This paper presents a new hybrid biomechanical model-based non-rigid image registration method for lung motion estimation. In the proposed method, a patient-specific biomechanical modelling process captures major physically realistic deformations with explicit physical modelling of sliding motion, whilst a subsequent non-rigid image registration process compensates for small residuals. The proposed algorithm was evaluated with 10 4D CT datasets of lung cancer patients. The target registration error (TRE), defined as the Euclidean distance of landmark pairs, was significantly lower with the proposed method (TRE = 1.37 mm) than with biomechanical modelling (TRE = 3.81 mm) and intensity-based image registration without specific considerations for sliding motion (TRE = 4.57 mm). The proposed method achieved a comparable accuracy as several recently developed intensity-based registration algorithms with sliding handling on the same datasets. A detailed comparison on the distributions of TREs with three non-rigid intensity-based algorithms showed that the proposed method performed especially well on estimating the displacement field of lung surface regions (mean TRE = 1.33 mm, maximum TRE = 5.3 mm). The effects of biomechanical model parameters (such as Poisson's ratio, friction and tissue heterogeneity) on displacement estimation were investigated. The potential of the algorithm in optimising biomechanical models of lungs through analysing the pattern of displacement compensation from the image registration process has also been demonstrated.

Current demographic trends such as increasing ethnic diversity and the ageing population indicate the importance for designers to appreciate and assess a wide variety of human capabilities, needs and wants. Work is being undertaken within the Inclusive Design Research Group to investigate how one might effectively communicate a wide range of people-based information, not only meeting designer's data requirements but also enhancing empathy with those being considered. A real-world case study is described to illustrate how rich user data in its many forms (that is, ‘human information’ as categorized by the authors) was captured and communicated to designers. This research is being carried out towards the development of an online resource which will help designers organize and interrogate issues relating to end users more effectively during the design process, and assist them in forming new connections and insights at the front end of concept creation.

Despite the potential benefits of mobile health (mHealth) services and applications, older adults face challenges and barriers to adopt mHealth. Published work on opportunities and challenges of mHealth for aging China has focused on trends in mHealth and its clinical applications, but not older adults’ perceptions or their processes of adoption. In this study, questionnaires and interviews were conducted to understand older adults’ perceptions and adoption of mHealth services in China. Conceptual models were generated using existing theories and refined using the findings of the user research. The proposed “pine tree model” illustrates the factors influencing Chinese older adults’ adoption of mHealth services and describes the process for better adoption. Based on the research, suggestions were proposed to promote mHealth adoption among older adults, which will inform better design of mHealth for the aging population in China.

Background: Advances in mobile technology and public needs have resulted in the emergence of mobile health (mHealth) services. Despite the potential benefits of mHealth apps, older adults face challenges and barriers in adopting them. Objective: The aims of this study are to understand older adults’ perception of mHealth services and to discover the barriers that older adults face in the initial adoption of mHealth apps. Methods: This paper systematically analyzed main determinants related to mHealth services and investigated them through questionnaires, interviews, and a workshop. Two studies were carried out in London. In study 1, the questionnaires with follow-up interviews were conducted based on the literature review to uncover older adults’ perception (including perceived usefulness, perceived ease of use, and perceived behavioral control) of mHealth services. Study 2 was a workshop helping older adults to trial selected mHealth apps. The workshop was conducted by the first author (JP) with assistance from 5 research students. The barriers that older adults faced in the initial adoption period were observed. The interviews and workshop were audiotaped and transcribed. Descriptive statistics and the thematic analysis technique were used for data analysis. Results: In total, 30 older adults in London completed the questionnaires and interviews in study 1. The results of study 1 show that the lack of obvious advantage, low reliability, scary information, and the risk of privacy leakage would decrease older adults’ perceived usefulness of mHealth services; the design of app interface would directly affect the perceived ease of use; and aging factors, especially the generation gap, would create barriers for older users. In total, 12 participants took part in the workshop of study 2, including 8 who took part in study 1. The results of study 2 identified that access to technology, the way of interaction, the risk of money loss, heavy workload of using an mHealth app, and different lifestyle are influential factors to older adults’ adoption of mHealth services. Conclusions: The perceptions of mHealth services of older adults were investigated; the barriers that older adults may face in the initial adoption stage were identified. On the basis of the synthesis of these results, design suggestions were proposed, including technical improvement, free trial, information clarification, and participatory design. They will help inform the design of mHealth services to benefit older adults.