Critical Behavior Monitoring for Children with Special Needs in Preventing Physical Injury Using Kinect

This research studies ways to prevent physical injury for children with special needs, or specifically children with Autism Spectrum Disorder (ASD). The prevention is achievable by monitoring child behavior in the classroom from time to time. A Critical Behavior Monitoring model was developed for this purpose. The model is integrated with a Kinect sensor (by Microsoft) to process the signal acquired for human activities recognition. Currently, the model manages to identify 17 different human activities and notify parents or teachers via SMS and/or email if any unusual or critical activities are detected (i.e. falling down or asking for help). This will ensure immediate action is taken to prevent injuries or the situation from getting worse.

The Role of Ambient Intelligent Environments for Tracking Functional Decline

We live in a ubiquitous world where we are surrounded by context sensitive information and smart devices that are able to capture information about our surroundings unobtrusively. Making use of such rich information can enable recognition of activities conducted by elderly users, and in turn can allow the possibility of tracking any functional decline. This chapter highlights the current methods for unobtrusively recognising activities of daily living within a home environment for people with physical or cognitive disabilities. A main group for which this is important for are Alzheimer's patients. The chapter also bases the discussion of what makes a successful environment for carrying out accurate activity recognition, which is then followed by a proposed taxonomy of the key characteristics that are required for robust activity recognition within a smart environment, contextualised with real-life scenarios.

Robotics for Assisting Children with Physical and Cognitive Disabilities

This chapter summarizes the findings of a study on robotics research and application for assisting children with disabilities between the years 2009 and 2013. The said disabilities include impairment of motor skills, locomotion, and social interaction that is commonly attributed to children suffering from Autistic Spectrum Disorders (ASD) and Cerebral Palsy (CP). As opposed to assistive technologies for disabilities that largely account for restoration of physical capabilities, disabled children also require dedicated rehabilitation for social interaction and mental health. As such, the breadth of this study covers existing efforts in rehabilitation of both physical and socio-psychological domains, which involve Human-Robot Interaction. Overviewed topics include assisted locomotion training, passive stretching and active movement rehabilitation, upper-extremity motor function, social interactivity, therapist-mediators, active play encouragement, as well as several life-long assistive robotics in current use. This chapter concludes by drawing attention to ethical and adoption issues that may obstruct the field's effectiveness.

Persuasive Subtleties of Social Networking Sites

The key objective of this chapter is to improve deeper understanding of SNSs' usage, acceptance, and users' actual behaviors. The authors propose that understanding the phenomenal success of Facebook could provide valuable information for developing health behavior change interventions. Using structured questionnaires, the authors collect qualitative data to understand SNSs users' online behaviors with an explicit focus on enjoyment and entertainment, desire to be connected, reciprocation, information quality, need for admiration, and influence of task obtrusiveness. The authors perform quantitative analyses with a special focus on value-based constructs because values are motivational constructs and could help predict users' behaviors. Results indicate that enjoyment and entertainment, reciprocation, and admiration have the strongest influence on individuals' behaviors. Although it is still early for people to use SNSs for health purposes, the results could pave the way for future research into this interesting area.

Dance and Movement as Therapy for Children with Autism Spectrum Disorders (ASD)

This chapter attempts to introduce the concept of Dance and Movement Therapy (DMT) in treating autistic-like symptoms and discusses the validity and feasibility of adopting DMT as a complementary component of an existing intervention framework. By defining mainstream DMT, identifying its implications for children across the spectrum, and briefly touching upon the theoretical aspects of its workings, it is hoped that parents, teachers, and educators can gain a more thorough understanding of this method. An outline of how it can be adapted for children with a range of abilities is also supplied. Finally, initial observations of DMT applied in Kuching, Malaysia, are shared with concluding suggestions for success within this particular cultural and social context. This chapter is aimed at the new practitioner looking for a starting point resource as well as parents, teachers, and educators who may be thinking about implementing DMT into a child's routine or programme.

Assistive Systems for the Workplace

Recent advances in motion recognition allow the development of Context-Aware Assistive Systems (CAAS) for industrial workplaces that go far beyond the state of the art: they can capture a user's movement in real-time and provide adequate feedback. Thus, CAAS can address important questions, like Which part is assembled next? Where do I fasten it? Did an error occur? Did I process the part in time? These new CAAS can also make use of projectors to display the feedback within the corresponding area on the workspace (in-situ). Furthermore, the real-time analysis of work processes allows the implementation of motivating elements (gamification) into the repetitive work routines that are common in manual production. In this chapter, the authors first describe the relevant backgrounds from industry, computer science, and psychology. They then briefly introduce a precedent implementation of CAAS and its inherent problems. The authors then provide a generic model of CAAS and finally present a revised and improved implementation.

Depth Cameras in AAL Environments

Automatic and privacy-preserving systems to monitor elderly people in their home environment are one of the basic targets addressed by the wide research area of Ambient Assisted Living. Thanks to the low-cost Microsoft Kinect® device, high-resolution depth and visual sensing is now not limited to experimental and prototype implementations and is ready to address marketable solutions. This chapter emphasizes the advantages provided by Kinect in the field of automatic monitoring, discussing its performance in human subject detection and tracking. Two sample use cases are discussed in detail: the former deals with generating a numerical representation of the Get Up and Go Test outcome, the latter implements an automatic fall detection algorithm based on depth frames analysis, with the sensor in a top configuration. The chapter ends suggesting issues that need to be addressed to further extend the range of applications for the Kinect device and enhance the obtainable performance.

A Mobile Navigation System Based on Visual Cues for Pedestrians with Cognitive Disabilities

The authors present a prototype of a mobile navigation system designed for pedestrians with cognitive disabilities. The system first determines the shortest route from current location to a desired predefined destination from a set of candidate routes obtained from Bing Maps and Google Maps. Then the system extracts intermediate targets (decision points) from the route according to street crossings. The guidance to the next intermediate target is provided in the form of atomic textual and auditory instructions, together with visual cues extracted automatically from Google Street View. The experimental evaluation of the application is carried out via a field study with two subjects with Down syndrome in authentic urban setting. The chapter concludes with a reflection on the design of the system and the findings of the field study.

Developing Assistive Interventions

Digital interventions have received a great deal of attention from researchers and scholars. Development, implementation, and evaluation of behavior change, and assistive technologies for improved living are being increasingly studied. Assistive technologies in particular have opened up venues for technological advancements for supported living for people with mental and physical disabilities. This chapter is conceptual in nature and discusses the emergence of digital interventions for improved living. Further advancement of a relatively new research field of Persuasive Technology is discussed that is largely related to supporting healthy living. The aim of the chapter is to review early digital interventions and emergence of behavior change and assistive technologies. It highlights potential benefits that could be realized through the use of carefully designed behavior change and assistive technologies. In addition, several key challenges, promises, and pitfalls are briefly outlined. Presented knowledge would help researchers and practitioners in abstracting, designing, and evaluating assistive technologies.

Telemedicine Program for Management and Treatment of Stress Urinary Incontinence in Women

Stress Urinary Incontinence (SUI), defined as involuntary urine leakage caused by physical activity and/or efforts, is a frequently found pathology among women that significantly affects their quality of life. SUI treatments are often less effective than expected because they require a conscious effort by the patient to follow them correctly and usually have drawbacks, such as their high cost, time, and/or schedule requirements. ICT-mediated Physical Therapy treatment programs can be useful to improve Stress Urinary Incontinence symptoms and pelvic floor function in women while maintaining total confidentiality, with an at home treatment, accomplishing a higher adherence to the treatment, keeping a low budget for the patients, and saving the health systems' economic resources.