Abstract This paper presents data and analysis from survey research conducted by the Rehabilitation Engineering Research Center on Information and Communication Technology Access for Mobile Rehabilitation (mRehab RERC) on the use and unmet needs for mHealth mobile apps by people with disabilities in the United States. Quantitative and qualitative data are reported on user experiences with mHealth apps to map the behavior, interests and needs of people with specific types of disability (physical, cognitive, sensory, emotional/psychological, and speech). Summary results are presented for all respondents and each disability type. Slightly more than half of the participants in this sample (53.2%) reported using mHealth apps. Fitness and exercise apps were the mHealth apps most used by respondents with disabilities, followed by hospital/clinical portal apps. Symptom and disease management apps are the least commonly used, even though these would seem to be important for people with chronic conditions. Text-based responses regarding unmet needs for mHealth apps can be sorted into accessibility needs and functionality needs. In general, respondents with sensory limitations were more likely to identify accessibility needs. However, all disability groups identified both types of unmet needs. These results can help inform research and development efforts to provide mHealth apps that meet the needs of people with disabilities.

Abstract This paper presents data and analysis from survey research conducted by the Rehabilitation Engineering Research Center on Information and Communications Technology Access for Information and Communications Technology (ICT) Access for Community Living, Health and Function (LiveWell RERC) on the perceptions and attitudes of clinical professionals in rehabilitation medicine regarding mobile health (mHealth) and mobile rehabilitation (mRehab) practices, techniques and technology in the United States. The analytical focus of this paper is on two key survey questions related to specific barriers and opportunities (most critical use-cases) for adopting mHealth/mRehab interventions. We present response data to these two questions segmented by clinical specialty – physical, occupational, speech and recreation therapy – to identify possible variation between and among these rehabilitation professions. This analysis provides a detailed map of the terrain of clinician expectations and experiences for the adoption and implementation of mHealth/mRehab interventions in the United States, and possibly other countries. Results show substantial support for mRehab interventions and technologies across all four clinical specialties. The most frequently identified barriers to effective use of mobile and internet technologies to support patients remotely focused on patients (ability to learn and use the technology, and internet access), not clinicians. The was more variability among clinical specializations regarding best use-cases. Tracking patient adherence to prescribed activities and supporting patients in the home and community were the most frequently cited best use cases across the whole sample.

Numerous sensors in modern mobile phones enable a range of people-centric applications. This paper envisions a system called PhonePoint Pen that uses the in-built accelerometer in mobile phones to recognize human writing. By holding the phone like a pen, a user should be able to write short messages or draw simple diagrams in the air. The acceleration due to hand gestures can be translated into geometric strokes, and recognized as characters. We prototype the PhonePoint Pen on the Nokia N95 platform, and evaluate it through real users. Results show that English characters can be identified with an average accuracy of 91.9%, if the users conform to a few reasonable constraints. Future work is focused on refining the prototype, with the goal of offering a new user-experience that complements keyboards and touch-screens.