Purpose: The purpose of this paper is to focus on ethical and judicial themes related to technology and the older adults.Design/methodology/approach: Different consecutive phases in technology design and allocation will be discussed from a range of perspectives.Findings: Longevity is one of the greatest achievements of contemporary science and a result of development of social relations. Currently, various non-communicable diseases affect older adults and impose the greatest burden on global health. There is a great emphasis across Europe on caring for the older person in their own homes. Technology has a mediating role in determining the possibilities for good quality of life (QOL). The concept of assisting the older adult through the use of technology so as to access healthcare services has enormous potential. Although the potential of technology in healthcare is widely recognised, technology use can have its downsides. Professionals need to be aware of the risks, namely, those related to the privacy of the older person, which may accompany technology use.Research limitations/implications: By 2050, there will be more people aged over 65 than there are children. This phenomenon of global ageing constitutes a massive challenge in the area of health protection.Practical implications: Professionals need to be aware of the risks, for example, related to the privacy of the older person, that may accompany technology use.Social implications: There is a great emphasis across Europe on caring for the older person in their own homes. Technology has a mediating role in determining the possibilities for QOL.Originality/value: The concept of assisting the older adult through the use of technology to avail of healthcare has enormous potential. Assistive technology, social media use and augmentative and alternative communication can have a positive effect on the QOL of older people, as long as they are supported enough in use of these technologies. However, ethical and juridical considerations are at stake as well.

Background: Several footwear design characteristics are known to have detrimental effects on the foot. However, one characteristic that has received relatively little attention is the point where the sole flexes in the sagittal plane. Several footwear assessment forms assume that this should ideally be located directly under the metarsophalangeal joints (MTPJs), but this has not been directly evaluated. The aim of this study was therefore to assess the influence on plantar loading of different locations of the shoe sole flexion point.Method: Twenty‐one asymptomatic females with normal foot posture participated. Standardised shoes were incised directly underneath the metatarsophalangeal joints, proximal to the MTPJs or underneath the midfoot. The participants walked in a randomised sequence of the three shoes whilst plantar loading patterns were obtained using the Pedar® in‐shoe pressure measurement system. The foot was divided into nine anatomically important masks, and peak pressure (PP), contact time (CT) and pressure time integral (PTI) were determined. A ratio of PP and PTI between MTPJ2‐3/MTPJ1 was also calculated.Results: Wearing the shoe with the sole flexion point located proximal to the MTPJs resulted in increased PP under MTPJ 4–5 (6.2%) and decreased PP under the medial midfoot compared to the sub‐MTPJ flexion point (−8.4%). Wearing the shoe with the sole flexion point located under the midfoot resulted in decreased PP, CT and PTI in the medial and lateral hindfoot (PP: −4.2% and −5.1%, CT: −3.4% and −6.6%, PTI: −6.9% and −5.7%) and medial midfoot (PP: −5.9% CT: −2.9% PTI: −12.2%) compared to the other two shoes.Conclusion: The findings of this study indicate that the location of the sole flexion point of the shoe influences plantar loading patterns during gait. Specifically, shoes with a sole flexion point located under the midfoot significantly decrease the magnitude and duration of loading under the midfoot and hindfoot, which may be indicative of an earlier heel lift.

Patients with orthopedic problems often use assistive devices, e.g., ankle-foot orthoses and therapeutic footwear, to support their mobility. However, many users are not satisfied with their devices or do not use them at all, resulting in a decrease of quality of life. It has been shown that a main cause for dissatisfaction and non-use lies in the process of drawing up requirements. It appears that orthopedic engineers have too little insight in the different areas of life of patients leading to deficient design requirements. In this article a general approach—the so-called Triple I model—is presented to understand the different areas of life of patients. This model offers, in line with and directed by the intention of the International Classification of Functioning, Disability and Health (ICF) model three perspectives or ‘pairs of lenses’ to analyze these areas of life: the identity, the interests of key stakeholders or social actors, and the underlying societal ideals. The Triple I model is elaborated for assistive devices and offers an associated methodology to orthopedic engineers to systematically map the different areas of life of patients, to understand the requirements for every area, and to explore the conditions. In case of assistive devices five different areas of life have to be investigated: daily living at home, work, transport, social and spiritual activities, sport and leisure.

BACKGROUND: Non-use of and dissatisfaction with ankle foot orthoses (AFOs) occurs frequently. The objective of this study is to gain insight in the conversation during the intake and examination phase, from the clients' perspective, at two levels: 1)

A position sensing glove called SmartScan, which creates a 3D virtual model of a real object, is presented. The data from the glove is processed by a volume minimization algorithm to validate the position sensor data. This allows only data from the object’s surface to be retained. The data validation algorithm allows the user to progressively improve an image by repeatedly moving their hand over the object. In addition, the user can choose their own balance between feature resolution and invalid data rejection. The SmartScan glove is tested on a foot model and is shown to be robust against motion artifacts, having a mean accuracy of 2.9 mm (compared to a 3D model generated from optical imaging) without calibration.

This report describes and develops different methods for converting 3D time series data to surface representations. The considered methods contain public domain mesh generation software, as well as linear regression models and surface representations using signed distance functions. We provide a simple code base for the latter two methods such that they can be used for further research in a simple manner. We apply and test the algorithms on a point cloud for a foot model. All methods yield good representations of the underlying foot geometry. Such algorithms can therefore have a big impact on handling foot problems.