A scoping review of digital fabrication techniques applied to prosthetics and orthotics: Part 1 of 2-Prosthetics.

BACKGROUND: Traditionally, the manufacture of prostheses is time-consuming and labor-intensive. One possible route to improving access and quality of these devices is the digitalizing of the fabrication process, which may reduce the burden of manual labor and bring the potential for automation that could help unblock access to assistive technologies globally. OBJECTIVES: To identify where there are gaps in the literature that are creating barriers to decision-making on either appropriate uptake by clinical teams or on the needed next steps in research that mean these technologies can continue on a pathway to maturity. STUDY DESIGN: Scoping literature review. METHODS: A comprehensive search was completed in the following databases: Allied and Complementary Medicine Database, MEDLINE, Embase, Global Health Archive, CINAHL Plus, Cochrane Library, Web of Science, Association for Computing Machinery, Institute of Electrical and Electronics Engineers, and Engineering Village, resulting in 3487 articles to be screened. RESULTS: After screening, 130 lower limb prosthetic articles and 117 upper limb prosthetic articles were included in this review. Multiple limitations in the literature were identified, particularly a lack of long-term, larger-scale studies; research into the training requirements for these technologies and the necessary rectification processes; and a high range of variance of production workflows and materials which makes drawing conclusions difficult. CONCLUSIONS: These limitations create a barrier to adequate evidence-based decision-making for clinicians, technology developers, and wider policymakers. Increased collaboration between academia, industry, and clinical teams across more of the pathway to market for new technologies could be a route to addressing these gaps.

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.

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.

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.

Assistive Technology Use and Provision During COVID-19: Results From a Rapid Global Survey.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has impacted all segments of society, but it has posed particular challenges for the inclusion of persons with disabilities, those with chronic illness and older people regarding their participation in daily life. These groups often benefit from assistive technology (AT) and so it is important to understand how use of AT may be affected by or may help to mitigate the impacts of COVID-19. Objective: The objectives of this study were to explore the how AT use and provision have been affected during the initial stages of the COVID-19 pandemic, and how AT policies and systems may be made more resilient based on lessons learned during this global crisis. METHODS: This study was a rapid, international online qualitative survey in the 6 United Nations (UN) languages (English, French, Spanish, Russian, Arabic, Mandarin Chinese) facilitated by extant World Health Organization (WHO) and International Disability Alliance networks. Themes and subthemes of the qualitative responses were identified using Braun and Clarke's 6-phase analysis. RESULTS: Four primary themes were identified in in the data: Disruption of Services, Insufficient Emergency Preparedness, Limitations in Existing Technology, and Inadequate Policies and Systems. Subthemes were identified within each theme, including subthemes related to developing resilience in AT systems, based on learning from the pandemic. CONCLUSION: COVID-19 has disrupted the delivery of AT services, primarily due to infection control measures resulting in lack of provider availability and diminished one-to-one services. This study identified a need for stronger user-centred development of funding policies and infrastructures that are more sustainable and resilient, best practices for remote service delivery, robust and accessible tools and systems, and increased capacity of clients, caregivers, and clinicians to respond to pandemic and other crisis situations.

A review of innovation strategies and processes to improve access to AT: Looking ahead to open innovation ecosystems.

It is essential to understand the strategies and processes which are deployed currently across the Assistive Technology (AT) space toward measuring innovation. The main aim of this paper is to identify functional innovation strategies and processes which are being or can be deployed in the AT space to increase access to AT globally. We conducted a scoping review of innovation strategies and processes in peer-reviewed literature databases and complemented this by identifying case studies demonstrating innovation strategies. The review includes WHO world region, publication year, AT type and a sector analysis against the Systems-Market for Assistive and Related Technologies Framework. We analyzed the case studies and interviews using thematic analysis. We included 91 papers out of 3,127 after review along with 72 case studies. Our results showed that product innovations were more prevalent than provision or supply innovations across papers and case studies. Case studies yielded two themes: open innovation (OI); radical and disruptive innovation. Financial instruments which encourage OI are needed and we recommend pursuing OI for AT innovation. Embedding AT within larger societal missions will be key to success governments and investors need to understand what AT is and their translational socioeconomic value.

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.