Harmonising Assistive Technology Assessment Data: A Case Study in Nepal

There is a practical demand to maximise existing data to understand and meet the assistive technology (AT) needs in dynamic populations. Harmonisation can generate new insight by integrating multiple datasets that were not previously comparable into a single longitudinal dataset. We harmonised AT assessment data from three population-based surveys collected several years apart in Nepal: the Living Conditions of Persons with Disabilities (2014-2015), the Multiple Indicator Cluster Survey (2019), and the rapid Assistive Technology Assessment (2022). The harmonised dataset demonstrates a method that can be used for unifying AT surveys in other settings and conducting trend analyses that are necessary for monitoring a population's dynamic AT needs. We set out to explore AT data's potential for harmonisation, and learned there is indeed value in this approach for situating disparate datasets, though the methodology proposed will need further validation

Digital Fabrication of Lower Limb Prosthetic Sockets

This innovation insight discusses current approaches to digital fabrication of lower limb prosthetics (LLP) sockets aimed at low resourced settings. Digital fabrication of LLPs sockets has been researched for a number of decades, yet these technologies are not widely adopted, and most of the activities within this domain reside in high-income settings. However, the majority of amputees are in LMICs where there is a severe lack of access to services. It is in LMICs then, that the advantages that digital technologies offer could be of particular benefit however little to no progress in digital workflow adoption has been made to date

A Deep Learning Approach to Non-linearity in Wearable Stretch Sensors

There is a growing need for flexible stretch sensors to monitor real time stress and strain in wearable technology. However, developing stretch sensors with linear responses is difficult due to viscoelastic and strain rate dependent effects. Instead of trying to engineer the perfect linear sensor we take a deep learning approach which can cope with non-linearity and yet still deliver reliable results. We present a general method for calibrating highly hysteretic resistive stretch sensors. We show results for textile and elastomeric stretch sensors however we believe the method is directly applicable to any physical choice of sensor material and fabrication, and easily adaptable to other sensing methods, such as those based on capacitance. Our algorithm does not require any a priori knowledge of the physical attributes or geometry of the sensor to be calibrated, which is a key advantage as stretchable sensors are generally applicable to highly complex geometries with integrated electronics requiring bespoke manufacture. The method involves three-stages. The first stage requires a calibration step in which the strain of the sensor material is measured using a webcam while the electrical response is measured via a set of arduino-based electronics. During this data collection stage, the strain is applied manually by pulling the sensor over a range of strains and strain rates corresponding to the realistic in-use strain and strain rates. The correlated data between electrical resistance and measured strain and strain rate are stored. In the second stage the data is passed to a Long Short Term Memory Neural Network (LSTM) which is trained using part of the data set. The ability of the LSTM to predict the strain state given a stream of unseen electrical resistance data is then assessed and the maximum errors established. In the third stage the sensor is removed from the webcam calibration set-up and embedded in the wearable application where the live stream of electrical resistance is the only measure of strain-this corresponds to the proposed use case. Highly accurate stretch topology mapping is achieved for the three commercially available flexible sensor materials tested

Experiences of lower limb prosthesis users in Kenya: a qualitative study to understand motivation to use and satisfaction with prosthetic outcomes

PURPOSE: To explore the personal and system factors that motivate and enhance outcomes for patients accessing a prosthetic service and using a lower-limb prosthesis within a low resource setting. MATERIALS AND METHODS: This study employed a qualitative approach to explore the motivations and satisfaction of individuals with lower limb loss engaging with a prosthetic service in Mombasa, Kenya. In-depth interviews were conducted over Microsoft Teams with 10 lower limb prosthesis users and thematic analysis was applied. RESULTS: Five key themes emerged: acceptance, self-determination, hope, clinician relationship and perception. These findings demonstrate the importance of hopeful thinking and a supportive community in overcoming physical and stigmatising challenges. The findings further highlight the value of the service provider relationship beyond just prescribing an assistive device. CONCLUSION: These results have relevance in developing patient-centred services, assistive devices and personnel training that are responsive, motivating, and cognisant of the service user. This is of particular interest as assistive technology services are newly developed in low resource settings.IMPLICATIONS FOR REHABILITATIONThis research provides an understanding of lower-limb prosthesis users' satisfaction of a device and motivation for engaging with a prosthetic service within a low resource setting.The relationship the rehabilitation professional has with the service user plays a significant role in facilitating motivation during rehabilitation.Rehabilitation professionals should consider how they can foster a network of support amongst service users when planning services in remote, rural locations.Rehabilitation professionals should be aware of how hopeful thinking can be facilitated during rehabilitation to support motivation.When reviewing the success of services, or designing new service models, the service users should be consulted on what they would deem as a successful outcome

Repair strategies for assistive technology in low resource settings

PURPOSE: To investigate the practices of repair that exist for users of mobility assistive products in low resource settings, as well as the psychosocial impact that the repair, or non-repair, of these devices has on users' lives. MATERIALS AND METHODS: This article collates data on repair practices and the responses from participants on the topic of repair from studies conducted by the authors across four different low resource settings in Kenya, Uganda, Sierra Leone, and Indonesia. This data was then analyzed to identify the common themes found across geographies. RESULTS: Three major models of repair practice emerged from the data: "Individual or Informal Repair in the Community"; "Local Initiatives"; and "Specialist AT Workshop Repair". Additionally, the wider impact on the participants' lives of "Problems & Concerns with Repair"; "Experiences of Breakages & Frequencies of Repair" and the "Impact of Broken Devices" are explored. CONCLUSIONS: The results of this analysis demonstrate the paramount importance of community-based repair of devices, and how despite this importance, repair is often overlooked in the planning and design of assistive products and services. There is a need to further incorporate and support these informal contributions as part of the formal provision systems of assistive device.IMPLICATIONS FOR REHABILITATIONA lack of available specialist repair services in low resource settings hinders the potential impact of assistive technology provision systems.Community-based repair is the major route by which assistive devices are repaired in low resource settings.Appropriate community-based repair strategies should be incorporated into and supported by the formal assistive technology provision models in order to optimise outcomes.A lack of data on outcomes across the lifecycle of assistive products hinders progress on improving focus on follow-up services - in particular repair & maintenance.By supporting community-based repair, repairs that are inappropriate for that approach could be better directed to specialist repair services

Could Assistive Technology Provision Models Help Pave the Way for More Environmentally Sustainable Models of Product Design, Manufacture and Service in a Post-COVID World?

From multiple studies conducted through the FCDO AT2030 Programme, as well as key literature, we examine whether Assistive Technology (AT) provision models could look towards more sustainable approaches, and by doing this benefit not only the environment, but also address the problems that the current provision systems have. We show the intrinsic links between disability inclusion and the climate crisis, and the particular vulnerability people with disabilities face in its wake. In particular, we discuss how localised circular models of production could be beneficial, facilitating context driven solutions and much needed service elements such as repair and maintenance. Key discussion areas include systems approaches, digital fabrication, repair and reuse, and material recovery. Finally, we look at what needs be done in order to enable these approaches to be implemented. In conclusion, we find that there are distinct parallels between what AT provision models require to improve equitable reliable access, and strategies that could reduce environmental impact and bring economic benefit to local communities. This could allow future AT ecosystems to be key demonstrators of circular models, however further exploration of these ideas is required to make sense of the correct next steps. What is key in all respects, moving forward, is aligning AT provision with sustainability interventions

Repair strategies for assistive technology in low resource settings

PurposeTo investigate the practices of repair that exist for users of mobility assistive products in low resource settings, as well as the psychosocial impact that the repair, or non-repair, of these devices has on users’ lives.Materials and MethodsThis article collates data on repair practices and the responses from participants on the topic of repair from studies conducted by the authors across four different low resource settings in Kenya, Uganda, Sierra Leone, and Indonesia. This data was then analyzed to identify the common themes found across geographies.ResultsThree major models of repair practice emerged from the data: “Individual or Informal Repair in the Community”; “Local Initiatives”; and “Specialist AT Workshop Repair”. Additionally, the wider impact on the participants’ lives of “Problems & Concerns with Repair”; “Experiences of Breakages & Frequencies of Repair” and the “Impact of Broken Devices” are explored.ConclusionsThe results of this analysis demonstrate the paramount importance of community-based repair of devices, and how despite this importance, repair is often overlooked in the planning and design of assistive products and services. There is a need to further incorporate and support these informal contributions as part of the formal provision systems of assistive device.IMPLICATIONS FOR REHABILITATIONA lack of available specialist repair services in low resource settings hinders the potential impact of assistive technology provision systems.Community-based repair is the major route by which assistive devices are repaired in low resource settings.Appropriate community-based repair strategies should be incorporated into and supported by the formal assistive technology provision models in order to optimise outcomes.A lack of data on outcomes across the lifecycle of assistive products hinders progress on improving focus on follow-up services – in particular repair & maintenance.By supporting community-based repair, repairs that are inappropriate for that approach could be better directed to specialist repair services