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Introduction Drug administration by self-injection provides an option to treat chronic inflammatory diseases such as rheumatoid arthritis (RA) and Crohn’s disease (CD). However, a negative self-injection experience for patients may reduce patient adherence to the recommended treatment regimen. In this study, a holistic approach was used to identify common themes along the treatment pathway and at self-injection that, if changed, could improve patient experience and treatment outcomes. Methods Two ethnographic studies were conducted: Field Insights CODE (FI[CODE]) examined the treatment pathway within the context of the experience of living with RA or CD, and Injection Mission 2020 (IM2020) focused on the moment of self-injection. FI(CODE) used an open ethnographic approach to interview 62 patients and 10 healthcare professionals (HCPs) from the US and UK. IM2020 included a review of over 50 injection device design information sources from the sponsor, and interviews with 9 patients, 8 HCPs, and 5 medical device designers from the US, UK, Canada, and Japan. Results FI(CODE) identified suboptimal treatment practices along the treatment pathway in four key areas: treatment team communication, treatment choice, patient empowerment, and treatment delivery. Patients with more treatment options and greater disease understanding were less likely to struggle with the treatment process. IM2020 demonstrated that five related components influenced the self-injection experience: delivery process, emotional state, social perception, educational level, and ritualization of the self-injection process. Conclusion These analyses highlight several potential areas for improvement, including aligning the device more to patients’ needs to improve treatment adherence, better accessibility to educational resources to increase patient disease understanding, and guidance to empower patients to develop an optimal personalized self-injection ritual. Funding UCB Pharma. Electronic supplementary material The online version of this article (doi:10.1007/s40744-017-0080-4) contains supplementary material, which is available to authorized users.

We describe recent results obtained with AQUA, a mobile robot capable of swimming, walking and amphibious operation. Designed to rely primarily on visual sensors, the AQUA robot uses vision to navigate underwater using servobased guidance, and also to obtain high-resolution range scans of its local environment. This paper describes some of the pragmatic and logistic obstacles encountered, and provides an overview of some of the basic capabilities of the vehicle and its associated sensors. Moreover, this paper presents the first ever amphibious transition from walking to swimming.

Abstract-In this paper, we explore the idea of using inertial and actuator information to accurately identify the environment of an amphibious robot. In particular, in our work with a legged robot we use internal sensors to measure the dynamics and interaction forces experienced by the robot. From these measurements we use simple machine learning methods to probabilistically infer properties of the environment, and therefore identify it. The robot's gait can then be automatically selected in response to environmental changes. Experimental results show that for several environments (sand, water, snow, ice, etc.), the identification process is over 90 per cent accurate. The requisite data can be collected during a half-leg rotation (about 250 ms), making it one of the fastest and most economical environment identifiers for a dynamic robot. For the littoral setting, a gaitchange experiment is done as a proof-of-concept of a robot automatically adapting its gait to suit the environment.