scholarly journals User-Centred Design of Multidisciplinary Spatial Data Platforms for Human-History Research

2021 ◽  
Vol 10 (7) ◽  
pp. 467
Author(s):  
Meeli Roose ◽  
Tua Nylén ◽  
Harri Tolvanen ◽  
Outi Vesakoski
Keyword(s):  
Design Process ◽  
Spatial Data ◽  
User Centered Design ◽  
Human Beings ◽  
Human History ◽  
Data Types ◽  
Building Process ◽  
Development Goals ◽  
User Friendly ◽  
User Centered

The role of open spatial data is growing in human-history research. Spatiality can be utilized to bring together and seamlessly examine data describing multiple aspects of human beings and their environment. Web-based spatial data platforms can create equal opportunities to view and access these data. In this paper, we aim at advancing the development of user-friendly spatial data platforms for multidisciplinary research. We conceptualize the building process of such a platform by systematically reviewing a diverse sample of historical spatial data platforms and by piloting a user-centered design process of a multidisciplinary spatial data platform. We outline (1) the expertise needed in organizing multidisciplinary spatial data sharing, (2) data types that platforms should be able to handle, (3) the most useful platform functionalities, and (4) the design process itself. We recommend that the initiative and subject expertise should come from the end-users, i.e., scholars of human history, and all key end-user types should be involved in the design process. We also highlight the importance of geographic expertise in the process, an important link between subject, spatial and technical viewpoints, for reaching a common understanding and common terminology. Based on the analyses, we identify key development goals for spatial data platforms, including full layer management functionalities. Moreover, we identify the main roles in the user-centered design process, main user types and suggest good practices including a multimodal design workshop.

scholarly journals Smartphone App to Self-Monitor Nausea During Pediatric Chemotherapy Treatment: User-Centered Design Process

10.2196/18564 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e18564
Author(s):  
Astrid Eliasen ◽  
Mikkel Kramme Abildtoft ◽  
Niels Steen Krogh ◽  
Catherine Rechnitzer ◽  
Jesper Sune Brok ◽  
...  
Keyword(s):  
Design Process ◽  
Response Rates ◽  
Nausea And Vomiting ◽  
Smartphone App ◽  
User Centered Design ◽  
Pediatric Cancer Patients ◽  
Patient Reported ◽  
User Friendly ◽  
Nausea Severity ◽  
User Centered

Background Nausea and vomiting are common and distressing side effects for children receiving chemotherapy. Limited evidence is available to guide antiemetic recommendations; therefore, prospective and reliable evaluation of antiemetic efficacy is needed. Smartphone apps can be used to effortlessly and precisely collect patient-reported outcomes in real time. Objective Our objective was to develop a smartphone app to monitor nausea and vomiting episodes in pediatric cancer patients aged 0 to 18 years and to test its usability and adherence to its use. Methods We used a user-centered design process and the evolutionary prototype model to develop and evaluate the app. Multidisciplinary group discussions and several rounds of patient feedback and modification were conducted. We translated the validated Pediatric Nausea Assessment Tool to assess nausea severity in children aged 4 to 18 years. The child’s own term for nausea was interactively incorporated in the nausea severity question, with response options expressed as 4 illustrative faces. Parent-reported outcomes were used for children aged 0 to 3 years. Reminders were sent using push notifications in order to ensure high response rates. Children aged 0 to 18 years who were undergoing chemotherapy were recruited from the Department of Pediatric Oncology at Copenhagen University Hospital Rigshospitalet to evaluate the app. Results The app’s most important function was to record nausea severity in children. After assistance from a researcher, children aged 4 to 18 years were able to report their symptoms in the app, and parents were able to report symptoms for their children aged 0 to 3 years. Children (n=20, aged 2.0-17.5 years) and their parents evaluated the app prospectively during a collective total of 60 chemotherapy cycles. They expressed that the app was user-friendly, intuitive, and that the time spent on data entry was fair. The response rates were on average 92%, 93%, and 80% for the day before, the first day of, and the next 3 days after chemotherapy, respectively. Researchers and clinicians were able to obtain an overview of the patient’s chemotherapy dates and responses through a secure and encrypted web-based administrative portal. Data could be downloaded for further analysis. Conclusions The user-friendly app could be used to facilitate future pediatric antiemetic trials and to refine antiemetic treatment during chemotherapy.

scholarly journals Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study

10.2196/16862 ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. e16862
Author(s):  
Curtis Lee Petersen ◽  
Ryan Halter ◽  
David Kotz ◽  
Lorie Loeb ◽  
Summer Cook ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Older Adults ◽  
Natural Language Processing ◽  
Sentiment Analysis ◽  
Design Process ◽  
Language Processing ◽  
User Centered Design ◽  
The Mean ◽  
User Friendly ◽  
User Centered

Background Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process. Objective This study aims to develop a mobile app for a novel device through a user-centered design process with both older adults and clinicians while exploring whether data collected through this process can be used in NLP and sentiment analysis Methods Through a user-centered design process, we conducted semistructured interviews during the development of a geriatric-friendly Bluetooth-connected resistance exercise band app. We interviewed patients and clinicians at weeks 0, 5, and 10 of the app development. Each semistructured interview consisted of heuristic evaluations, cognitive walkthroughs, and observations. We used the Bing sentiment library for a sentiment analysis of interview transcripts and then applied NLP-based latent Dirichlet allocation (LDA) topic modeling to identify differences and similarities in patient and clinician participant interviews. Sentiment was defined as the sum of positive and negative words (each word with a +1 or −1 value). To assess utility, we used quantitative assessment questionnaires—System Usability Scale (SUS) and Usefulness, Satisfaction, and Ease of use (USE). Finally, we used multivariate linear models—adjusting for age, sex, subject group (clinician vs patient), and development—to explore the association between sentiment analysis and SUS and USE outcomes. Results The mean age of the 22 participants was 68 (SD 14) years, and 17 (77%) were female. The overall mean SUS and USE scores were 66.4 (SD 13.6) and 41.3 (SD 15.2), respectively. Both patients and clinicians provided valuable insights into the needs of older adults when designing and building an app. The mean positive-negative sentiment per sentence was 0.19 (SD 0.21) and 0.47 (SD 0.21) for patient and clinician interviews, respectively. We found a positive association with positive sentiment in an interview and SUS score (ß=1.38; 95% CI 0.37 to 2.39; P=.01). There was no significant association between sentiment and the USE score. The LDA analysis found no overlap between patients and clinicians in the 8 identified topics. Conclusions Involving patients and clinicians allowed us to design and build an app that is user friendly for older adults while supporting compliance. This is the first analysis using NLP and usability questionnaires in the quantification of user-centered design of technology for older adults.

scholarly journals Smartphone App to Self-Monitor Nausea During Pediatric Chemotherapy Treatment: User-Centered Design Process (Preprint)

2020 ◽  
Author(s):  
Astrid Eliasen ◽  
Mikkel Kramme Abildtoft ◽  
Niels Steen Krogh ◽  
Catherine Rechnitzer ◽  
Jesper Sune Brok ◽  
...  
Keyword(s):  
Design Process ◽  
Response Rates ◽  
Nausea And Vomiting ◽  
Smartphone App ◽  
User Centered Design ◽  
Pediatric Cancer Patients ◽  
Patient Reported ◽  
User Friendly ◽  
Nausea Severity ◽  
User Centered

BACKGROUND Nausea and vomiting are common and distressing side effects for children receiving chemotherapy. Limited evidence is available to guide antiemetic recommendations; therefore, prospective and reliable evaluation of antiemetic efficacy is needed. Smartphone apps can be used to effortlessly and precisely collect patient-reported outcomes in real time. OBJECTIVE Our objective was to develop a smartphone app to monitor nausea and vomiting episodes in pediatric cancer patients aged 0 to 18 years and to test its usability and adherence to its use. METHODS We used a user-centered design process and the evolutionary prototype model to develop and evaluate the app. Multidisciplinary group discussions and several rounds of patient feedback and modification were conducted. We translated the validated Pediatric Nausea Assessment Tool to assess nausea severity in children aged 4 to 18 years. The child’s own term for nausea was interactively incorporated in the nausea severity question, with response options expressed as 4 illustrative faces. Parent-reported outcomes were used for children aged 0 to 3 years. Reminders were sent using push notifications in order to ensure high response rates. Children aged 0 to 18 years who were undergoing chemotherapy were recruited from the Department of Pediatric Oncology at Copenhagen University Hospital Rigshospitalet to evaluate the app. RESULTS The app’s most important function was to record nausea severity in children. After assistance from a researcher, children aged 4 to 18 years were able to report their symptoms in the app, and parents were able to report symptoms for their children aged 0 to 3 years. Children (n=20, aged 2.0-17.5 years) and their parents evaluated the app prospectively during a collective total of 60 chemotherapy cycles. They expressed that the app was user-friendly, intuitive, and that the time spent on data entry was fair. The response rates were on average 92%, 93%, and 80% for the day before, the first day of, and the next 3 days after chemotherapy, respectively. Researchers and clinicians were able to obtain an overview of the patient’s chemotherapy dates and responses through a secure and encrypted web-based administrative portal. Data could be downloaded for further analysis. CONCLUSIONS The user-friendly app could be used to facilitate future pediatric antiemetic trials and to refine antiemetic treatment during chemotherapy.

scholarly journals Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study (Preprint)

2019 ◽  
Author(s):  
Curtis Lee Petersen ◽  
Ryan Halter ◽  
David Kotz ◽  
Lorie Loeb ◽  
Summer Cook ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Older Adults ◽  
Natural Language Processing ◽  
Sentiment Analysis ◽  
Design Process ◽  
Language Processing ◽  
User Centered Design ◽  
The Mean ◽  
User Friendly ◽  
User Centered

BACKGROUND Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process. OBJECTIVE This study aims to develop a mobile app for a novel device through a user-centered design process with both older adults and clinicians while exploring whether data collected through this process can be used in NLP and sentiment analysis METHODS Through a user-centered design process, we conducted semistructured interviews during the development of a geriatric-friendly Bluetooth-connected resistance exercise band app. We interviewed patients and clinicians at weeks 0, 5, and 10 of the app development. Each semistructured interview consisted of heuristic evaluations, cognitive walkthroughs, and observations. We used the Bing sentiment library for a sentiment analysis of interview transcripts and then applied NLP-based latent Dirichlet allocation (LDA) topic modeling to identify differences and similarities in patient and clinician participant interviews. Sentiment was defined as the sum of positive and negative words (each word with a +1 or −1 value). To assess utility, we used quantitative assessment questionnaires—System Usability Scale (SUS) and Usefulness, Satisfaction, and Ease of use (USE). Finally, we used multivariate linear models—adjusting for age, sex, subject group (clinician vs patient), and development—to explore the association between sentiment analysis and SUS and USE outcomes. RESULTS The mean age of the 22 participants was 68 (SD 14) years, and 17 (77%) were female. The overall mean SUS and USE scores were 66.4 (SD 13.6) and 41.3 (SD 15.2), respectively. Both patients and clinicians provided valuable insights into the needs of older adults when designing and building an app. The mean positive-negative sentiment per sentence was 0.19 (SD 0.21) and 0.47 (SD 0.21) for patient and clinician interviews, respectively. We found a positive association with positive sentiment in an interview and SUS score (ß=1.38; 95% CI 0.37 to 2.39; <i>P</i>=.01). There was no significant association between sentiment and the USE score. The LDA analysis found no overlap between patients and clinicians in the 8 identified topics. CONCLUSIONS Involving patients and clinicians allowed us to design and build an app that is user friendly for older adults while supporting compliance. This is the first analysis using NLP and usability questionnaires in the quantification of user-centered design of technology for older adults.

Ergonomics as Mediator within the Product Design Process

2000 ◽  
Vol 44 (8) ◽  
pp. 20-23 ◽  
Author(s):  
Ralph Bruder
Keyword(s):  
Product Development ◽  
Product Design ◽  
Design Process ◽  
User Centered Design ◽  
Human Centered Design ◽  
Mediating Role ◽  
Product Design Process ◽  
User Friendly ◽  
User Centered

As a consequence of an increasing complexity of products using procedures a human-centered-design process is more and more important. This thesis can be based on the success of user friendly products on market but also by looking at new regulations concerning human-centered design (e.g. pr EN-ISO 13407). Within an user-centered design process there is a need for a continuos balancing between interests of users and producers. This mediating role can be fulfilled by persons with an ergonomic background. The potentiality of ergonomic for the initialization, accompaniment and evaluation of an user-centered design process was demonstrated within the product development of a new electronic pipette.

scholarly journals A User Centered Methodology for the Design of Smart Apparel for Older Users

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2804
Author(s):  
Silvia Imbesi ◽  
Sofia Scataglini
Keyword(s):  
Design Process ◽  
Quality Function Deployment ◽  
Well Being ◽  
Comparison Method ◽  
User Centered Design ◽  
Smart Clothing ◽  
Older Users ◽  
Smart Garments ◽  
General Response ◽  
User Centered

Smart clothing plays a big role to foster innovation and to. boost health and well-being, improving the quality of the life of people, especially when addressed to niche users with particular needs related to their health. Designing smart apparel, in order to monitor physical and physiological functions in older users, is a crucial asset that user centered design is exploring, balancing needs expressed by the users with technological requirements related to the design process. In this paper, the authors describe a user centered methodology for the design of smart garments based on the evaluation of users’ acceptance of smart clothing. This comparison method can be considered as similar to a simplified version of the quality function deployment tool, and is used to evaluate the general response of each garment typology to different categories of requirements, determining the propensity of the older user to the utilization of the developed product. The suggested methodology aims at introducing in the design process a tool to evaluate and compare developed solutions, reducing complexity in design processes by providing a tool for the comparison of significant solutions, correlating quantitative and qualitative factors.

Developing Clinical Decision Support System for Sleep Staging Tasks by Formulating Explanations from Artificial Intelligence: User-Centered Design and Evaluation. (Preprint)

2021 ◽  
Author(s):  
Jeonghwan Hwang ◽  
Taeheon Lee ◽  
Honggu Lee ◽  
Seonjeong Byun
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Design Process ◽  
Clinical Decision Support ◽  
User Study ◽  
Clinical Decision ◽  
Sleep Staging ◽  
User Centered Design ◽  
Iterative Design ◽  
User Centered

BACKGROUND Despite the unprecedented performances of deep learning algorithms in clinical domains, full reviews of algorithmic predictions by human experts remain mandatory. Under these circumstances, artificial intelligence (AI) models are primarily designed as clinical decision support systems (CDSSs). However, from the perspective of clinical practitioners, the lack of clinical interpretability and user-centered interfaces block the adoption of these AI systems in practice. OBJECTIVE The aim of this study was to develop an AI-based CDSS for assisting polysomnographic technicians in reviewing AI-predicted sleep staging results. This study proposed and evaluated a CDSS that provides clinically sound explanations for AI predictions in a user-centered fashion. METHODS User needs for the system were identified during interviews with polysomnographic technicians. User observation sessions were conducted to understand the workflow of the practitioners during sleep scoring. Iterative design process was performed to ensure easy integration of the tool into clinical workflows. Then, we evaluated the system with polysomnographic technicians. We measured the improvements in sleep staging accuracies after adopting our tool and assessed qualitatively how the participants perceived and used the tool. RESULTS The user study revealed that technicians desire explanations relevant to key electroencephalogram (EEG) patterns for sleep staging when assessing the correctness of the AI predictions. Here, technicians could evaluate whether AI models properly locate and use those patterns during prediction. Based on this, information in AI models that is closely related to sleep EEG patterns was formulated and visualized during the iterative design process. Furthermore, we developed a different visualization strategy for each pattern based on the way the technicians interpreted the EEG recordings with these patterns during their workflows. Generally, the tool evaluation results from the nine polysomnographic technicians were positive. Quantitatively, technicians achieved better classification performances after reviewing the AI-generated predictions with the proposed system; classification accuracies measured with Macro-F1 scores improved from 60.20 to 62.71. Qualitatively, participants reported that the provided information from the tool effectively supported them, and they were able to develop notable adoption strategies for the tool. CONCLUSIONS Our findings indicate that formulating clinical explanations for automated predictions using the information in the AI with a user-centered design process is an effective strategy for developing a CDSS for sleep staging.

scholarly journals User-centered design of a patient’s work station for haptic robot-based telerehabilitation after stroke

2017 ◽  
Vol 3 (1) ◽  
pp. 39-43 ◽  
Author(s):  
Ekaterina Ivanova ◽  
Michael Minge ◽  
Henning Schmidt ◽  
Manfred Thüring ◽  
Jörg Krüger
Keyword(s):  
Hospital Discharge ◽  
Design Process ◽  
Neurological Rehabilitation ◽  
User Centered Design ◽  
Work Station ◽  
Rehabilitation Training ◽  
Robotic Therapy ◽  
Rehabilitation Hospitals ◽  
Early Phases ◽  
User Centered

Abstract:Robotic therapy devices have been an important part of clinical neurological rehabilitation for several years. Until now such devices are only available for patients receiving therapy inside rehabilitation hospitals. Since patients should continue rehabilitation training after hospital discharge at home, intelligent robotic rehab devices could help to achieve this goal. This paper presents therapeutic requirements and early phases of the user-centered design process of the patient’s work station as part of a novel robot-based system for motor telerehabilitation.

Methodical Spatial Database Design with Topological Polygon Structures

2012 ◽  
Vol 3 (1) ◽  
pp. 21-30
Author(s):  
Jean Damascène Mazimpaka
Keyword(s):  
Design Process ◽  
Spatial Data ◽  
Spatial Databases ◽  
Early Stage ◽  
Spatial Database ◽  
Database Design ◽  
Integrity Constraints ◽  
Data Types ◽  
Data Infrastructure ◽  
Database Development

Spatial databases form the foundation for a Spatial Data Infrastructure (SDI). For this, a spatial database should be methodically developed to accommodate its role in SDI. It is desirable to have an approach to spatial database development that considers maintenance from the early stage of database design and in a flexible way. Moreover, there is a lack of a mechanism to capture topological relations of spatial objects during the design process. This paper presents an approach that integrates maintenance of topological integrity constraints into the whole spatial database development cycle. The approach is based on the concept of Abstract Data Types. A number of topological classes have been identified and modelling primitives developed for them. Topological integrity constraints are embedded into maintenance functions associated with the topological classes. A semi-automatic transformation process has been developed following the principles of Model Driven Architecture to simplify the design process.

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