bodies, skeleton parts such as head, neck (which are responsible for head movements), arms, hands (to decide on hand postures), and legs and feet (for standing posture identification) have been modeled and stored as a vector. Each feature is defined as a set of movable joints. Every interaction among the skeleton joints defines an action. Human skeletal information may be represented as a hierarchy of joints, in a parent–child relationship. So that whenever there is a change in joint its corresponding parent joint may also be altered.

The findings have to do with analyzing the reasons for falls in the elderly and their need for yoga as a precautionary measure. As yoga is ideally suited to self-assisted learning, it is feasible to design a system that assists people who do not wish to practice yoga in public. However, asanas are to be classified prior to doing so. In this paper, the authors have designed a posture identification framework comprising the sitting and standing postures that are fundamental to all yoga asanas, using joint angle measurements. Having fixed joint angle values is not possible, given the variations in angle values among the participants. Consequently, such parameters as the hip joint and knee angles are to be specified in range for a classification of asanas.

This work identifies the angle limits of standing and sitting postures so as to design a self-assisting system for yoga. Yoga asanas are classified and tested to enable their accurate identification. Extensive testing with older people is needed to assess the system.

The increase in the population of the elderly, coupled with their need for medical care, is a major concern worldwide. As older people are reluctant to practice yoga in public, it is anticipated that the proposed system will motivate them to do so at their convenience, and in the seclusion of their homes.

As older people are reluctant to adapt as well as practice yoga in public view, the proposal motivates and helps them to carry out yoga practices at their convenience.

This paper fulfills the initial study on the need and feasibility of creating a self-assisted yoga learning system. To identify postures and classify them joint angles are used; their range of motion has been calculated in order to set them as parameters of classification.