Towards a Patient-Centered Design of a Cancer Telerehabilitation System.

Successful implementation of telehealth platforms requires a detailed understanding of patient's needs, preferences, and attitudes toward a home-based platform. The goal of this study was to identify patient-centered characteristics of a cancer rehabilitation system based on cognitive evaluation of user interface and semi-structured qualitative interviews. Quantitative and qualitative feedback from 29 patients with metastatic urogenital cancer was collected after using a cancer telerehabilitation system. Heuristic evaluation, cognitive walkthrough, and analysis of qualitative interviews demonstrated a high level of support for the concept of home-based cancer telerehabilitation by cancer patients. Post-task surveys demonstrated sufficient usability and satisfaction scores from the participants. The patients provided valuable and insightful comments on how to further improve the functionality and interface of the platform. Further improvement of the system usability, consistency, and accessibility based on the patient-centered design principles will significantly facilitate the implementation of cancer telerehabilitation in clinical practice.

Machine Learning Approaches for Exercise Exertion Level Classification Using Data from Wearable Physiologic Monitors.

This research aimed to develop a model for real-time prediction of aerobic exercise exertion levels. ECG signals were registered during 16-minute cycling exercises. Perceived ratings of exertion (RPE) were collected each minute from the study participants. Based on the reported RPE, each consecutive minute of the exercise was assigned to the "high exertion" or "low exertion" class. The characteristics of heart rate variability (HRV) in time and frequency domains were used as predictive features. The top ten ranked predictive features were selected using the minimum redundancy maximum relevance (mRMR) algorithm. The support vector machine demonstrated the highest accuracy with an F1 score of 82%.

Assessing Patient Perspectives on Pulmonary Telerehabilitation Using Thematic Analysis of Semi-Structured Qualitative Interviews.

The study was aimed at exploring patients' experiences after the completion of a 12-month pulmonary telerehabilitation (PR) program. Semi-structured qualitative interviews were conducted with 16 COPD patients. The interviews were analyzed using a thematic approach to identify patterns and themes. The patients exhibited high acceptability and satisfaction with the remote PR program and provided valuable input for its improvement. These insights will be used for the implementation of a patient-centered COPD telerehabilitation system.

Towards an Open-Source Platform to Harmonize and Share Research Results from COVID-19 Interventional and Observational Studies.

As the SARS-CoV-2 virus continues to remain a universal threat on a global scale, a large number of COVID-19 clinical trials and observational studies are being conducted and published. Currently, 9,202 COVID-19 clinical trials have been registered on ClinicalTrials.gov and 293,187 COVID-19 articles were indexed in PubMed. To fully capitalize on the voluminous number of publications reporting COVID-19 interventional and observational studies, their results should be freely accessible via an open-source harmonized shared resource. We introduced ReMeDy (https://remedy.mssm.edu/), an intelligent integrative informatics platform aimed to harmonize and cross-link diverse COVID-19 trial outcomes and observational data. We tested the potential of the platform by uploading 52 COVID-19 clinical trials and 48 COVID-19 observational retrospective studies. ReMeDy was validated based on its capability to store and organize diverse data. The next steps include developing a crowdsourcing functionality coupled with automated outcome extraction using natural language processing.

Assessing Patient Perspectives of a Cancer Telerehabilitation Platform Using Thematic Analysis of Semi-Structured Qualitative Interviews.

Cancer-related physical impairments and functional decline affect most patients receiving chemotherapy. Despite evidence that exercise can improve these symptoms, access to exercise-based rehabilitation for cancer patients is limited. Providing telerehabilitation services has shown promising results in alleviating these barriers to access. An in-depth understanding of patient perspectives on cancer telerehabilitation is imperative for the successful development of patient-centered interfaces and functionality. The goal of this study was to explore patients' views and experiences based on a walkthrough of a mobile cancer telerehabilitation system. After the walkthrough, semi-structured qualitative interviews were conducted in 29 cancer patients undergoing chemotherapy. The interviews were analyzed using a thematic analysis approach to deductively identify patterns and themes. Patients responded with approval for the telerehabilitation system, particularly its convenience and ease of use. Patients with reported low technology literacy adapted to the system with minimal problems. The thematic analysis results provided an in-depth understanding of the patients' needs and preferences of the interface and functionality of the telerehabilitation system. These valuable insights will be considered for future development and implementation of a patient-centered cancer telerehab system.

Patient Perspectives on Long-Term Use of a Pulmonary Telerehabilitation Platform: A Qualitative Analysis.

To effectively develop patient-centered interfaces and functionality, it is essential to investigate different viewpoints on pulmonary telerehabilitation. The purpose of this study is to explore the views and experiences of COPD patients after the completion of a 12-month home-based pulmonary telerehabilitation program. Semi-structured qualitative interviews were conducted with 15 COPD patients. The interviews were analyzed using a thematic analysis approach to deductively identify patterns and themes. Patients responded with approval for the telerehabilitation system, particularly for its convenience and ease of use. This study offers a thorough investigation of patient viewpoints when utilizing the telerehabilitation technology. These insightful observations will be considered for future development and implementation of a patient-centered COPD telerehabilitation system to provide support tailored to patient needs, preferences, and expectations.

Automated Classification of Exercise Exertion Levels Based on Real-Time Wearable Physiological Signal Monitoring.

This study aimed to build machine learning (ML) algorithms for the automated classification of cycling exercise exertion levels using data from wearable devices. The best predictive features were selected using the minimum redundancy maximum relevance algorithm (mRMR). Top selected features were then used to build and assess the accuracy of five ML classifiers to predict the level of exertion. The Naïve Bayes showed the best F1 score of 79%. The proposed approach may be used for real-time monitoring of exercise exertion.

Feasibility of a Virtual Reality App to Promote Pulmonary Rehabilitation.

One of the major barriers to joining pulmonary rehabilitation (PR) programs is a lack of awareness about its benefits, combined with overall skepticism about regular exercise among COPD patients. Empowering COPD patients with foundational knowledge about PR may potentially facilitate their decision to join a PR program. A virtual reality (VR) app may serve as an engaging and interactive means to deliver PR education; however, the feasibility of this approach in COPD patients is unknown. The goal of this project was to assess the feasibility of VR-based PR education in COPD patients. Using mixed methods design, the feasibility of the VR app was assessed by evaluating its usability, patient acceptance, and its impact on patient knowledge about PR. The results of the usability assessment showed high user acceptance of the VR system and the ability to successfully operate the VR appliances. The use of the VR education app resulted in a statistically significant increase in patient understanding of the main concepts of pulmonary rehabilitation. Further development and evaluation of VR-based systems for patient engagement and empowerment are warranted.

Qualitative Assessment of Implementation of a Discharge Prediction Tool Using RE-AIM Framework.

The implementation process in the routine clinical care of a new predictive tool based on machine learning algorithms has been investigated using the RE-AIM framework. Semi-structured qualitative interviews have been conducted with a broad range of clinicians to elucidate potential barriers and facilitators of the implementation process across five major domains: Reach, Efficacy, Adoption, Implementation, and Maintenance. The analysis of 23 clinician interviews demonstrated a limited reach and adoption of the new tool and identified areas for improvement in implementation and maintenance. Future implementation efforts of machine learning tools should support the proactive engagement of a wide range of clinical users since the very initiation of the predictive analytics project, provide higher transparency of the underlying algorithms, employ broader onboarding of all potential users on a periodic basis, and collect feedback from clinicians on an ongoing basis.

Development and Evaluation of Wireless Interfaces to Monitor and Control Cycling Exercise During Home Telerehabilitation.

Purpose: This paper focuses on developing and testing three versions of interactive bike (iBikE) interfaces for remote monitoring and control of cycling exercise sessions to promote upper and lower limb rehabilitation. Methods: Two versions of the system, which consisted of a portable bike and a tablet PC, were designed to communicate through either Bluetooth low energy (BLE) or Wi-Fi interfaces for real-time monitoring of exercise progress by both the users and their clinical team. The third version of the iBikE system consisted of a motorized bike and a tablet PC. It utilized conventional Bluetooth to implement remote control of the motorized bike's speed during an exercise session as well as to provide real-time visualization of the exercise progress. We developed three customized tablet PC apps with similar user interfaces but different communication protocols for all the platforms to provide a graphical representation of exercise progress. The same microcontroller unit (MCU), ESP-32, was used in all the systems. Results: Each system was tested in 1-minute exercise sessions at various speeds. To evaluate the accuracy of the measured data, in addition to reading speed values from the iBikE app, the cycling speed of the bikes was measured continuously using a tachometer. The mean differences of averaged RPMs for both data sets were calculated. The calculated values were 0.38 ± 0.03, 0.25 ± 0.27, and 6.7 ± 3.3 for the BLE system, the Wi-Fi system, and the conventional Bluetooth system, respectively. Conclusion: All interfaces provided sufficient accuracy for use in telerehabilitation.

Exploring Determinants of Longevity of Biomedical Databases.

The maintenance of biomedical databases requires ongoing and systematic efforts in keeping them up-to-date which may affect long-term sustainability. Since research has become more reliant on publicly available biomedical data collections, it is important to understand factors affecting their longevity. The aim of this article was to explore potential determinants of biomedical database longevity. To build an analytical dataset, we used Database journal that have been created as an open access platform for presenting biological databases. A stratified analysis of all the original databases published in Database journal between 2009 and 2016 was conducted depending on their accessibility status. Overall, 35% of 518 analyzed databases were not accessible in 2020. We showed that databases with higher citation counts from institutions with higher scientific output were significantly more likely to be currently accessible. Databases from researchers with higher h-index were more likely to be accessible. Further investigation is warranted to identify factors affecting longevity of high impact databases.

NLP-Assisted Pipeline for COVID-19 Core Outcome Set Identification Using ClinicalTrials.gov.

Core outcome sets (COS) are necessary to ensure the systematic collection, metadata analysis and sharing the information across studies. However, development of an area-specific clinical research is costly and time consuming. ClinicalTrials.gov, as a public repository, provides access to a vast collection of clinical trials and their characteristics such as primary outcomes. With the growing number of COVID-19 clinical trials, identifying COSs from outcomes of such trials is crucial. This paper introduces a semi-automatic pipeline that can efficiently identify, aggregate and rank the COS from the primary outcomes of COVID-19 clinical trials. Using Natural language processing (NLP) techniques, our proposed pipeline successfully downloads and processes 5090 trials from all over the world and identifies COVID-19-specific outcomes that appeared in more than 1% of the trials. The top-of-the-list outcomes identified by the pipeline are mortality due to COVID-19, COVID-19 infection rate and COVID-19 symptoms.

Characteristics of Electronic Informed Consent Platforms for Consenting Patients to Research Studies: A Scoping Review.

Informed consent process assures that research study participants are properly informed about the study prior to their consent. Due to the increasing significance of electronic informed consent (eIC) platforms, particularly during the COVID-19 pandemic, we conducted a scoping review of eIC systems to address the following characteristics: 1) technological features of current eIC platforms, 2) eIC platforms usability and efficacy, and 3) areas for future eIC research. We performed a literature search using publically available PubMed repository, where we included studies discussing an eIC platform or multimedia educational module given to patients prior to signing a consent form. In addition, we tracked first author, year of publication, sample size, study location, eIC procedure, methodology, and eIC's comparison to paper consent. Our results showed that with a few noted exceptions, electronic consent improves patient usability, satisfaction, knowledge, and trust scores when compared to traditional paper consent.

Usability Inspection of a Mobile Cancer Telerehabilitation System.

Cancer rehabilitation (CR) has been shown to address physical impairments and progressive disablement experienced by patients with cancer. Access to CR is limited by multiple barriers. Previous studies demonstrated that telemedicine approaches may facilitate access to rehabilitation services however usability and acceptance of cancer telerehabilitation has not been systematically evaluated. This goal of this study was usability inspection of a mobile cancer telerehabilitation system based on cognitive walkthroughs and heuristics evaluations, supplemented by surveys to capture health literacy, patient engagement, and acceptance. The System Usability Scale provided a standardized reference for usability and satisfaction, and the mean result of 83.2±16.9 placed this mobile interface in the top 10th percentile. A semi-structured qualitative interview provided actionable feedback, which informed the next iteration of this project. Overall, this mobile telerehabilitation system was considered by cancer patients easy-to-use, satisfying, and engaging with 91% of participants planning to use it in the future.

A Web-based Platform to Share Harmonized Results from COVID-19 Clinical Studies.

COVID-19 has caused a worldwide pandemic, accompanied by a high number of deaths and hospitalizations. Multiple preventative vaccines and variety of COVID-19 treatments have been developed and explored. This large volume of scientific work led to an extensive number of COVID-19 publications, which resulted in the necessity to standardize, store, share, and investigate research results in a harmonized manner. Attempts to standardize and share COVID-19 research data have been lacking. The purpose of the ReMeDy platform is to provide an intelligent informatics solution of integrating diverse COVID-19 trial outcomes and omics data across COVID-19 research studies. To test the platform, we utilized 48 COVID-19 observational retrospective studies. The robustness of the platform was validated through the ability to efficiently organize the diverse data elements. Next steps include expanding our database through the inclusion of all published COVID-19 studies. ReMeDy is located at https://remedy.mssm.edu/.

Telemonitoring of Home-Based Biking Exercise: Assessment of Wireless Interfaces.

BACKGROUND: Telerehabiliation has been shown to have great potential in expanding access to rehabilitation services, enhancing patients' quality of life, and improving clinical outcomes. Stationary biking exercise can serve as an effective aerobic component of home-based physical rehabilitation programs. Remote monitoring of biking exercise provides necessary safeguards to ensure exercise adherence and safety in patients' homes. The scalability of the current remote monitoring of biking exercise solutions is impeded by the high cost that limits patient access to these services, especially among older adults with chronic health conditions. OBJECTIVE: The aim of this project was to design and test two low-cost wireless interfaces for the telemonitoring of home-based biking exercise. METHODS: We designed an interactive biking system (iBikE) that comprises a tablet PC and a low-cost bike. Two wireless interfaces to monitor the revolutions per minute (RPM) were built and tested. The first version of the iBikE system uses Bluetooth Low Energy (BLE) to send information from the iBikE to the PC tablet, and the second version uses a Wi-Fi network for communication. Both systems provide patients and their clinical teams the capability to monitor exercise progress in real time using a simple graphical representation. The bike can be used for upper or lower limb rehabilitation. We developed two tablet applications with the same graphical user interfaces between the application and the bike sensors but with different communication protocols (BLE and Wi-Fi). For testing purposes, healthy adults were asked to use an arm bike for three separate subsessions (1 minute each at a slow, medium, and fast pace) with a 1-minute resting gap. While collecting speed values from the iBikE application, we used a tachometer to continuously measure the speed of the bikes during each subsession. Collected data were later used to assess the accuracy of the measured data from the iBikE system. RESULTS: Collected RPM data in each subsession (slow, medium, and fast) from the iBikE and tachometer were further divided into 4 categories, including RPM in every 10-second bin (6 bins), RPM in every 20-second bin (3 bins), RPM in every 30-second bin (2 bins), and RPM in each 1-minute subsession (60 seconds, 1 bin). For each bin, the mean difference (iBikE and tachometer) was then calculated and averaged for all bins in each subsession. We saw a decreasing trend in the mean RPM difference from the 10-second to the 1-minute measurement. For the 10-second measurements during the slow and fast cycling, the mean discrepancy between the wireless interface and tachometer was 0.67 (SD 0.24) and 1.22 (SD 0.67) for the BLE iBike, and 0.66 (SD 0.48) and 0.87 (SD 0.91) for the Wi-Fi iBike system, respectively. For the 1-minute measurements during the slow and fast cycling, the mean discrepancy between the wireless interface and tachometer was 0.32 (SD 0.26) and 0.66 (SD 0.83) for the BLE iBike, and 0.21 (SD 0.21) and 0.47 (SD 0.52) for the Wi-Fi iBike system, respectively. CONCLUSIONS: We concluded that a low-cost wireless interface provides the necessary accuracy for the telemonitoring of home-based biking exercise.

Cognitive Testing of an Electronic Consent Platform: Researcher Perspectives.

This study focuses on feedback from domain experts to assess usability and acceptance of the E-Consent electronic consent platform. Quantitative and qualitative data were captured throughout the usability inspection, which was structured around a cognitive walkthrough with heuristics evaluation. Additional surveys measured biobanking knowledge and attitudes and familiarity with informed consent. A semi-structured qualitative interview captured open-ended feedback. 23 researchers of various ages and job titles were included for analysis. The System Usability Scale (SUS) provided a standardized reference for usability and satisfaction, and the mean result of 86.7 corresponds with an 'above average' usability rating in the >90th percentile. Overall, participants believe that electronic consenting using this platform will be faster than previous workflows while enhancing patient understanding, and human rapport is still a key component of the consent process. Expert review has provided valuable insight and actionable information that will be used to further enhance this maturing platform.

A Platform for Integrating and Sharing Cancer Stem Cell Data.

Advancements in cancer research and treatment have highlighted the need for standardization and sharing of cancer stem cell (CSC) data to facilitate research transparency and to promote collaboration within the scientific community. Although previous applications have attempted to gather and disseminate these data, currently no platform organizes the heterogeneous CSC information into a harmonized project-based framework. The aim of our platform, ReMeDy, is to provide an intelligent informatics solution integrating diverse CSC characteristics, outcomes information, and omics data across clinical, preclinical and in vitro studies. These heterogeneous data streams are organized within a multi-modular framework, subjected to a stringent validation by using standardized ontologies, and stored in a searchable format. To test usefulness of our approach for capturing diverse data related to CSCs, we integrated data from 52 publicly-available CSC projects. We validated the robustness of the platform, by efficiently organizing diverse data elements, and demonstrated its potential for promoting future knowledge discovery driven by aggregation of published data. Next steps include expanding number of uploaded CSC projects and developing additional data visualization tools. The platform is accessible through https://remedy.mssm.edu/.

Intelligent Integrative Platform for Sharing Heterogenuous Stem Cell Research Data.

Recent studies demonstrated that comparative analysis of stem cell research data sets originating from multiple studies can produce new information and help with hypotheses generation. Effective approaches for incorporating multiple diverse heterogeneous data sets collected from stem cell projects into a harmonized project-based framework have been lacking. Here, we provide an intelligent informatics solution for integrating comprehensive characterizations of stem cells with research subject and project outcome information. Our platform is the first to seamlessly integrate information from iPSCs and cancer stem cell research into a single platform, using a multi-modular common data element framework. Heterogeneous data is validated using predefined ontologies and stored in a relational database, to ensure data quality and ease of access. Testing was performed using 103 published, publicly-available iPSC and cancer stem cell projects conducted in clinical, preclinical and in vitro evaluations. We validated the robustness of the platform, by seamlessly harmonizing diverse data elements, and demonstrated its potential for knowledge generation through the aggregation and harmonization of data. Future aims of this project include increasing the database size using crowdsourcing and natural language processing functionalities. The platform is publicly available at https://remedy.mssm.edu/.

ReMeDy: a platform for integrating and sharing published stem cell research data with a focus on iPSC trials.

ABSTRACT: Recent regenerative medicine studies have emphasized the need for increased standardization, harmonization and sharing of information related to stem cell product characterization, to help drive these innovative interventions toward public availability and to increase collaboration in the scientific community. Although numerous attempts and numerous databases have been made to manage these data, a platform that incorporates all the heterogeneous data collected from stem cell projects into a harmonized project-based framework is still lacking. The aim of the database, which is described in this study, is to provide an intelligent informatics solution that integrates comprehensive characterization of diverse stem cell product characteristics with research subject and project outcome information. In the resulting platform, heterogeneous data are validated using predefined ontologies and stored in a relational database, to ensure data quality and ease of access. Testing was performed using 51 published, publically available induced pluripotent stem cell projects conducted in clinical, preclinical and in-vitro evaluations. Future aims of this project include further increasing the database size to include all published stem cell trials and develop additional data visualization tools to improve usability. Our testing demonstrated the robustness of the proposed platform, by seamlessly harmonizing diverse common data elements, and the potential of this platform for driving knowledge generation from the aggregation and harmonization of these diverse data. DATABASE URL: https://remedy.mssm.edu/.