Accurate Prediction of Knee Angles during Open-Chain Rehabilitation Exercises Using a Wearable Array of Nanocomposite Stretch Sensors

In this work, a knee sleeve is presented for application in physical therapy applications relating to knee rehabilitation. The device is instrumented with sixteen piezoresistive sensors to measure knee angles during exercise, and can support at-home rehabilitation methods. The development of the device is presented. Testing was performed on eighteen subjects, and knee angles were predicted using a machine learning regressor. Subject-specific and device-specific models are analyzed and presented. Subject-specific models average root mean square errors of 7.6 and 1.8 degrees for flexion/extension and internal/external rotation, respectively. Device-specific models average root mean square errors of 12.6 and 3.5 degrees for flexion/extension and internal/external rotation, respectively. The device presented in this work proved to be a repeatable, reusable, low-cost device that can adequately model the knee's flexion/extension and internal/external rotation angles for rehabilitation purposes.

Statistical Analysis of the Consistency of HRV Analysis Using BCG or Pulse Wave Signals

Ballistocardiography (BCG) is considered a good alternative to HRV analysis with its non-contact and unobtrusive acquisition characteristics. However, consensus about its validity has not yet been established. In this study, 50 healthy subjects (26.2 ± 5.5 years old, 22 females, 28 males) were invited. Comprehensive statistical analysis, including Coefficients of Variation (CV), Lin’s Concordance Correlation Coefficient (LCCC), and Bland-Altman analysis (BA ratio), were utilized to analyze the consistency of BCG and ECG signals in HRV analysis. If the methods gave different answers, the worst case was taken as the result. Measures of consistency such as Mean, SDNN, LF gave good agreement (the absolute value of CV difference < 2%, LCCC > 0.99, BA ratio < 0.1) between J-J (BCG) and R-R intervals (ECG). pNN50 showed moderate agreement (the absolute value of CV difference < 5%, LCCC > 0.95, BA ratio < 0.2), while RMSSD, HF, LF/HF indicated poor agreement (the absolute value of CV difference ≥ 5% or LCCC ≤ 0.95 or BA ratio ≥ 0.2). Additionally, the R-R intervals were compared with P-P intervals extracted from the pulse wave (PW). Except for pNN50, which exhibited poor agreement in this comparison, the performances of the HRV indices estimated from the PW and the BCG signals were similar.

Wearable Photoplethysmography for Cardiovascular Monitoring

Smart wearables provide an opportunity to monitor health in daily life and are emerging as potential tools for detecting cardiovascular disease (CVD). Wearables such as fitness bands and smartwatches routinely monitor the photoplethysmogram signal, an optical measure of the arterial pulse wave that is strongly influenced by the heart and blood vessels. In this survey, we summarize the fundamentals of wearable photoplethysmography and its analysis, identify its potential clinical applications, and outline pressing directions for future research in order to realize its full potential for tackling CVD.

The Bumpy Road to Stem Cell Therapies: Rational Design of Surface Topographies to Dictate Stem Cell Mechanotransduction and Fate

Cells sense and respond to a variety of physical cues from their surrounding microenvironment, and these are interpreted through mechanotransductive processes to inform their behavior. These mechanisms have particular relevance to stem cells, where control of stem cell proliferation, potency, and differentiation is key to their successful application in regenerative medicine. It is increasingly recognized that surface micro- and nanotopographies influence stem cell behavior and may represent a powerful tool with which to direct the morphology and fate of stem cells. Current progress toward this goal has been driven by combined advances in fabrication technologies and cell biology. Here, the capacity to generate precisely defined micro- and nanoscale topographies has facilitated the studies that provide knowledge of the mechanotransducive processes that govern the cellular response as well as knowledge of the specific features that can drive cells toward a defined differentiation outcome. However, the path forward is not fully defined, and the "bumpy road" that lays ahead must be crossed before the full potential of these approaches can be fully exploited. This review focuses on the challenges and opportunities in applying micro- and nanotopographies to dictate stem cell fate for regenerative medicine. Here, key techniques used to produce topographic features are reviewed, such as photolithography, block copolymer lithography, electron beam lithography, nanoimprint lithography, soft lithography, scanning probe lithography, colloidal lithography, electrospinning, and surface roughening, alongside their advantages and disadvantages. The biological impacts of surface topographies are then discussed, including the current understanding of the mechanotransductive mechanisms by which these cues are interpreted by the cells, as well as the specific effects of surface topographies on cell differentiation and fate. Finally, considerations in translating these technologies and their future prospects are evaluated.

Data-Driven Classification of Human Movements in Virtual Reality-Based Serious Games: Preclinical Rehabilitation Study in Citizen Science

BACKGROUND

Sustained engagement is essential for the success of telerehabilitation programs. However, patients' lack of motivation and adherence could undermine these goals. To overcome this challenge, physical exercises have often been gamified. Building on the advantages of serious games, we propose a citizen science-based approach in which patients perform scientific tasks by using interactive interfaces and help advance scientific causes of their choice. This approach capitalizes on human intellect and benevolence while promoting learning. To further enhance engagement, we propose performing citizen science activities in immersive media, such as virtual reality (VR).

OBJECTIVE

This study aims to present a novel methodology to facilitate the remote identification and classification of human movements for the automatic assessment of motor performance in telerehabilitation. The data-driven approach is presented in the context of a citizen science software dedicated to bimanual training in VR. Specifically, users interact with the interface and make contributions to an environmental citizen science project while moving both arms in concert.

METHODS

In all, 9 healthy individuals interacted with the citizen science software by using a commercial VR gaming device. The software included a calibration phase to evaluate the users' range of motion along the 3 anatomical planes of motion and to adapt the sensitivity of the software's response to their movements. During calibration, the time series of the users' movements were recorded by the sensors embedded in the device. We performed principal component analysis to identify salient features of movements and then applied a bagged trees ensemble classifier to classify the movements.

RESULTS

The classification achieved high performance, reaching 99.9% accuracy. Among the movements, elbow flexion was the most accurately classified movement (99.2%), and horizontal shoulder abduction to the right side of the body was the most misclassified movement (98.8%).

CONCLUSIONS

Coordinated bimanual movements in VR can be classified with high accuracy. Our findings lay the foundation for the development of motion analysis algorithms in VR-mediated telerehabilitation.

Current trends and opportunities in the methodology of electrodermal activity measurement

Electrodermal activity (EDA) has been measured in the laboratory since the late 1800s. Although the influence of sudomotor nerve activity and the sympathetic nervous system on EDA is well established, the mechanisms underlying EDA signal generation are not completely understood. Owing to simplicity of instrumentation and modern electronics, these measurements have recently seen a transfer from the laboratory to wearable devices, sparking numerous novel applications while bringing along both challenges and new opportunities. In addition to developments in electronics and miniaturization, current trends in material technology and manufacturing have sparked innovations in electrode technologies, and trends in data science such as machine learning and sensor fusion are expanding the ways that measurement data can be processed and utilized. Although challenges remain for the quality of wearable EDA measurement, ongoing research and developments may shorten the quality gap between wearable EDA and standardized recordings in the laboratory. In this topical review, we provide an overview of the basics of EDA measurement, discuss the challenges and opportunities of wearable EDA, and review recent developments in instrumentation, material technology, signal processing, modeling and data science tools that may advance the field of EDA research and applications over the coming years.

Web Portals for Patients With Chronic Diseases: Scoping Review of the Functional Features and Theoretical Frameworks of Telerehabilitation Platforms

Background

The COVID-19 pandemic has required an increased need for rehabilitation activities applicable to patients with chronic diseases. Telerehabilitation has several advantages, including reducing clinic visits by patients vulnerable to infectious diseases. Digital platforms are often used to assist rehabilitation services for patients in remote settings. Although web portals for medical use have existed for years, the technology in telerehabilitation remains a novel method.

Objective

This scoping review investigated the functional features and theoretical approaches of web portals developed for telerehabilitation in patients with chronic diseases.

Methods

PubMed and Web of Science were reviewed to identify articles associated with telerehabilitation. Of the 477 nonduplicate articles reviewed, 35 involving 14 portals were retrieved for the scoping review. The functional features, targeted diseases, and theoretical approaches of these portals were studied.

Results

The 14 portals targeted patients with chronic obstructive pulmonary disease, cardiovascular, osteoarthritis, multiple sclerosis, cystic fibrosis diseases, and stroke and breast cancer survivors. Monitoring/data tracking and communication functions were the most common, followed by exercise instructions and diary/self-report features. Several theoretical approaches, behavior change techniques, and motivational techniques were found to be utilized.

Conclusions

The web portals could unify and display multiple types of data and effectively provide various types of information. Asynchronous correspondence was more favorable than synchronous, real-time interactions. Data acquisition often required assistance from other digital tools. Various functions with patient-centered principles, behavior change strategies, and motivational techniques were observed for better support shifting to a healthier lifestyle. These findings suggested that web portals for telerehabilitation not only provided entrance into rehabilitation programs but also reinforced participant-centered treatment, adherence to rehabilitation, and lifestyle changes over time.

Mobile Contactless Fingerprint Recognition: Implementation, Performance and Usability Aspects

This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1360 contactless and contact-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our contactless scheme and the contact-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method. Based on our experimental results, we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of contactless fingerprint recognition are summarized.

Relationship between physical capacity and depression in heart failure patients undergoing hybrid comprehensive telerehabilitation vs. usual care: subanalysis from the TELEREH-HF Randomized Clinical Trial

AIMS

The hybrid comprehensive telerehabilitation (HCTR) consisting of telecare (with psychological telesupport), telerehabilitation, and remote monitoring of cardiovascular implantable electronic devices might be an option to improve both physical capacity and depressive symptoms. The aim of the study was to investigate the influence of HCTR on depressive symptoms and physical capacity in heart failure (HF) patients in comparison with usual care (UC).

METHODS AND RESULTS

The present analysis formed part of a multicentre, randomized trial that enrolled 850 HF patients (New York Heart Association I-III, left ventricular ejection fraction ≤ 40%). Patients were randomized 1:1 to HCTR or UC. Patients underwent an HCTR programme (1 week in hospital and 8 weeks at home; exercise training 5 times weekly) or UC with observation. The Beck Depression Inventory II (BDI-II) score (cut point for depression ≥ 14) was used to assess depression and the physical capacity was measured by peak oxygen consumption (peak VO2; mL/kg/min). Measurements were made before and after 9-week intervention/observation (HCTR/UC group). Both groups were comparable in terms of demographic and clinical characteristics. In HCTR group, at entry, 23% of the sample obtained BDI-II scores ≥14 vs. 27.5% in UC group. There were no significant differences between groups regarding ΔBDI-II score (P = 0.992) after 9-week HCTR/UC. There was a significant improvement in physical capacity only in the HCTR group in both patients with (P = 0.033) and without (P < 0.001) depression.

CONCLUSIONS

In HF patients, HCTR provided similar reduction of depressive symptoms as UC. HCTR resulted in a significant improvement in physical capacity in patients with and without depression.

Digital health use in latent tuberculosis infection care: A systematic review

PURPOSE

With one-quarter of the world's population estimated to have latent tuberculosis infection (LTBI), it is important that the drop-outs from the LTBI cascade of care are minimized. Digital health technology could play an important role in case detection and treatment adherence. This study aims to evaluate the use and impact of digital health technology in LTBI care.

METHODS

A systematic literature search was conducted on six electronic databases from database inception until May 31st 2021. Studies that reported on the clinical use or economic analysis of digital health technology for LTBI care were included. Two investigators independently evaluated, extracted relevant studies, and assessed the risk of bias of using the Cochrane tools. The studies were synthesized qualitatively.

RESULTS

Fifteen articles describing 14 studies were included. Voice and/or textual reminders and synchronous video call to improve LTBI treatment adherence were the most commonly examined digital health interventions. Other interventions examined the use of mobile phones to improve the number of patients who returned for tuberculin skin test follow-up measurement (screening retention) and eLearning videos to enhance health literacy in LTBI care. The economic analysis supported the use of textual reminders in LTBI treatment as a cost-effective option for widescale implantation.

CONCLUSIONS

Despite limited evidence on the effects of digital health technologies in LTBI, available studies suggest they are at least equivalent to current practice. This means digital health can potentially supplement current practice, to constantly monitor and engage with people undergoing LTBI screening or treatment, as an initiative to ensure the provision of continuous and optimal care to all LTBI-affected individuals.

A Decade in Review: A Systematic Review of Virtual Reality Interventions for Emotional Disorders

Research is increasingly demonstrating the therapeutic benefits of virtual reality interventions for various mental health conditions, though these rarely translate from research to application in clinical settings. This systematic review aims to examine the efficacy of current virtual reality interventions for emotional disorders, with a focus on clinical and technological features that influence translation of treatments from research to clinical practice. A comprehensive systematic literature search was conducted following PRISMA guidelines, for studies including the application of a virtual reality intervention to a clinical population of adults with an emotional disorder. Thirty-seven eligible studies were identified, appraised, and assessed for bias. Treatment effects were typically large across studies, with virtual reality being considered an efficacious treatment modality for various anxiety disorders and post-traumatic stress disorder. Virtual reality interventions were typically used for delivering exposure in cognitive behavioural therapy approaches. Considerable variability was seen in cost, technological specifications, degree of therapist involvement, delivery format, dosage, duration, and frequency of treatment. Suboptimal methodological rigour was identified in some studies. Remote use of virtual reality was rare, despite increasing options for in home use. Virtual reality interventions have the potential to overcome barriers to care and better meet the needs of consumers. Future research should examine the efficacy of virtual reality for treatment of depressive disorders and obsesive compulsive disorder. Improved methodological reporting and development of transdiagnostic and remotely delivered virtual reality interventions, will likely increase the translation of this treatment modality.

Enhanced location tracking in sensor fusion-assisted virtual reality micro-manipulation environments

Virtual reality (VR) technology plays a significant role in many biomedical applications. These VR scenarios increase the valuable experience of tasks requiring great accuracy with human subjects. Unfortunately, commercial VR controllers have large positioning errors in a micro-manipulation task. Here, we propose a VR-based framework along with a sensor fusion algorithm to improve the microposition tracking performance of a microsurgical tool. To the best of our knowledge, this is the first application of Kalman filter in a millimeter scale VR environment, by using the position data between the VR controller and an inertial measuring device. This study builds and tests two cases: (1) without sensor fusion tracking and (2) location tracking with active sensor fusion. The static and dynamic experiments demonstrate that the Kalman filter can provide greater precision during micro-manipulation in small scale VR scenarios.

Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11344 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (mean bias -0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (mean bias 0.20 ms, p < 0.001) and nocturnal recordings (mean bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

RiIG Modeled WCP Image-Based CNN Architecture and Feature-Based Approach in Breast Tumor Classification from B-Mode Ultrasound

This study presents two new approaches based on Weighted Contourlet Parametric (WCP) images for the classification of breast tumors from B-mode ultrasound images. The Rician Inverse Gaussian (RiIG) distribution is considered for modeling the statistics of ultrasound images in the Contourlet transform domain. The WCP images are obtained by weighting the RiIG modeled Contourlet sub-band coefficient images. In the feature-based approach, various geometrical, statistical, and texture features are shown to have low ANOVA p-value, thus indicating a good capacity for class discrimination. Using three publicly available datasets (Mendeley, UDIAT, and BUSI), it is shown that the classical feature-based approach can yield more than 97% accuracy across the datasets for breast tumor classification using WCP images while the custom-made convolutional neural network (CNN) can deliver more than 98% accuracy, sensitivity, specificity, NPV, and PPV values utilizing the same WCP images. Both methods provide superior classification performance, better than those of several existing techniques on the same datasets.

Accelerating Hyperparameter Tuning in Machine Learning for Alzheimer's Disease With High Performance Computing

Driven by massive datasets that comprise biomarkers from both blood and magnetic resonance imaging (MRI), the need for advanced learning algorithms and accelerator architectures, such as GPUs and FPGAs has increased. Machine learning (ML) methods have delivered remarkable prediction for the early diagnosis of Alzheimer's disease (AD). Although ML has improved accuracy of AD prediction, the requirement for the complexity of algorithms in ML increases, for example, hyperparameters tuning, which in turn, increases its computational complexity. Thus, accelerating high performance ML for AD is an important research challenge facing these fields. This work reports a multicore high performance support vector machine (SVM) hyperparameter tuning workflow with 100 times repeated 5-fold cross-validation for speeding up ML for AD. For demonstration and evaluation purposes, the high performance hyperparameter tuning model was applied to public MRI data for AD and included demographic factors such as age, sex and education. Results showed that computational efficiency increased by 96%, which helped to shed light on future diagnostic AD biomarker applications. The high performance hyperparameter tuning model can also be applied to other ML algorithms such as random forest, logistic regression, xgboost, etc.

Relationships between Heart Rate Variability, Sleep Duration, Cortisol and Physical Training in Young Athletes

The aims of the current study were to examine the relationships between heart rate variability (HRV), salivary cortisol, sleep duration and training in young athletes. Eight athletes (16 ± 1 years) were monitored for 7 weeks during training and competition seasons. Subjects were training for endurance-based winter sports (cross-country skiing and biathlon). Training was divided into two zones (K1, easy training and K2, hard training). Heart rate and blood lactate during submaximal running tests (SRT), as well as cortisol, sleep duration and nocturnal HRV (RMSSD), were determined every other week. HRV and cortisol levels were correlated throughout the 7-week period (r = -0.552, P = 0.01), with the strongest correlation during week 7 (r = -0.879, P = 0.01). The relative changes in K1 and HRV showed a positive correlation from weeks 1-3 (r = 0.863, P = 0.006) and a negative correlation during weeks 3-5 (r = -0.760, P = 0.029). The relative change in sleep during weeks 1-3 were negatively correlated with cortisol (r = -0.762, P = 0.028) and K2 (r = -0.762, P = 0.028). In conclusion, HRV appears to reflect the recovery of young athletes during high loads of physical and/or physiological stress. Cortisol levels also reflected this recovery, but significant change required a longer period than HRV, suggesting that cortisol may be less sensitive to stress than HRV. Moreover, our results indicated that during the competition season, recovery for young endurance athletes increased in duration and additional sleep may be beneficial.

Augmenting Perceived Softness of Haptic Proxy Objects Through Transient Vibration and Visuo-Haptic Illusion in Virtual Reality

In this article, we investigate the effects of active transient vibration and visuo-haptic illusion to augment the perceived softness of haptic proxy objects. We introduce a system combining active transient vibration at the fingertip with visuo-haptic illusions. In our hand-held device, a voice coil actuator transmits active transient vibrations to the index fingertip, while a force sensor measures the force applied on passive proxy objects to create visuo-haptic illusions in virtual reality. We conducted three user studies to understand both the vibrotactile effect and its combined effect with visuo-haptic illusions. A preliminary study confirmed that active transient vibrations can intuitively alter the perceived softness of a proxy object. Our first study demonstrated that those same active transient vibrations can generate different perceptions of softness depending on the material of the proxy object used. In our second study, we evaluated the combination of active transient vibration and visuo-haptic illusion, and found that both significantly influence perceived softness, with with the visuo-haptic effect being dominant. Our third study further investigated the vibrotactile effect while controlling for the visuo-haptic illusion. The combination of these two methods allows users to effectively perceive various levels of softness when interacting with haptic proxy objects.

Assessment of Virtual Reality as a Didactic Resource in Higher Education

Given that the university teachers with more experience in the use of virtual reality are those corresponding to the areas of Health Sciences and of Engineering and Architecture, this article analyzes the assessment these teachers make about virtual reality as a teaching resource in their respective disciplines. The study uses a questionnaire that assesses the technical aspects and future projection of virtual reality, its drawbacks and the perception of the different dimensions of the participants’ knowledge about virtual reality and its didactic employability. The questionnaire was answered by a sample of 423 university teachers of different genders, ages, academic level and teaching experience, whose teaching activity is developed in various Latin American universities in the area of Health Sciences or in the area of Engineering/Architecture. Their answers have been analyzed descriptively and Spearman’s r statistics and the Multifactor ANOVA test have been used to verify the existence of significant differences in their evaluations for the different variables considered, cross-referencing them with the field of knowledge. Within the main results, gaps by area, years of teaching experience and academic level in the participants’ evaluations have been identified and discussed.

Feasibility of a Sensor-Controlled Digital Game for Heart Failure Self-management: Randomized Controlled Trial

BACKGROUND

Poor self-management of heart failure (HF) contributes to devastating health consequences. Our innovative sensor-controlled digital game (SCDG) integrates data from sensors to trigger game rewards, progress, and feedback based on the real-time behaviors of individuals with HF.

OBJECTIVE

The aim of this study is to compare daily weight monitoring and physical activity behavior adherence by older adults using an SCDG intervention versus a sensors-only intervention in a feasibility randomized controlled trial.

METHODS

English-speaking adults with HF aged 55 years or older who owned a smartphone and could walk unassisted were recruited from Texas and Oklahoma from November 2019 to August 2020. Both groups were given activity trackers and smart weighing scales to track behaviors for 12 weeks. The feasibility outcomes of recruitment, retention, intervention engagement, and satisfaction were assessed. In addition to daily weight monitoring and physical activity adherence, the participants' knowledge, functional status, quality of life, self-reported HF behaviors, motivation to engage in behaviors, and HF-related hospitalization were also compared between the groups at baseline and at 6, 12, and 24 weeks.

RESULTS

A total of 38 participants with HF-intervention group (IG; 19/38, 50%) and control group (CG; 19/38, 50%)-were enrolled in the study. Of the 38 participants, 18 (47%) were women, 18 (47%) were aged 65 years or older, 21 (55%) had been hospitalized with HF in the past 6 months, and 29 (76%) were White. Furthermore, of these 38 participants, 31 (82%)-IG (15/19, 79%) and CG (16/19, 84%)-had both weight monitoring and physical activity data at the end of 12 weeks, and 27 (71%)-IG (14/19, 74%) and CG (13/19, 68%)-participated in follow-up assessments at 24 weeks. For the IG participants who installed the SCDG app (15/19, 79%), the number of days each player opened the game app was strongly associated with the number of days the player engaged in weight monitoring (r=0.72; P=.04) and the number of days with physical activity step data (r=0.9; P<.001). The IG participants who completed the satisfaction survey (13/19, 68%) reported that the SCDG was easy to use. Trends of improvement in daily weight monitoring and physical activity in the IG, as well as within-group improvements in HF functional status, quality of life, knowledge, self-efficacy, and HF hospitalization in both groups, were observed in this feasibility trial.

CONCLUSIONS

Playing an SCDG on smartphones was feasible and acceptable for older adults with HF for motivating daily weight monitoring and physical activity. A larger efficacy trial of the SCDG intervention will be needed to validate trends of improvement in daily weight monitoring and physical activity behaviors.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03947983; https://clinicaltrials.gov/ct2/show/NCT03947983.

Tests for tuberculosis infection: landscape analysis

BACKGROUND

Only the tuberculin skin test (TST) and two interferon-γ release assays (IGRAs), QuantiFERON-TB Gold In-Tube and T-SPOT.TB, are currently endorsed by the World Health Organization as tests for tuberculosis (TB) infection. While IGRAs are more specific than the TST, they require sophisticated laboratory infrastructure and are costly to perform. However, both types of tests have limited performance to predict development of active TB. Tests with improved predictive performance and operational characteristics are needed.

METHODS

We reviewed the current landscape of tests for TB infection identified through a web-based survey targeting diagnostic manufacturers globally.

RESULTS

We identified 20 tests for TB infection: 15 in vitro tests and five skin tests. 13 of the in vitro tests are whole-blood IGRAs and 14 use early secreted antigenic target 6 (ESAT-6) and culture filtrate protein 10 (CFP-10), with or without additional antigens. 10 of the tests are based on assays other than an ELISA, such as a fluorescent lateral flow assay that requires less manual operation and shorter assay time and hence is more suitable for decentralisation compared with the existing IGRAs. Four of the five skin tests use ESAT-6 and CFP-10 proteins, while the remaining test uses a new antigen that is specific to Mycobacterium tuberculosis complex.

CONCLUSIONS

New tests have the potential to improve accuracy, operational characteristics and end-user access to tests for TB infection. However, published data in various populations and settings are limited for most new tests. Evaluation of these new tests in a standardised design would facilitate their endorsement and programmatic scale-up.

Effects of Telerehabilitation Interventions on Heart Failure Management (2015-2020): Scoping Review

Background

Heart failure is one of the world’s most frequently diagnosed cardiovascular diseases. An important element of heart failure management is cardiac rehabilitation, the goal of which is to improve patients’ recovery, functional capacity, psychosocial well-being, and health-related quality of life. Patients in cardiac rehabilitation may lack sufficient motivation or may feel that the rehabilitation process does not meet their individual needs. One solution to these challenges is the use of telerehabilitation. Although telerehabilitation has been available for several years, it has only recently begun to be utilized in heart failure studies. Especially within the past 5 years, we now have several studies focusing on the effectiveness of telerehabilitation for heart failure management, all with varying results. Based on a review of these studies, this paper offers an assessment of the effectiveness of telerehabilitation as applied to heart failure management.

Objective

The aim of this scoping review was to assess the effects of telerehabilitation in the management of heart failure by systematically reviewing the available scientific literature within the period from January 1, 2015, to December 31, 2020.

Methods

The literature search was carried out using PubMed and EMBASE. After duplicates were removed, 77 articles were screened and 12 articles were subsequently reviewed. The review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for scoping reviews) guidelines. As measures of the effectiveness of telerehabilitation, the following outcomes were used: patients’ quality of life, physical capacity, depression or anxiety, and adherence to the intervention.

Results

A total of 12 articles were included in this review. In reviewing the effects of telerehabilitation for patients with heart failure, it was found that 4 out of 6 randomized controlled trials (RCTs), a single prospective study, and 4 out of 5 reviews reported increased quality of life for patients. For physical capacity, 4 RCTs and 3 systematic reviews revealed increased physical capacity. Depression or depressive symptoms were reported as being reduced in 1 of the 6 RCTs and in 2 of the 5 reviews. Anxiety or anxiety-related symptoms were reported as reduced in only 1 review. High adherence to the telerehabilitation program was reported in 4 RCTs and 4 reviews. It should be mentioned that some of the reviewed articles described the same studies although they employed different outcome measures.

Conclusions

It was found that there is a tendency toward improvement in patients’ quality of life and physical capacity when telerehabilitation was used in heart failure management. The outcome measures of depression, anxiety, and adherence to the intervention were found to be positive. Additional research is needed to determine more precise and robust effects of telerehabilitation.

Pay attention to doctor-patient dialogues: Multi-modal knowledge graph attention image-text embedding for COVID-19 diagnosis

The sudden increase in coronavirus disease 2019 (COVID-19) cases puts high pressure on healthcare services worldwide. At this stage, fast, accurate, and early clinical assessment of the disease severity is vital. In general, there are two issues to overcome: (1) Current deep learning-based works suffer from multimodal data adequacy issues; (2) In this scenario, multimodal (e.g., text, image) information should be taken into account together to make accurate inferences. To address these challenges, we propose a multi-modal knowledge graph attention embedding for COVID-19 diagnosis. Our method not only learns the relational embedding from nodes in a constituted knowledge graph but also has access to medical knowledge, aiming at improving the performance of the classifier through the mechanism of medical knowledge attention. The experimental results show that our approach significantly improves classification performance compared to other state-of-the-art techniques and possesses robustness for each modality from multi-modal data. Moreover, we construct a new COVID-19 multi-modal dataset based on text mining, consisting of 1393 doctor-patient dialogues and their 3706 images (347 X-ray + 2598 CT + 761 ultrasound) about COVID-19 patients and 607 non-COVID-19 patient dialogues and their 10754 images (9658 X-ray + 494 CT + 761 ultrasound), and the fine-grained labels of all. We hope this work can provide insights to the researchers working in this area to shift the attention from only medical images to the doctor-patient dialogue and its corresponding medical images.

Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease

BACKGROUND

Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD).

METHODS

Thirty-nine participants with CVD, Alzheimer's disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson's disease, or amyotrophic lateral sclerosis (median age 68 (45-83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance.

RESULTS

Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17-22 min/day), with significant differences between some locations (p = 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (p < 0.001) and there was a small but significant increase in non-wear over the collection period (p = 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners.

CONCLUSION

A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.

Short-Time Impedance Spectroscopy Using a Mode-Switching Nonsinusoidal Oscillator: Applicability to Biological Tissues and Continuous Measurement

Herein, we propose an impedance spectroscopy method using a mode-switching nonsinusoidal oscillator and apply this method for measuring the impedance of biological tissues and continuous impedance measurement. To obtain impedance spectra over a wide frequency range, we fabricated a novel nonsinusoidal oscillator incorporating binary counters and analog switches. This oscillator could periodically switch oscillation frequency through the mode switching of the feedback resistor. From the oscillation waveform at each oscillation frequency of this circuit (oscillator), we determined the impedance spectrum of a measured object using the discrete-time Fourier transform. Subsequently, we obtained the broad impedance spectrum of the measured object by merging odd-order harmonic spectral components up to the 19th order for each oscillation frequency. From the measured spectrum, the resistive and capacitive components of the circuit simulating bioimpedance were estimated with high accuracy. Moreover, the proposed method was used to measure the impedance of porcine myocardium; changes in the impedance spectrum of the myocardial tissue due to coagulation could be measured. Furthermore, rapid variations in the resistance value of a CdS photocell could be continuously measured using the proposed method.

Immersive Virtual Reality and Vestibular Rehabilitation in Multiple Sclerosis: Case Report

Background

Dizziness and imbalance are common and disabling symptoms in patients with multiple sclerosis (MS) and are caused by a central, peripheral, or mixed vestibulopathy. Central vestibular disorder is the most frequently reported vestibular problem in the MS population due to demyelination. Vestibular rehabilitation ameliorates these symptoms and their repercussions and improves quality of life. Immersive virtual reality (VRi) is an emerging tool in this field; however, no previous research has been performed studying its effects in MS.

Objective

The aim of this study was to apply a VRi vestibular training protocol to a patient with MS and assess the effects induced by the experimental intervention.

Methods

This case study included a 54-year-old woman with relapsing-remitting MS. We developed a standardized VRi exercise protocol for vestibular rehabilitation based on the gold-standard Cawthorne-Cooksey vestibular training protocol. The 20-session intervention was made up of 10 initial sessions and 10 advanced sessions. Each 50-minute session was performed two to three times per week for 7 weeks. Four evaluations were carried out over the study period: at baseline (T0), between initial and advances phases (T1), postintervention (T2), and 1 month after the experimental procedure (T3). The research outcomes were dizziness, balance, gait, impact of fatigue, quality of life, repercussions in muscular tone, and usability of the head-mounted display device.

Results

After implementing the VRi vestibular protocol, improvements were seen in the following patient parameters: Dizziness Handicap Inventory score (62 points at T0; 4 points at T2); Berg Balance Scale score (47 points at T0; 54 points at T2); instrumented Timed Up and Go time (8.35 seconds at T0; 5.57 seconds at T2); muscular tone of the erector spinae, rectus femoris, and soleus; Modified Fatigue Impact Scale score (61 points at T0; 37 points at T2); and Multiple Sclerosis Quality of Life-54 values (67.16% in the physical health area at T2; 33.56% in the mental health area at T2). The patient rated the usability of the system as 90%, based on the System Usability Scale, and gave the system a grade of A.

Conclusions

Although further research is needed, this study provided initial evidence that the first VRi vestibular protocol for the MS population can improve dizziness, balance, gait, impact of fatigue, quality of life, and muscular tone through an exergame intervention. This study may help establish a standardized VRi protocol for vestibular rehabilitation.

Comparative Study Qualitative and Quantitative Techniques in the Study of Occlusion

Introduction

The wide variety of methods for recording occlusal contacts and the contradictory data on the interpretation of the obtained markings provoked us to make a comparative laboratory study between different occlusal indicators.

Purpose

Evaluation of a qualitative and quantitative method for registration of occlusal contacts in static occlusion in laboratory conditions.

Materials and Methods

In completion of the objective, we designed an apparatus for registration of the occlusal contacts (AROC) in static occlusion which is used, corresponding to the MIP in clinical conditions. The occlusal indicators that were included in the study were articulating paper 100 μ, articulating foil 12 μ, and T-Scan Novus system with a sensor thickness of 100 μ. The collected primary statistical information was entered and processed with the statistical package SPSS Statistics 19.0, and the graphs were prepared using Microsoft Office 2019. We performed descriptive statistical analysis in this study. Comparisons were performed using one-way analysis of variance (ANOVA), Student's t-test, and Pearson coefficient method. For a significance level, p < 0.05 was chosen. Result and Discussion. With quality occlusal indicators, it is possible only to visually determine the size, number, and intensity of the marked contacts. After the statistical processing of the obtained data on the number of registered contacts, a significant difference is found in the number of contacts of certain teeth (18, 24, 25, 28, 38, 35, 34, 33, 44, 45, and 48) registered with articulating paper and articulating foil. The maximum force that is reported during the study with the T-Scan system is 93.72% and the forces in the right half of the dentition are 51.7% and in the left 48.9%. To visualize the location of the registered occlusal contacts with the system, it is intraoral to use a quality indicator and we recommend the use of articulating foil.

Conclusion

Based on findings from the current in vitro simulation, we can conclude that the type of occlusal indicator influences the registration of contacts, and therefore, we propose as a method of choice to achieve a balanced occlusion in clinical practice to combine the use of one conventional and one quantitative method.

Advanced Bioelectrical Signal Processing Methods: Past, Present, and Future Approach-Part III: Other Biosignals

Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient digital signal processing methods are presented. This paper covers the following bioelectrical signals and their processing methods: electromyography (EMG), electroneurography (ENG), electrogastrography (EGG), electrooculography (EOG), electroretinography (ERG), and electrohysterography (EHG).

An optimal feature enriched region of interest (ROI) extraction for periocular biometric system

With the onset of COVID-19 pandemic, wearing of face mask became essential and the face occlusion created by the masks deteriorated the performance of the face biometric systems. In this situation, the use of periocular region (region around the eye) as a biometric trait for authentication is gaining attention since it is the most visible region when masks are used. One important issue in periocular biometrics is the identification of an optimal size periocular ROI which contains enough features for authentication. The state of the art ROI extraction algorithms use fixed size rectangular ROI calculated based on some reference points like center of the iris or centre of the eye without considering the shape of the periocular region of an individual. This paper proposes a novel approach to extract optimum size periocular ROIs of two different shapes (polygon and rectangular) by using five reference points (inner and outer canthus points, two end points and the midpoint of eyebrow) in order to accommodate the complete shape of the periocular region of an individual. The performance analysis on UBIPr database using CNN models validated the fact that both the proposed ROIs contain enough information to identify a person wearing face mask.

Au nanoparticle concentration study in hybrid plasmonic microlasers

In this paper, the concentration effects of Au nanoparticles placed in dye-doped polymeric spherical microlasers are investigated. The microlasers (average diameter of ∼293µm) are made with a mixture of UV curable polymer named Norland Blocking Adhesive (NBA) and Rhodamine 6 G. Four different ratios (between the Au nanoparticles and the NBA solutions) are investigated here, namely, 1000, 2000, 3000, and 4000 ratios. The Au nanoparticles (size of ∼5nm) are randomly scattered within the microlaser. The light is collected via a multimode optical fiber, ending to a spectrometer/CCD camera. It is found that the 3000 ratio case exhibited the lowest energy threshold value and the highest photonic emission slope. The 4000 ratio (lowest concentration) exhibited a behavior that was very similar to a microlasers with no Au particles. In terms of longevity of the laser modes, the 3000 ratio case exhibited the most stable emission, although the laser mode disappeared at an earlier time. The emission of the 2000 ratio case dropped drastically after a few seconds but increased after that before dropping again; in this case, the TE and TM laser modes were found to be in competition with each other due to the partial overlapping of the plasmonic emission with some of the resonant cavity modes and due to the thermal expansion effect. The quality factor was found to be of the same order of magnitude for all cases (∼10⁴). Ultimately, this work allows us to select the optimum microlaser's configuration in terms of Au nanoparticle concentration as well as laser mode emission and longevity for different mechanical and biomedical sensing applications.

Feasibility and Effects of Virtual Reality Motor-Cognitive Training in Community-Dwelling Older People With Cognitive Frailty: Pilot Randomized Controlled Trial

BACKGROUND

Cognitive frailty refers to the coexistence of physical frailty and cognitive impairment, and is associated with many adverse health outcomes. Although cognitive frailty is prevalent in older people, motor-cognitive training is effective at enhancing cognitive and physical function. We proposed a virtual reality (VR) simultaneous motor-cognitive training program, which allowed older people to perform daily activities in a virtual space mimicking real environments.

OBJECTIVE

We aimed to (1) explore the feasibility of offering VR simultaneous motor-cognitive training to older people with cognitive frailty and (2) compare its effects with an existing motor-cognitive training program in the community on the cognitive function and physical function of older people with cognitive frailty.

METHODS

A two-arm (1:1), assessor-blinded, parallel design, randomized controlled trial was employed. The eligibility criteria for participants were: (1) aged ≥60 years, (2) community dwelling, and (3) with cognitive frailty. Those in the intervention group received cognitive training (ie, cognitive games) and motor training (ie, cycling on an ergometer) simultaneously on a VR platform, mimicking the daily living activities of older people. Those in the control group received cognitive training (ie, cognitive games) on tablet computers and motor training (ie, cycling on the ergometer) sequentially on a non-VR platform. Both groups received a 30-minute session twice a week for 8 weeks. Feasibility was measured by adherence, adverse outcomes, and successful learning. The outcomes were cognitive function, physical frailty level, and walking speed.

RESULTS

Seventeen participants were recruited and randomized to either the control group (n=8) or intervention group (n=9). At baseline, the median age was 74.0 years (IQR 9.5) and the median Montreal Cognitive Assessment score was 20.0 (IQR 4.0). No significant between-group differences were found in baseline characteristics except in the number of chronic illnesses (P=.04). At postintervention, the intervention group (Z=-2.67, P=.01) showed a significantly larger improvement in cognitive function than the control group (Z=-1.19, P=.24). The reduction in physical frailty in the intervention group (Z=-1.73, P=.08) was similar to that in the control group (Z=-1.89, P=.06). Improvement in walking speed based on the Timed Up-and-Go test was moderate in the intervention group (Z=-0.16, P=.11) and greater in the control group (Z=-2.52, P=.01). The recruitment rate was acceptable (17/33, 52%). Both groups had a 100% attendance rate. The intervention group had a higher completion rate than the control group. Training was terminated for one participant (1/9, 11%) due to minimal VR sickness (Virtual Reality Sickness Questionnaire score=18.3/100). Two participants (2/8, 25%) in the control group withdrew due to moderate leg pain. No injuries were observed in either group.

CONCLUSIONS

This study provides preliminary evidence that the VR simultaneous motor-cognitive training is effective at enhancing the cognitive function of older people with cognitive frailty. The effect size on frailty was close to reaching a level of significance and was similar to that observed in the control group. VR training is feasible and safe for older people with cognitive frailty.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04467216; https://clinicaltrials.gov/ct2/show/NCT04467216.

Recommendations for the Design and Implementation of Virtual Reality for Acquired Brain Injury Rehabilitation: Systematic Review

BACKGROUND

Virtual reality (VR) is increasingly being used for the assessment and treatment of impairments arising from acquired brain injuries (ABIs) due to perceived benefits over traditional methods. However, no tailored options exist for the design and implementation of VR for ABI rehabilitation and, more specifically, traumatic brain injury (TBI) rehabilitation. In addition, the evidence base lacks systematic reviews of immersive VR use for TBI rehabilitation. Recommendations for this population are important because of the many complex and diverse impairments that individuals can experience.

OBJECTIVE

This study aims to conduct a two-part systematic review to identify and synthesize existing recommendations for designing and implementing therapeutic VR for ABI rehabilitation, including TBI, and to identify current evidence for using immersive VR for TBI assessment and treatment and to map the degree to which this literature includes recommendations for VR design and implementation.

METHODS

This review was guided by PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). A comprehensive search of 11 databases and gray literature was conducted in August 2019 and repeated in June 2020. Studies were included if they met relevant search terms, were peer-reviewed, were written in English, and were published between 2009 and 2020. Studies were reviewed to determine the level of evidence and methodological quality. For the first part, qualitative data were synthesized and categorized via meta-synthesis. For the second part, findings were analyzed and synthesized descriptively owing to the heterogeneity of data extracted from the included studies.

RESULTS

In the first part, a total of 14 papers met the inclusion criteria. Recommendations for VR design and implementation were not specific to TBI but rather to stroke or ABI rehabilitation more broadly. The synthesis and analysis of data resulted in three key phases and nine categories of recommendations for designing and implementing VR for ABI rehabilitation. In the second part, 5 studies met the inclusion criteria. A total of 2 studies reported on VR for assessment and three for treatment. Studies were varied in terms of therapeutic targets, VR tasks, and outcome measures. VR was used to assess or treat impairments in cognition, balance, and anxiety, with positive outcomes. However, the levels of evidence, methodological quality, and inclusion of recommendations for VR design and implementation were poor.

CONCLUSIONS

There is limited research on the use of immersive VR for TBI rehabilitation. Few studies have been conducted, and there is limited inclusion of recommendations for therapeutic VR design and implementation. Future research in ABI rehabilitation should consider a stepwise approach to VR development, from early co-design studies with end users to larger controlled trials. A list of recommendations is offered to provide guidance and a more consistent model to advance clinical research in this area.

A Biofeedback App for Migraine: Development and Usability Study

Background

Biofeedback is effective in treating migraines. It is believed to have a beneficial effect on autonomous nervous system activity and render individuals resilient to stressors that may trigger a migraine. However, widespread use of biofeedback is hampered by the need for a trained therapist and specialized equipment. Emerging digital health technology, including smartphones and wearables (mHealth), enables new ways of administering biofeedback. Currently, mHealth interventions for migraine appear feasible, but development processes and usability testing remain insufficient.

Objective

The objective of this study was to evaluate and improve the feasibility and usability of an mHealth biofeedback treatment app for adults with migraine.

Methods

In a prospective development and usability study, 18 adults with migraine completed a 4-week testing period of self-administered therapist-independent biofeedback treatment consisting of a smartphone app connected to wearable sensors (Cerebri, Nordic Brain Tech AS). The app included biofeedback training, instructions for self-delivery, and a headache diary. Two wearable sensors were used to measure surface electromyographic voltage at the trapezius muscle and peripheral skin temperature and heart rate at the right second fingertip. Participants were instructed to complete a daily headache diary entry and biofeedback session of 10 minutes duration. The testing period was preceded by a preusability expectation interview and succeeded by a postusability experience interview. In addition, an evaluation questionnaire was completed at weeks 2 and 4. Adherence was calculated as the proportion of 10-minute sessions completed within the first 28 days of treatment. Usability and feasibility were analyzed and summarized quantitatively and qualitatively.

Results

A total of 391 biofeedback sessions were completed with a median of 25 (IQR 17-28) per participant. The mean adherence rate was 0.76 (SD 0.26). The evaluation questionnaire revealed that functionality and design had the highest scores, whereas engagement and biofeedback were lower. Qualitative preexpectation analysis revealed that participants expected to become better familiar with physical signals and gain more understanding of their migraine attacks and noted that the app should be simple and understandable. Postusability analysis indicated that participants had an overall positive user experience with some suggestions for improvement regarding the design of the wearables and app content. The intervention was safe and tolerable. One case of prespecified adverse events was recorded in which a patient developed a skin rash from the sticky surface electromyography electrodes.

Conclusions

The app underwent a rigorous development process that indicated an overall positive user experience, good usability, and high adherence rate. This study highlights the value of usability testing in the development of mHealth apps.

How Interpersonal Distance Between Avatar and Human Influences Facial Affect Recognition in Immersive Virtual Reality

Purpose: The purpose of this study was to determine the optimal interpersonal distance (IPD) between humans and affective avatars in facial affect recognition in immersive virtual reality (IVR). The ideal IPD is the one in which the humans show the highest number of hits and the shortest reaction times in recognizing the emotions displayed by avatars. The results should help design future therapies to remedy facial affect recognition deficits.

Methods: A group of 39 healthy volunteers participated in an experiment in which participants were shown 65 dynamic faces in IVR and had to identify six basic emotions plus neutral expression presented by the avatars. We decided to limit the experiment to five different distances: D1 (35 cm), D2 (55 cm), D3 (75 cm), D4 (95 cm), and D5 (115 cm), all belonging to the intimate and personal interpersonal spaces. Of the total of 65 faces, 13 faces were presented for each of the included distances. The views were shown at different angles: 50% in frontal view, 25% from the right profile, and 25% from the left profile. The order of appearance of the faces presented to each participant was randomized.

Results: The overall success rate in facial emotion identification was 90.33%, being D3 the IPD with the best overall emotional recognition hits, although statistically significant differences could not be found between the IPDs. Consistent with results obtained in previous studies, identification rates for negative emotions were higher with increasing IPD, whereas the recognition task improved for positive emotions when IPD was closer. In addition, the study revealed irregular behavior in the facial detection of the emotion surprise.

Conclusions: IVR allows us to reliably assess facial emotion recognition using dynamic avatars as all the IPDs tested showed to be effective. However, no statistically significant differences in facial emotion recognition were found among the different IPDs.

Augmented, Mixed, and Virtual Reality-Based Head-Mounted Devices for Medical Education: Systematic Review

BACKGROUND

Augmented reality (AR), mixed reality (MR), and virtual reality (VR), realized as head-mounted devices (HMDs), may open up new ways of teaching medical content for low-resource settings. The advantages are that HMDs enable repeated practice without adverse effects on the patient in various medical disciplines; may introduce new ways to learn complex medical content; and may alleviate financial, ethical, and supervisory constraints on the use of traditional medical learning materials, like cadavers and other skills lab equipment.

OBJECTIVE

We examine the effectiveness of AR, MR, and VR HMDs for medical education, whereby we aim to incorporate a global health perspective comprising low- and middle-income countries (LMICs).

METHODS

We conducted a systematic review according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) and Cochrane guidelines. Seven medical databases (PubMed, Cochrane Library, Web of Science, Science Direct, PsycINFO, Education Resources Information Centre, and Google Scholar) were searched for peer-reviewed publications from January 1, 2014, to May 31, 2019. An extensive search was carried out to examine relevant literature guided by three concepts of extended reality (XR), which comprises the concepts of AR, MR, and VR, and the concepts of medicine and education. It included health professionals who took part in an HMD intervention that was compared to another teaching or learning method and evaluated with regard to its effectiveness. Quality and risk of bias were assessed with the Medical Education Research Study Quality Instrument, the Newcastle-Ottawa Scale-Education, and A Cochrane Risk of Bias Assessment Tool for Non-Randomized Studies of Interventions. We extracted relevant data and aggregated the data according to the main outcomes of this review (knowledge, skills, and XR HMD).

RESULTS

A total of 27 studies comprising 956 study participants were included. The participants included all types of health care professionals, especially medical students (n=573, 59.9%) and residents (n=289, 30.2%). AR and VR implemented with HMDs were most often used for training in the fields of surgery (n=13, 48%) and anatomy (n=4, 15%). A range of study designs were used, and quantitative methods were clearly dominant (n=21, 78%). Training with AR- and VR-based HMDs was perceived as salient, motivating, and engaging. In the majority of studies (n=17, 63%), HMD-based interventions were found to be effective. A small number of included studies (n=4, 15%) indicated that HMDs were effective for certain aspects of medical skills and knowledge learning and training, while other studies suggested that HMDs were only viable as an additional teaching tool (n=4, 15%). Only 2 (7%) studies found no effectiveness in the use of HMDs.

CONCLUSIONS

The majority of included studies suggested that XR-based HMDs have beneficial effects for medical education, whereby only a minority of studies were from LMICs. Nevertheless, as most studies showed at least noninferior results when compared to conventional teaching and training, the results of this review suggest applicability and potential effectiveness in LMICs. Overall, users demonstrated greater enthusiasm and enjoyment in learning with XR-based HMDs. It has to be noted that many HMD-based interventions were small-scale and conducted as short-term pilots. To generate relevant evidence in the future, it is key to rigorously evaluate XR-based HMDs with AR and VR implementations, particularly in LMICs, to better understand the strengths and shortcomings of HMDs for medical education.

Non-communicable Disease Surveillance in Malaysia: An Overview of Existing Systems and Priorities Going Forward

In 2012, the World Health Organization (WHO) set a comprehensive set of nine global voluntary targets, including the landmark “25 by 25” mortality reduction target, and 25 indicators. WHO has also highlighted the importance of Non-Communicable Disease (NCD) surveillance as a key action by Member States in addressing NCDs. This study aimed to examine the current national NCD surveillance tools, activities and performance in Malaysia based on the WHO Global Monitoring Framework for NCDs and to highlight gaps and priorities moving forward. A desk review was conducted from August to October in 2020, to examine the current national NCD surveillance activities in Malaysia from multiple sources. Policy and program documents relating to NCD surveillance in Malaysia from 2010 to 2020 were identified and analyzed. The findings of this review are presented according to the three major themes of the Global Monitoring Framework: monitoring of exposure/risk factor, monitoring of outcomes and health system capacity/response. Currently, there is a robust monitoring system for NCD Surveillance in Malaysia for indicators that are monitored by the WHO NCD Global Monitoring Framework, particularly for outcome and exposure monitoring. However, Malaysia still lacks data for the surveillance of the health system indicators of the framework. Although Malaysia has an NCD surveillance in place that is adequate for the WHO NCD Global Monitoring Framework, there are areas that require strengthening. The country must also look beyond these set of indicators in view of the increasing burden and impact of the COVID-19 pandemic. This includes incorporating mental health indicators and leveraging on alternate sources of data relating to behaviors.

Modelling disease transmission from touchscreen user interfaces

The extensive use of touchscreens for all manner of human-computer interactions has made them plausible instruments of touch-mediated disease transmission. To that end, we employ stochastic simulations to model human-fomite interaction with a distinct focus on touchscreen interfaces. The timings and frequency of interactions from within a closed population of infectious and susceptible individuals was modelled using a queuing network. A pseudo-reproductive number R was used to compare outcomes under various parameter conditions. We then apply the simulation to a specific real-world scenario; namely that of airport self-check-in and baggage drop. A counterintuitive result was that R decreased with increased touch rates required for touchscreen interaction. Additionally, as one of few parameters to be controlled, the rate of cleaning/disinfecting screens plays an essential role in mitigating R, though alternative technological strategies could prove more effective. The simulation model developed provides a foundation for future advances in more sophisticated fomite disease-transmission modelling.

Medical Device Regulation Efforts for mHealth Apps during the COVID-19 Pandemic—An Experience Report of Corona Check and Corona Health

Within the healthcare environment, mobile health (mHealth) applications (apps) are becoming more and more important. The number of new mHealth apps has risen steadily in the last years. Especially the COVID-19 pandemic has led to an enormous amount of app releases. In most countries, mHealth applications have to be compliant with several regulatory aspects to be declared a “medical app”. However, the latest applicable medical device regulation (MDR) does not provide more details on the requirements for mHealth applications. When developing a medical app, it is essential that all contributors in an interdisciplinary team—especially software engineers—are aware of the specific regulatory requirements beforehand. The development process, however, should not be stalled due to integration of the MDR. Therefore, a developing framework that includes these aspects is required to facilitate a reliable and quick development process. The paper at hand introduces the creation of such a framework on the basis of the Corona Health and Corona Check apps. The relevant regulatory guidelines are listed and summarized as a guidance for medical app developments during the pandemic and beyond. In particular, the important stages and challenges faced that emerged during the entire development process are highlighted.

Using Medical Device Standards for Design and Risk Management of Immersive Virtual Reality for At-Home Therapy and Remote Patient Monitoring

Numerous virtual reality (VR) systems have received regulatory clearance as therapeutic medical devices for in-clinic and at-home use. These systems enable remote patient monitoring of clinician-prescribed rehabilitation exercises, although most of these systems are nonimmersive. With the expanding availability of affordable and easy-to-use head-mounted display (HMD)-based VR, there is growing interest in immersive VR therapies. However, HMD-based VR presents unique risks. Following standards for medical device development, the objective of this paper is to demonstrate a risk management process for a generic immersive VR system for remote patient monitoring of at-home therapy. Regulations, standards, and guidance documents applicable to therapeutic VR design are reviewed to provide necessary background. Generic requirements for an immersive VR system for home use and remote patient monitoring are identified using predicate analysis and specified for both patients and clinicians using user stories. To analyze risk, failure modes and effects analysis, adapted for medical device risk management, is performed on the generic user stories and a set of risk control measures is proposed. Many therapeutic applications of VR would be regulated as a medical device if they were to be commercially marketed. Understanding relevant standards for design and risk management early in the development process can help expedite the availability of innovative VR therapies that are safe and effective.

Critical Success Factors in Adoption of Wearable Technology Devices for Seniors in Thailand

The adoption of wearable devices has been proposed as a promising approach to improve the well-being of senior in Thai care services. This study aims to find the critical success factors (CSFs) in adopting wearable technology from the stakeholder perspective. We collected data from total 27 participants from three groups of stakeholders: formal caregivers, informal caregivers, and seniors. Using the grounded theory approach, we found four types of CSFs and its variety in according to devices and stakeholders’ viewpoints. Based on the findings, this paper also discusses how to develop wearable devices to satisfy stakeholder requirements and improve their wellbeing.

A Virtual Reality-Based App to Educate Health Care Professionals and Medical Students About Inflammatory Arthritis: Feasibility Study

Background

Inflammatory arthritides (IA) such as rheumatoid arthritis or psoriatic arthritis are disorders that can be difficult to comprehend for health professionals and students in terms of the heterogeneity of clinical symptoms and pathologies. New didactic approaches using innovative technologies such as virtual reality (VR) apps could be helpful to demonstrate disease manifestations as well as joint pathologies in a more comprehensive manner. However, the potential of using a VR education concept in IA has not yet been evaluated.

Objective

We evaluated the feasibility of a VR app to educate health care professionals and medical students about IA.

Methods

We developed a VR app using data from IA patients as well as 2D and 3D-visualized pathological joints from X-ray and computed tomography–generated images. This VR app (Rheumality) allows the user to interact with representative arthritic joint and bone pathologies of patients with IA. In a consensus meeting, an online questionnaire was designed to collect basic demographic data (age, sex); profession of the participants; and their feedback on the general impression, knowledge gain, and potential areas of application of the VR app. The VR app was subsequently tested and evaluated by health care professionals (physicians, researchers, and other professionals) and medical students at predefined events (two annual rheumatology conferences and academic teaching seminars at two sites in Germany). To explore associations between categorical variables, the χ² or Fisher test was used as appropriate. Two-sided P values ≤.05 were regarded as significant.

Results

A total of 125 individuals participated in this study. Among them, 56% of the participants identified as female, 43% identified as male, and 1% identified as nonbinary; 59% of the participants were 18-30 years of age, 18% were 31-40 years old, 10% were 41-50 years old, 8% were 51-60 years old, and 5% were 61-70 years old. The participants (N=125) rated the VR app as excellent, with a mean rating of 9.0 (SD 1.2) out of 10, and many participants would recommend use of the app, with a mean recommendation score of 3.2 (SD 1.1) out of 4. A large majority (120/125, 96.0%) stated that the presentation of pathological bone formation improves understanding of the disease. We did not find any association between participant characteristics and evaluation of the VR experience or recommendation scores.

Conclusions

The data show that IA-targeting innovative teaching approaches based on VR technology are feasible.

Video Telehealth Occupational Therapy Services for Older Veterans: National Survey Study

BACKGROUND

Occupational therapy (OT) is a vital service that supports older adults' ability to age in place. Given the barriers to accessing care, video telehealth is a means of providing OT. Even within Veterans Health Administration (VHA), a pioneer in telehealth, video telehealth by OT practitioners to serve older adults is not well understood.

OBJECTIVE

This study examines VHA OT practice using video telehealth with older veterans using an implementation framework.

METHODS

A web-based national survey of VHA OT practitioners conducted between September and October 2019 contained a mix of mostly closed questions with some open-text options. The questions were developed using the Promoting Action on Research Implementation in Health Services model with input from subject matter experts. The questions gathered the extent to which VHA OT practitioners use video telehealth with older veterans; are comfortable with video telehealth to deliver specific OT services; and, for those using video telehealth with older veterans, the barriers, facilitators of change, and perceived benefits of video telehealth.

RESULTS

Of approximately 1455 eligible VHA OT practitioners, 305 participated (21.0% response rate). Most were female (196/259, 75.7%) occupational therapists (281/305, 92.1%) with a master's degree (147/259, 56.8%) and 10 years or fewer (165/305, 54.1%) of VHA OT practice. Less than half (125/305, 41.0%) had used video telehealth with older veterans, and users and nonusers of video telehealth were demographically similar. When asked to rate perceived comfort with video telehealth to deliver OT services, participants using video telehealth expressed greater comfort than nonusers, which was significant for 9 of the 13 interventions: activities of daily living (P<.001), instrumental activities of daily living (P=.004), home safety (P<.001), home exercise or therapeutic exercise (P<.001), veteran or caregiver education (P<.001), durable medical equipment (P<.001), assistive technology (P<.001), education and work (P=.04), and wheelchair clinic or seating and positioning (P<.001). More than half (74/125, 59.2%) of those using video telehealth reported at least one barrier, with the most frequently endorsed being Inadequate space, physical locations and related equipment. Most (92/125, 73.6%) respondents using video telehealth reported at least one facilitator, with the most frequently endorsed facilitators reflecting respondent attitudes, including the belief that video telehealth would improve veteran access to care (77/92, 84%) and willingness to try innovative approaches (76/92, 83%).

CONCLUSIONS

Most VHA OT survey respondents had not used video telehealth with older veterans. Users and nonusers were demographically similar. Differences in the percentages of respondents feeling comfortable with video telehealth for specific OT interventions suggest that some OT services may be more amenable to video telehealth. This, coupled with the primacy of respondent beliefs versus organizational factors as facilitators, underscores the need to gather clinicians' attitudes to understand how they are driving the implementation of video telehealth.

Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study

BACKGROUND

Outside of a clinical setting, oscillometric devices make remote monitoring of blood pressure and virtual care more convenient and feasible. HeartBeat Technologies Ltd developed a novel approach to measuring blood pressure remotely after an initial blood pressure reading by a nurse using the conventional measurement method. Using a finger pulse oximeter, a photoplethysmogram wave is transmitted by Bluetooth to a smartphone or tablet. A smartphone app (MediBeat) transmits the photoplethysmogram to a server for analysis by a proprietary algorithm-the person's current blood pressure is sent back to the smartphone and to the individual's health care provider.

OBJECTIVE

This study sought to determine whether the HeartBeat algorithm calculates blood pressure as accurately as required by the European Society of Hypertension International Protocol revision 2010 (ESH-IP2) for validation of blood pressure measuring devices.

METHODS

ESH-IP2 requirements, modified to conform to a more recent international consensus statement, were followed. The ESH-IP2 establishes strict guidelines for the conduct and reporting of any validation of any device to measure blood pressure, including using the standard manual blood pressure instrument as a comparator and specific required accuracy levels for low, medium, and high ranges of blood pressure readings. The consensus statement requires a greater number of study participants for each of the blood pressure ranges. The validation of the accuracy of the algorithm was conducted with a Contec CMS50EW pulse oximeter and a Samsung Galaxy XCover 4 smartphone.

RESULTS

The differences between the HeartBeat-calculated and the manually measured blood pressures of 62 study participants did not meet the ESH-IP2 standards for accuracy for either systolic or diastolic blood pressure measurements. There was no discernible pattern in the inaccuracies of the HeartBeat-calculated measurements.

CONCLUSIONS

The October 4, 2019 version of the HeartBeat algorithm, implemented in combination with the MediBeat app, a pulse oximeter, and an Android smartphone, was not sufficiently accurate for use in a general adult population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04082819; http://clinicaltrials.gov/ct2/show/NCT04082819.

Use of technology and social media in dementia care: Current and future directions

As the population across the globe continues to dramatically increase, the prevalence of cognitive impairment and dementia will inevitably increase as well, placing increasing burden on families and health care systems. Technological advancements over the past decade provide potential benefit in not only relieving caregiver burden of caring for a loved one with dementia, but also enables individuals with dementia to age in place. Technological devices have served to improve functioning, tracking and mobility. Similarly, smartphones, tablets and the ubiquitous world wide web have facilitated the dissemination of health information to previously hard to reach populations largely through use of various social media platforms. In this review, we discuss the current and future uses of technology via devices and social media to promote healthy aging in individuals with dementia, and also limitations and challenges to consider in the future.

Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients

Optical heart rate monitoring (OHR) with reflective wrist photoplethysmography is a technique mainly used in the wellness application domain for monitoring heart rate levels during exercise. In the absence of motion, OHR technique is also able to estimate individual beat-to-beat intervals relatively well and can therefore also be used, for example, in monitoring of cardiac arrhythmias, stress, or sleep quality through heart rate variability (HRV) analysis. HRV analysis has also potential in monitoring the recovery of patients, e.g. after a medical intervention. However, in order to detect subtle changes, the calculated HRV parameters should be sufficiently accurate and very few studies exist that asses the accuracy of OHR derived HRV in non-healthy subjects. In this paper, we present a method to estimate beat-to-beat-intervals (BBIs) from reflective wrist PPG signal and evaluated the accuracy of the proposed method in estimating BBIs in a cross-sectional study with 29 hospitalized patients (mean age 70.6 years) in 24-h recordings performed after peripheral vascular surgery or endovascular interventions. Finally, we evaluate the accuracy of more than 30 commonly used HRV parameters and find that the accuracy of certain metrics, for example SDNN and triangular index, shown in the literature to be associated with the deterioration of the status of the patients during recovery from surgical intervention, could be adequate for patient monitoring. On the other hand, the parameters more affected by the high-frequency content of the HRV and especially the LF/HF-ratio should be used with caution.

A Systematic Investigation of Models for Color Image Processing in Wound Size Estimation

In recent years, research in tracking and assessing wound severity using computerized image processing has increased. With the emergence of mobile devices, powerful functionalities and processing capabilities have provided multiple non-invasive wound evaluation opportunities in both clinical and non-clinical settings. With current imaging technologies, objective and reliable techniques provide qualitative information that can be further processed to provide quantitative information on the size, structure, and color characteristics of wounds. These efficient image analysis algorithms help determine the injury features and the progress of healing in a short time. This paper presents a systematic investigation of articles that specifically address the measurement of wounds’ sizes with image processing techniques, promoting the connection between computer science and health. Of the 208 studies identified by searching electronic databases, 20 were included in the review. From the perspective of image processing color models, the most dominant model was the hue, saturation, and value (HSV) color space. We proposed that a method for measuring the wound area must implement different stages, including conversion to grayscale for further implementation of the threshold and a segmentation method to measure the wound area as the number of pixels for further conversion to metric units. Regarding devices, mobile technology is shown to have reached the level of reliable accuracy.

Accuracy Investigation of the Pose Determination of a VR System

The usage of VR gear in mixed reality applications demands a high position and orientation accuracy of all devices to achieve a satisfying user experience. This paper investigates the system behaviour of the VR system HTC Vive Pro at a testing facility that is designed for the calibration of highly accurate positioning instruments like geodetic total stations, tilt sensors, geodetic gyroscopes or industrial laser scanners. Although the experiments show a high reproducibility of the position readings within a few millimetres, the VR system has systematic effects with magnitudes of several centimetres. A tilt of about 0.4° of the reference plane with respect to the horizontal plane was detected. Moreover, our results demonstrate that the tracking algorithm faces problems when several lighthouses are used.

Effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain: A systematic review and meta-analysis of randomized controlled trials

OBJECTIVE

The study sought to examine the effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain by a systematic review and meta-analysis of randomized controlled trials.

MATERIALS AND METHODS

We searched MEDLINE, EMBASE, CINAHL Plus, and the Cochrane Library from database inception to August 2020. A meta-analysis and subgroup analyses, stratified by technology type and program feature, were conducted.

RESULTS

Twelve randomized controlled trials were reviewed, all of which implemented the programs for 4 weeks to 6 months. Telephone, Web, mobile app, computer, and virtual reality were used to deliver the programs. The meta-analysis showed that these programs were associated with significant improvements in knee pain (standardized mean difference [SMD] = -0.29; 95% confidence interval [CI], -0.48 to -0.10; P = .003) and quality of life (SMD = 0.25; 95% CI, 0.04 to 0.46; P = .02) but not with significant improvement in physical function (SMD = 0.22; 95% CI, 0 to 0.43; P = .053). Subgroup analyses showed that some technology types and program features were suggestive of potential benefits.

CONCLUSIONS

Using technology to deliver the exercise programs appears to offer benefits. The technology types and program features that were associated with health values have been identified, based on which suggestions are discussed for the further research and development of such programs.