Automated prompting technologies in rehabilitation and at home

Purpose - The purpose of this paper is to test the efficacy of an interactive verbal prompting technology (Guide) on supporting the morning routine. Data have already established the efficacy of such prompting during procedural tasks, but the efficacy of such prompting in tasks with procedural and motivational elements remains unexamined. Such tasks, such as getting out of bed in the morning and engaging in personal care, are often the focus of rehabilitation goals. Design/methodology/approach - A single-n study with a male (age 61) who had severe cognitive impairment and was having trouble completing the morning routine. An A-B-A'-B'-A?-B? design was used, with the intervention phase occurring both in an in-patient unit (B, B') and in the participant's own home (B?). Findings - Interactive verbal prompting technology (Guide) significantly reduced support worker prompting and number of errors in the in-patient setting and in the participant's own home. Research limitations/implications - The results suggest that interactive verbal prompting can be used to support motivational tasks such as getting out of bed and the morning routine. This study used a single subject experimental design and the results need to be confirmed in a larger sample. Originality/value - This is the first report of use of interactive verbal prompting technology to support rehabilitation of a motivational task. It is also the first study to evaluate Guide in a domestic context

Human centric situational awareness

Context awareness is an approach that has been receiving increasing focus in the past years. A context aware device can understand surrounding conditions and adapt its behavior accordingly to meet user demands. Mobile handheld devices offer a motivating platform for context aware applications as a result of their rapidly growing set of features and sensing abilities. This research aims at building a situational awareness model that utilizes multimodal sensor data provided through the various sensing capabilities available on a wide range of current handheld smart phones. The model will make use of seven different virtual and physical sensors commonly available on mobile devices, to gather a large set of parameters that identify the occurrence of a situation for one of five predefined context scenarios: In meeting, Driving, in party, In Theatre and Sleeping. As means of gathering the wisdom of the crowd and in an effort to reach a habitat sensitive awareness model, a survey was conducted to understand the user perception of each context situation. The data collected was used to build the inference engine of a prototype context awareness system utilizing context weights introduced in [39] and the confidence metric in [26] with some variation as a means for reasoning. The developed prototype\u27s results were benchmarked against two existing context awareness platforms Darwin Phones [17] and Smart Profile [11], where the prototype was able to acquire 5% and 7.6% higher accuracy levels than the two systems respectively while performing tasks of higher complexity. The detailed results and evaluation are highlighted further in section 6.4

How can weight-loss app designers' best engage and support users? A qualitative investigation

This is the peer reviewed version of the article, which has been published in final form at doi: 10.1111/bjhp.12114. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for self-archiving.This study explored young adults' experiences of using e-health internetbased computer or mobile phone applications (apps) and what they valued about those apps.NIH

The making of modern motherhoods: Storying an emergent identity

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