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A shift in the traditional technocentric view of medical device design to a human-centered one is needed to bridge existing translational gaps and improve health equity. To ensure the successful and equitable adoption of health technology innovations, engineers must think beyond the device and the direct end user and must seek a more holistic understanding of broader stakeholder needs and the intended context of use early in a design process. The objectives of this review article are ( a) to provide rationale for the need to incorporate meaningful stakeholder analysis and contextual investigation in health technology development and biomedical engineering pedagogy, ( b) to review existing frameworks and human- and equity-centered approaches to stakeholder engagement and contextual investigation for improved adoption of innovative technologies, and ( c) to present case studyexamples of medical device design that apply these approaches to bridge the gaps between biomedical engineers and the contexts for which they are designing. 

Abstract BackgroundRecently, machine learning techniques have been applied to data collected from inertial measurement units to automatically assess balance, but rely on hand-engineered features. We explore the utility of machine learning to automatically extract important features from inertial measurement unit data for balance assessment. FindingsTen participants with balance concerns performed multiple balance exercises in a laboratory setting while wearing an inertial measurement unit on their lower back. Physical therapists watched video recordings of participants performing the exercises and rated balance on a 5-point scale. We trained machine learning models using different representations of the unprocessed inertial measurement unit data to estimate physical therapist ratings. On a held-out test set, we compared these learned models to one another, to participants’ self-assessments of balance, and to models trained using hand-engineered features. Utilizing the unprocessed kinematic data from the inertial measurement unit provided significant improvements over both self-assessments and models using hand-engineered features (AUROC of 0.806 vs. 0.768, 0.665). ConclusionsUnprocessed data from an inertial measurement unit used as input to a machine learning model produced accurate estimates of balance performance. The ability to learn from unprocessed data presents a potentially generalizable approach for assessing balance without the need for labor-intensive feature engineering, while maintaining comparable model performance. 

Abstract Stakeholder engagement with prototypes during the front-end phases of medical device design can support problem identification, problem definition, and early concept generation. This study examined what prototypes were leveraged to engage specific types of stakeholders during front-end medical device design. Analysis of semi-structured interviews with 22 design practitioners in the medical device industry revealed some common associations of prototype choice for particular stakeholders. A few associations are highlighted: designers engaged users with physical three-dimensional (3D) prototypes, financial decision-makers with physical 3D and two-dimensional (2D) prototypes, government and regulatory stakeholders with 2D prototypes, and expert advisors with digital 3D prototypes. The rationale provided by practitioners revealed the intentional selection of prototype form for specific stakeholder engagements. 

Abstract Prototypes have the potential to provoke discussion and to encourage stakeholders to play an active role during design engagements in the front-end phases of a design process. However, detailed descriptions of stakeholder engagement strategies in front-end design are lacking. The aim of this research study was to understand how design practitioners prepare and manage stakeholders for engagements involving prototypes in the front-end phases of a medical device design process. Design practitioners at companies developing mechanical and electromechanical medical devices for use in low- and middle-income countries were interviewed following a semi-structured interview guide. Interview transcripts were analysed, and inductive codes were developed. The findings suggest that design practitioners manage the group composition of stakeholders, review the project and prototype(s) with stakeholders at the start of the engagement, and show the progress of prototypes to stakeholders over multiple engagements. These strategies shed light on the importance of handling interpersonal relationships during stakeholder engagement with prototypes.