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Le Stum M, Clave A, Adzinyo Agbemanyole K, Stindel E, Le Goff-Pronost M. A pilot study on preferences from surgeons to deal with an innovative customized and connected knee prosthesis - A discret choice experiment. Heliyon 2024; 10:e30041. [PMID: 38784553 PMCID: PMC11112283 DOI: 10.1016/j.heliyon.2024.e30041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/17/2024] [Accepted: 04/18/2024] [Indexed: 05/25/2024] Open
Abstract
Background To address the increasing global demand for Total Knee Arthroplasty and reduce the need for revisions, several technologies combining 3D planning and artificial intelligence have emerged. These innovations aim to enhance customization, improve component positioning accuracy and precision. The integration of these advancements paves the way for the development of personalized and connected knee implant. Questions/purposes These groundbreaking advancements may necessitate changes in surgical practices. Hence, it is important to comprehend surgeons' intentions in integrating these technologies into their routine procedures. Our study aims to assess how surgeons' preferences will affect the acceptability of using this new implant and associated technologies within the entire care chain. Methods We employed a Discrete Choice Experiment, a predictive technique mirroring real-world healthcare decisions, to assess surgeons' trade-off evaluations and preferences. Results A total of 90 experienced surgeons, performing a significant number of procedures annually (mostly over 51) answered. Analysis indicates an affinity for technology but limited interest in integrating digital advancements like preoperative software and robotics. However, they are receptive to practice improvements and considering the adoption of future sensors. Conclusions In conclusion, surgeons prefer customized prostheses via augmented reality, accepting extra cost. Embedded sensor technology is deemed premature by them.
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Affiliation(s)
- Mathieu Le Stum
- Université de Brest, UBO, LATIM, UMR 1101, 22 rue Camille Desmoulins, 29200, Brest, France
- Institut National de la Santé et de la Recherche Médicale, Inserm, LaTIM, UMR 1101, 22 rue Camille Desmoulins, 29200, Brest, France
| | - Arnaud Clave
- Service d'orthopédie, Clinique Saint George, 2 Avenue de Rimiez, 06100, Nice, France
| | - Koffi Adzinyo Agbemanyole
- Institut Mines-Telecom, IMT Atlantique, LATIM, UMR 1101, M@rsouin, 655 Av. du Technopôle, 29280, Plouzané, France
| | - Eric Stindel
- Université de Brest, UBO, LATIM, UMR 1101, 22 rue Camille Desmoulins, 29200, Brest, France
- Centre Hospitalo-Universitaire de Brest, CHU Brest, LATIM, UMR 1101, 2 Avenue Foch, 29200, Brest, France
| | - Myriam Le Goff-Pronost
- Institut Mines-Telecom, IMT Atlantique, LATIM, UMR 1101, M@rsouin, 655 Av. du Technopôle, 29280, Plouzané, France
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Bérubé C, Lehmann VF, Maritsch M, Kraus M, Feuerriegel S, Wortmann F, Züger T, Stettler C, Fleisch E, Kocaballi AB, Kowatsch T. Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial. JMIR Hum Factors 2024; 11:e42823. [PMID: 38194257 PMCID: PMC10813835 DOI: 10.2196/42823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/06/2023] [Accepted: 12/04/2023] [Indexed: 01/10/2024] Open
Abstract
BACKGROUND Hypoglycemia is a frequent and acute complication in type 1 diabetes mellitus (T1DM) and is associated with a higher risk of car mishaps. Currently, hypoglycemia can be detected and signaled through flash glucose monitoring or continuous glucose monitoring devices, which require manual and visual interaction, thereby removing the focus of attention from the driving task. Hypoglycemia causes a decrease in attention, thereby challenging the safety of using such devices behind the wheel. Here, we present an investigation of a hands-free technology-a voice warning that can potentially be delivered via an in-vehicle voice assistant. OBJECTIVE This study aims to investigate the feasibility of an in-vehicle voice warning for hypoglycemia, evaluating both its effectiveness and user perception. METHODS We designed a voice warning and evaluated it in 3 studies. In all studies, participants received a voice warning while driving. Study 0 (n=10) assessed the feasibility of using a voice warning with healthy participants driving in a simulator. Study 1 (n=18) assessed the voice warning in participants with T1DM. Study 2 (n=20) assessed the voice warning in participants with T1DM undergoing hypoglycemia while driving in a real car. We measured participants' self-reported perception of the voice warning (with a user experience scale in study 0 and with acceptance, alliance, and trust scales in studies 1 and 2) and compliance behavior (whether they stopped the car and reaction time). In addition, we assessed technology affinity and collected the participants' verbal feedback. RESULTS Technology affinity was similar across studies and approximately 70% of the maximal value. Perception measure of the voice warning was approximately 62% to 78% in the simulated driving and 34% to 56% in real-world driving. Perception correlated with technology affinity on specific constructs (eg, Affinity for Technology Interaction score and intention to use, optimism and performance expectancy, behavioral intention, Session Alliance Inventory score, innovativeness and hedonic motivation, and negative correlations between discomfort and behavioral intention and discomfort and competence trust; all P<.05). Compliance was 100% in all studies, whereas reaction time was higher in study 1 (mean 23, SD 5.2 seconds) than in study 0 (mean 12.6, SD 5.7 seconds) and study 2 (mean 14.6, SD 4.3 seconds). Finally, verbal feedback showed that the participants preferred the voice warning to be less verbose and interactive. CONCLUSIONS This is the first study to investigate the feasibility of an in-vehicle voice warning for hypoglycemia. Drivers find such an implementation useful and effective in a simulated environment, but improvements are needed in the real-world driving context. This study is a kickoff for the use of in-vehicle voice assistants for digital health interventions.
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Affiliation(s)
- Caterina Bérubé
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Vera Franziska Lehmann
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Martin Maritsch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Mathias Kraus
- School of Business, Economics and Society, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nürnberg, Germany
| | - Stefan Feuerriegel
- School of Management, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Felix Wortmann
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Centre for Digital Health Interventions, Institute of Technology Management, University of St Gallen, St Gallen, Switzerland
| | - Thomas Züger
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Endocrinology and Metabolic Diseases, Kantonsspital Olten, Olten, Switzerland
| | - Christoph Stettler
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Elgar Fleisch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Centre for Digital Health Interventions, Institute of Technology Management, University of St Gallen, St Gallen, Switzerland
| | - A Baki Kocaballi
- School of Computer Science, University of Technology Sydney, Sydney, Australia
| | - Tobias Kowatsch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Centre for Digital Health Interventions, Institute of Technology Management, University of St Gallen, St Gallen, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St Gallen, St Gallen, Switzerland
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Festerling J, Siraj I, Malmberg LE. Exploring children's exposure to voice assistants and their ontological conceptualizations of life and technology. AI & SOCIETY 2022:1-28. [PMID: 36276897 PMCID: PMC9580440 DOI: 10.1007/s00146-022-01555-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 09/05/2022] [Indexed: 11/30/2022]
Abstract
Digital Voice Assistants (DVAs) have become a ubiquitous technology in today's home and childhood environments. Inspired by (Bernstein and Crowley, J Learn Sci 17:225-247, 2008) original study (n = 60, age 4-7 years) on how children's ontological conceptualizations of life and technology were systematically associated with their real-world exposure to robotic entities, the current study explored this association for children in their middle childhood (n = 143, age 7-11 years) and with different levels of DVA-exposure. We analyzed correlational survey data from 143 parent-child dyads who were recruited on 'Amazon Mechanical Turk' (MTurk). Children's ontological conceptualization patterns of life and technology were measured by asking them to conceptualize nine prototypical organically living and technological entities (e.g., humans, cats, smartphones, DVAs) with respect to their biology, intelligence, and psychology. Their ontological conceptualization patterns were then associated with their DVA-exposure and additional control variables (e.g., children's technological affinity, demographic/individual characteristics). Compared to biology and psychology, intelligence was a less differentiating factor for children to differentiate between organically living and technological entities. This differentiation pattern became more pronounced with technological affinity. There was some evidence that children with higher DVA-exposure differentiated more rigorously between organically living and technological entities on the basis of psychology. To the best of our knowledge, this is the first study exploring children's real-world exposure to DVAs and how it is associated with their conceptual understandings of life and technology. Findings suggest although psychological conceptualizations of technology may become more pronounced with DVA-exposure, it is far from clear such tendencies blur ontological boundaries between life and technology from children's perspective. Supplementary Information The online version contains supplementary material available at 10.1007/s00146-022-01555-3.
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Affiliation(s)
- Janik Festerling
- Department of Education, University of Oxford, 15 Norham Gardens, Oxford, OX2 6PY UK
| | - Iram Siraj
- Department of Education, University of Oxford, 15 Norham Gardens, Oxford, OX2 6PY UK
| | - Lars-Erik Malmberg
- Department of Education, University of Oxford, 15 Norham Gardens, Oxford, OX2 6PY UK
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Virtual Reality-Based Interface for Advanced Assisted Mobile Robot Teleoperation. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12126071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
This work proposes a new interface for the teleoperation of mobile robots based on virtual reality that allows a natural and intuitive interaction and cooperation between the human and the robot, which is useful for many situations, such as inspection tasks, the mapping of complex environments, etc. Contrary to previous works, the proposed interface does not seek the realism of the virtual environment but provides all the minimum necessary elements that allow the user to carry out the teleoperation task in a more natural and intuitive way. The teleoperation is carried out in such a way that the human user and the mobile robot cooperate in a synergistic way to properly accomplish the task: the user guides the robot through the environment in order to benefit from the intelligence and adaptability of the human, whereas the robot is able to automatically avoid collisions with the objects in the environment in order to benefit from its fast response. The latter is carried out using the well-known potential field-based navigation method. The efficacy of the proposed method is demonstrated through experimentation with the Turtlebot3 Burger mobile robot in both simulation and real-world scenarios. In addition, usability and presence questionnaires were also conducted with users of different ages and backgrounds to demonstrate the benefits of the proposed approach. In particular, the results of these questionnaires show that the proposed virtual reality based interface is intuitive, ergonomic and easy to use.
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Schrader L, Vargas Toro A, Konietzny S, Rüping S, Schäpers B, Steinböck M, Krewer C, Müller F, Güttler J, Bock T. Advanced Sensing and Human Activity Recognition in Early Intervention and Rehabilitation of Elderly People. JOURNAL OF POPULATION AGEING 2020. [DOI: 10.1007/s12062-020-09260-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
AbstractAgeing is associated with a decline in physical activity and a decrease in the ability to perform activities of daily living, affecting physical and mental health. Elderly people or patients could be supported by a human activity recognition (HAR) system that monitors their activity patterns and intervenes in case of change in behavior or a critical event has occurred. A HAR system could enable these people to have a more independent life.In our approach, we apply machine learning methods from the field of human activity recognition (HAR) to detect human activities. These algorithmic methods need a large database with structured datasets that contain human activities. Compared to existing data recording procedures for creating HAR datasets, we present a novel approach, since our target group comprises of elderly and diseased people, who do not possess the same physical condition as young and healthy persons.Since our targeted HAR system aims at supporting elderly and diseased people, we focus on daily activities, especially those to which clinical relevance in attributed, like hygiene activities, nutritional activities or lying positions. Therefore, we propose a methodology for capturing data with elderly and diseased people within a hospital under realistic conditions using wearable and ambient sensors. We describe how this approach is first tested with healthy people in a laboratory environment and then transferred to elderly people and patients in a hospital environment.We also describe the implementation of an activity recognition chain (ARC) that is commonly used to analyse human activity data by means of machine learning methods and aims to detect activity patterns. Finally, the results obtained so far are presented and discussed as well as remaining problems that should be addressed in future research.
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