Measuring Heart Rate Variability in Free-Living Conditions Using Consumer-Grade Photoplethysmography: Validation Study

Background

Heart rate variability (HRV) is used to assess cardiac health and autonomic nervous system capabilities. With the growing popularity of commercially available wearable technologies, the opportunity to unobtrusively measure HRV via photoplethysmography (PPG) is an attractive alternative to electrocardiogram (ECG), which serves as the gold standard. PPG measures blood flow within the vasculature using color intensity. However, PPG does not directly measure HRV; it measures pulse rate variability (PRV). Previous studies comparing consumer-grade PRV with HRV have demonstrated mixed results in short durations of activity under controlled conditions. Further research is required to determine the efficacy of PRV to estimate HRV under free-living conditions.

Objective

This study aims to compare PRV estimates obtained from a consumer-grade PPG sensor with HRV measurements from a portable ECG during unsupervised free-living conditions, including sleep, and examine factors influencing estimation, including measurement conditions and simple editing methods to limit motion artifacts.

Methods

A total of 10 healthy adults were recruited. Data from a Microsoft Band 2 and a Shimmer3 ECG unit were recorded simultaneously using a smartphone. Participants wore the devices for >90 min during typical day-to-day activities and while sleeping. After filtering, ECG data were processed using a combination of discrete wavelet transforms and peak-finding methods to identify R-R intervals. P-P intervals were edited for deletion using methods based on outlier detection and by removing sections affected by motion artifacts. Common HRV metrics were compared, including mean N-N, SD of N-N intervals, percentage of subsequent differences >50 ms (pNN50), root mean square of successive differences, low-frequency power (LF), and high-frequency power. Validity was assessed using root mean square error (RMSE) and Pearson correlation coefficient (R2).

Results

Data sets for 10 days and 9 corresponding nights were acquired. The mean RMSE was 182 ms (SD 48) during the day and 158 ms (SD 67) at night. R2 ranged from 0.00 to 0.66, with 2 of 19 (2 nights) trials considered moderate, 7 of 19 (2 days, 5 nights) fair, and 10 of 19 (8 days, 2 nights) poor. Deleting sections thought to be affected by motion artifacts had a minimal impact on the accuracy of PRV measures. Significant HRV and PRV differences were found for LF during the day and R-R, SDNN, pNN50, and LF at night. For 8 of the 9 matched day and night data sets, R2 values were higher at night (P=.08). P-P intervals were less sensitive to rapid R-R interval changes.

Conclusions

Owing to overall poor concurrent validity and inconsistency among participant data, PRV was found to be a poor surrogate for HRV under free-living conditions. These findings suggest that free-living HRV measurements would benefit from examining alternate sensing methods, such as multiwavelength PPG and wearable ECG.

Maximizing Telerehabilitation for Patients With Visual Loss After Stroke: Interview and Focus Group Study With Stroke Survivors, Carers, and Occupational Therapists

BACKGROUND

Visual field defects are a common consequence of stroke, and compensatory eye movement strategies have been identified as the most promising rehabilitation option. There has been a move toward compensatory telerehabilitation options, such as the Durham Reading and Exploration (DREX) training app, which significantly improves visual exploration, reading, and self-reported quality of life.

OBJECTIVE

This study details an iterative process of liaising with stroke survivors, carers, and health care professionals to identify barriers and facilitators to using rehabilitation tools, as well as elements of good practice in telerehabilitation, with a focus on how the DREX package can be maximized.

METHODS

Survey data from 75 stroke survivors informed 12 semistructured engagement activities (7 focus groups and 5 interviews) with 32 stroke survivors, 10 carers, and 24 occupational therapists.

RESULTS

Thematic analysis identified key themes within the data. Themes identified problems associated with poststroke health care from both patients' and occupational therapists' perspectives that need to be addressed to improve uptake of this rehabilitation tool and telerehabilitation options generally. This included identifying additional materials or assistance that were required to boost the impact of training packages. The acute rehabilitation setting was an identified barrier, and perceptions of technology were considered a barrier by some but a facilitator by others. In addition, 4 key features of telerehabilitation were identified: additional materials, the importance of goal setting, repetition, and feedback.

CONCLUSIONS

The data were used to try to overcome some barriers to the DREX training and are further discussed as considerations for telerehabilitation in general moving forward.

Enhancement of Intracellular Calcium Ion Mobilization by Moderately but Not Highly Positive Material Surface Charges

Electrostatic forces at the cell interface affect the nature of cell adhesion and function; but there is still limited knowledge about the impact of positive or negative surface charges on cell-material interactions in regenerative medicine. Titanium surfaces with a variety of zeta potentials between −90 mV and +50 mV were generated by functionalizing them with amino polymers, extracellular matrix proteins/peptide motifs and polyelectrolyte multilayers. A significant enhancement of intracellular calcium mobilization was achieved on surfaces with a moderately positive (+1 to +10 mV) compared with a negative zeta potential (−90 to −3 mV). Dramatic losses of cell activity (membrane integrity, viability, proliferation, calcium mobilization) were observed on surfaces with a highly positive zeta potential (+50 mV). This systematic study indicates that cells do not prefer positive charges in general, merely moderately positive ones. The cell behavior of MG-63s could be correlated with the materials’ zeta potential; but not with water contact angle or surface free energy. Our findings present new insights and provide an essential knowledge for future applications in dental and orthopedic surgery.

A Usability Study of Physiological Measurement in School Using Wearable Sensors

Measuring psychophysiological signals of adolescents using unobtrusive wearable sensors may contribute to understanding the development of emotional disorders. This study investigated the feasibility of measuring high quality physiological data and examined the validity of signal processing in a school setting. Among 86 adolescents, a total of more than 410 h of electrodermal activity (EDA) data were recorded using a wrist-worn sensor with gelled electrodes and over 370 h of heart rate data were recorded using a chest-strap sensor. The results support the feasibility of monitoring physiological signals at school. We describe specific challenges and provide recommendations for signal analysis, including dealing with invalid signals due to loose sensors, and quantization noise that can be caused by limitations in analog-to-digital conversion in wearable devices and be mistaken as physiological responses. Importantly, our results show that using toolboxes for automatic signal preprocessing, decomposition, and artifact detection with default parameters while neglecting differences between devices and measurement contexts yield misleading results. Time courses of students' physiological signals throughout the course of a class were found to be clearer after applying our proposed preprocessing steps.

COVID-19 Contact-Tracing Technology: Acceptability and Ethical Issues of Use

BACKGROUND

The contact-tracing COVID-19 technology allows for tracing people that come in contact to individuals with COVID-19 wherever they are located. The number of tracing COVID-19 infection technology and devices is rapidly increasing. This has prompted many researchers to study the acceptability and ethical issues related to the implementation of such technology.

AIM

The purpose of this study was to determine the acceptability of COVID-19 contact-tracing technology and ethical issues of use.

METHODS

A cross-sectional questionnaire-based study was used. The target population was Jordanian adults (>18 years). The survey was distributed to a convenience sample of 2000 general public in Jordan.

RESULTS

The results found that the number of people who accept to use COVID-19 contact-tracing technology was 71.6%. However, the percentage of people who were using this technology was 37.8. The main ethical concerns for many of participants were privacy, voluntariness, and beneficence of the data. Only income and living area were predictors for acceptability and use of tracing technology (p≤ 0.01).

CONCLUSION

The majority of Jordanians accept the implementation of contact-tracing technology for COVID-19 infection. Among ethical concerns of the implementation of such technology were privacy, beneficence and voluntariness.

IMPLICATIONS

The results of this study would help in improving the state of science regarding acceptability to use contact-tracing technology for health purposes. Moreover, the present findings provide evidence of predictors of acceptance and ethical concerns among Jordanian population about COVID-19 contact-tracing technology.

Usability of Individualized Head-Related Transfer Functions in Virtual Reality: Empirical Study With Perceptual Attributes in Sagittal Plane Sound Localization

BACKGROUND

In order to present virtual sound sources via headphones spatially, head-related transfer functions (HRTFs) can be applied to audio signals. In this so-called binaural virtual acoustics, the spatial perception may be degraded if the HRTFs deviate from the true HRTFs of the listener.

OBJECTIVE

In this study, participants wearing virtual reality (VR) headsets performed a listening test on the 3D audio perception of virtual audiovisual scenes, thus enabling us to investigate the necessity and influence of the individualization of HRTFs. Two hypotheses were investigated: first, general HRTFs lead to limitations of 3D audio perception in VR and second, the localization model for stationary localization errors is transferable to nonindividualized HRTFs in more complex environments such as VR.

METHODS

For the evaluation, 39 subjects rated individualized and nonindividualized HRTFs in an audiovisual virtual scene on the basis of 5 perceptual qualities: localizability, front-back position, externalization, tone color, and realism. The VR listening experiment consisted of 2 tests: in the first test, subjects evaluated their own and the general HRTF from the Massachusetts Institute of Technology Knowles Electronics Manikin for Acoustic Research database and in the second test, their own and 2 other nonindividualized HRTFs from the Acoustics Research Institute HRTF database. For the experiment, 2 subject-specific, nonindividualized HRTFs with a minimal and maximal localization error deviation were selected according to the localization model in sagittal planes.

RESULTS

With the Wilcoxon signed-rank test for the first test, analysis of variance for the second test, and a sample size of 78, the results were significant in all perceptual qualities, except for the front-back position between own and minimal deviant nonindividualized HRTF (P=.06).

CONCLUSIONS

Both hypotheses have been accepted. Sounds filtered by individualized HRTFs are considered easier to localize, easier to externalize, more natural in timbre, and thus more realistic compared to sounds filtered by nonindividualized HRTFs.

Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology

Background

There has been a recent increased interest in monitoring health using wearable sensor technologies; however, few have focused on breathing. The ability to monitor breathing metrics may have indications both for general health as well as respiratory conditions such as asthma, where long-term monitoring of lung function has shown promising utility.

Objective

In this paper, we explore a long short-term memory (LSTM) architecture and predict measures of interbreath intervals, respiratory rate, and the inspiration-expiration ratio from a photoplethysmogram signal. This serves as a proof-of-concept study of the applicability of a machine learning architecture to the derivation of respiratory metrics.

Methods

A pulse oximeter was mounted to the left index finger of 9 healthy subjects who breathed at controlled respiratory rates. A respiratory band was used to collect a reference signal as a comparison.

Results

Over a 40-second window, the LSTM model predicted a respiratory waveform through which breathing metrics could be derived with a bias value and 95% CI. Metrics included inspiration time (–0.16 seconds, –1.64 to 1.31 seconds), expiration time (0.09 seconds, –1.35 to 1.53 seconds), respiratory rate (0.12 breaths per minute, –2.13 to 2.37 breaths per minute), interbreath intervals (–0.07 seconds, –1.75 to 1.61 seconds), and the inspiration-expiration ratio (0.09, –0.66 to 0.84).

Conclusions

A trained LSTM model shows acceptable accuracy for deriving breathing metrics and could be useful for long-term breathing monitoring in health. Its utility in respiratory disease (eg, asthma) warrants further investigation.

Digital Media as a Proponent for Healthy Aging in the Older Chinese American Population: Longitudinal Analysis

Background

Ensuring health literacy among underserved populations is essential amid an aging population. Accessible and appropriate (both culturally and linguistically) information is important when considering digital media education for older Chinese Americans.

Objective

This study aims to investigate how social media fare over time in disseminating health information and how we may most effectively educate this population.

Methods

For this study, 5 geriatric-themed educational videos about Parkinson disease, fall prevention, gastrointestinal health, oral health, and pulmonary disease were uploaded to YouTube. Data were collected over a 40-month period. Descriptive statistics and chi-square analysis were used to compare results from the first and second 20-month periods.

Results

In 40 months, the 5 videos in aggregate accrued 1171.1 hours of watch time, 7299 views, and an average view duration of 9.6 minutes. Comparing the first and second 20-month periods, there was a significant increase in mobile device usage, from 79.4% (3541/4458) to 83.3% (2367/2841). There was no significant difference in the usage of various external traffic sources and methods of sharing, with WhatsApp accounting for the majority of sharing in both 20-month periods.

Conclusions

Our study provides insight into where to focus future strategies to optimize digital media content, and how to best recruit, direct, and disseminate health education to an older adult Chinese American population. Combining the success of YouTube, social media, and messaging platforms such as WhatsApp can help to transcend cultural and linguistic barriers to promote healthy aging.

Use of Smart Technology for the Early Diagnosis of Complications After Cardiac Surgery: The Box 2.0 Study Protocol

BACKGROUND

Atrial fibrillation (AF), sternal wound infection, and cardiac decompensation are complications that can occur after cardiac surgery. Early detection of these complications is clinically relevant, as early treatment is associated with better clinical outcomes. Remote monitoring with the use of a smartphone (mobile health [mHealth]) might improve the early detection of complications after cardiac surgery.

OBJECTIVE

The primary aim of this study is to compare the detection rate of AF diagnosed with an mHealth solution to the detection rate of AF diagnosed with standard care. Secondary objectives include detection of sternal wound infection and cardiac decompensation, as well as assessment of quality of life, patient satisfaction, and cost-effectiveness.

METHODS

The Box 2.0 is a study with a prospective intervention group and a historical control group for comparison. Patients undergoing cardiac surgery at Leiden University Medical Center are eligible for enrollment. In this study, 365 historical patients will be used as controls and 365 other participants will be asked to receive either The Box 2.0 intervention consisting of seven home measurement devices along with a video consultation 2 weeks after discharge or standard cardiac care for 3 months. Patient information will be analyzed according to the intention-to-treat principle. The Box 2.0 devices include a blood pressure monitor, thermometer, weight scale, step count watch, single-lead electrocardiogram (ECG) device, 12-lead ECG device, and pulse oximeter.

RESULTS

The study started in November 2018. The primary outcome of this study is the detection rate of AF in both groups. Quality of life is measured with the five-level EuroQol five-dimension (EQ-5D-5L) questionnaire. Cost-effectiveness is calculated from a society perspective using prices from Dutch costing guidelines and quality of life data from the study. In the historical cohort, 93.9% (336/358) completed the EQ-5D-5L and patient satisfaction questionnaires 3 months after cardiac surgery.

CONCLUSIONS

The rationale and design of a study to investigate mHealth devices in postoperative cardiac surgery patients are presented. The first results are expected in September 2020.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03690492; http://clinicaltrials.gov/show/NCT03690492.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/16326.

A Novel Cytocompatibility Strengthening Strategy of Ultrafine-Grained Pure Titanium

Ultrafine-grained pure (UFG) titanium processed by equal channel angular pressing possesses mechanical properties comparable to those of Ti-6Al-4V and features more favorable friction resistance, biocompatibility, and corrosion resistance than does commercially pure (CP) titanium. Nevertheless, UFG titanium is still a bio-inert material with a lack of bone-inducing ability. Here, TiO₂-hydroxyapatite (TiO₂-HA) coatings were fabricated on CP titanium and UFG titanium through combining micro-arc oxidation and hydrothermal treatment together to improve their cytocompatibility. The results indicate that, compared with conventional coatings that use CP titanium as the substrate, such coatings formed on the UFG titanium possess additional hydrophilicity and in vitro cytocompatibility. The fantastic hierarchical structure of the UFG TiO₂-HA coating (UG-MH coating), including microscale and nanoscale pores and short column-shaped and sheet-shaped HA grains with varying geometric shapes, excellent hydrophilicity, and high polar force, enhances the mutual effects between the osteoblasts and titanium implant since it provides an adequate microenvironment for the ingrowth of osteoblasts, inducing osteoblast adhesion, proliferation, and differentiation. The UG-MH coating has a synergistic effect due to its fantastic hydrophilic hierarchical structure and high polar force on the up-regulated expression of cytoskeletal actin proteins as well as osteocalcin, protein kinase C (PKC), nuclear factor of activated T-cells (NFAT), and Wnt5, enabling osteoblasts to differentiate via the Wnt calcium-dependent signaling pathway. This study highlights the idea that the modified UFG titanium will be more suitable than CP titanium in dental and orthopedic applications.

Evaluation of Home-Based Rehabilitation Sensing Systems with Respect to Standardised Clinical Tests

With increased demand for tele-rehabilitation, many autonomous home-based rehabilitation systems have appeared recently. Many of these systems, however, suffer from lack of patient acceptance and engagement or fail to provide satisfactory accuracy; both are needed for appropriate diagnostics. This paper first provides a detailed discussion of current sensor-based home-based rehabilitation systems with respect to four recently established criteria for wide acceptance and long engagement. A methodological procedure is then proposed for the evaluation of accuracy of portable sensing home-based rehabilitation systems, in line with medically-approved tests and recommendations. For experiments, we deploy an in-house low-cost sensing system meeting the four criteria of acceptance to demonstrate the effectiveness of the proposed evaluation methodology. We observe that the deployed sensor system has limitations in sensing fast movement. Indicators of enhanced motivation and engagement are recorded through the questionnaire responses with more than 83% of the respondents supporting the system’s motivation and engagement enhancement. The evaluation results demonstrate that the deployed system is fit for purpose with statistically significant (ϱc>0.99, R2>0.94, ICC>0.96) and unbiased correlation to the golden standard.

Reconstructing Personal Stories in Virtual Reality sas a Mechanism to Recover the Self

Advances in virtual reality present opportunities to relive experiences in an immersive medium that can change the way we perceive our life stories, potentially shaping our realities for the better. This paper studies the role of virtual reality as a tool for the creation of stories with the concept of the self as a narrator and the life of the self as a storyline. The basis of the study is the philosophical notion of the self-narrative as an explanatory story of the events in one’s life that constitutes the notion of one’s self. This application is suitable for cases when individuals need to recreate their self, such as during recovery after traumatic events. The analysis of the effects of virtual reality shows that it enables a person to engage in a process of deeper self-observation to understand and explain adverse events and to give meaning to these events to form a new story, which can complement the therapeutic outcomes of exposure treatments. This study proposes concrete examples of immersive scenarios used to reconstruct personal stories. Several possible levels of experience are proposed to suggest that recovery can be achieved through the gradual retelling of the self-narrative, addressing all of the underlying narratives. Considering the ethical challenges that might arise, this paper explores the ways in which immersion in virtual reality can benefit a person’s view toward life as a story and his or her self as its author, comparing this idea with previous research on the application of virtual reality for trauma treatment. The analysis also emphasizes the perception of narrative authorship in virtual reality as an essential method for recovering the self-narrative and improving a patient’s mental health during self-actualization.

Error Augmentation in Immersive Virtual Reality for Bimanual Upper-Limb Rehabilitation in Individuals With and Without Hemiplegic Cerebral Palsy

With more readily available commercial immersive virtual reality (VR) technologies, the potential of new feedback strategies as tools to facilitate motor rehabilitation should be investigated. Augmented feedback or error augmentation (EA) can easily be shown in a virtual environment. Here, visual EA provided via immersive VR was tested for its effectiveness to improve bimanual symmetry in a reaching task. A single-session crossover design was used to test two training cases, with or without EA. With EA, the distance between hands in the forward direction was augmented. Participants were recruited from typically developing (TD) populations (n = 12, ages 13-21) and performed in an adapted environment with an initial asymmetry between limbs. Also, five participants with hemiplegic cerebral palsy (CP) (ages 14-21, MACS I-III) completed the study. Among TD participants, a significantly larger change in symmetry in the adapted environment was shown after EA than training without EA (F (1, 10) = 9.64, p = 0.01). Each participant in the CP group also improved more after EA training (8.8-103.7)%, such that they achieved lower symmetry error after training with EA. As participants in both groups adapted more symmetrically with EA, beneficial changes from this training method could be evaluated in future studies for longer-term functional changes.

Pulse Rate Variability in Emergency Physicians During Shifts: Pilot Cross-Sectional Study

Background

The high prevalence of physician burnout, particularly in emergency medicine, has garnered national attention in recent years. Objective means of measuring stress while at work can facilitate research into stress reduction interventions, and wearable photoplethysmography (PPG) technology has been proposed as a potential solution. However, the use of low-burden wearable biosensors to study training and clinical practice among emergency physicians (EP) remains untested.

Objective

This pilot study aimed to (1) determine the feasibility of recording on-shift photoplethysmographic data from EP, (2) assess the quality of these data, and (3) calculate standard pulse rate variability (PRV) metrics from the acquired dataset and examine patterns in these variables over the course of an academic year.

Methods

A total of 21 EP wore PPG biosensors on their wrists during clinical work in the emergency department during a 9-hour shift. Recordings were collected during the first quarter of the academic year, then again during the fourth quarter of the same year for comparison. The overall rate of usable data collection per time was computed. Standard pulse rate (PR) and PRV metrics from these two time points were calculated and entered into Student t tests.

Results

More than 400 hours of data were entered into these analyses. Interpretable data were captured during 8.54% of the total recording time overall. In the fourth quarter of the academic year compared with the first quarter, there was no significant difference in median PR (75.8 vs 76.8; P=.57), mean R-R interval (0.81 vs 0.80; P=.32), SD of R-R interval (0.11 vs 0.11; P=.93), root mean square of successive difference of R-R interval (0.81 vs 0.80; P=.96), low-frequency power (3.5×103 vs 3.4×103; P=.79), high-frequency power (8.5×103 vs 8.3×103; P=.91), or low-frequency to high-frequency ratio (0.42 vs 0.41; P=.43), respectively. Power estimates for each of these tests exceeded .90. A secondary analysis of the resident-only subgroup similarly showed no significant differences over time, despite power estimates greater than .80.

Conclusions

Although the use of PPG biosensors to record real-time physiological data from EP while providing clinical care seems operationally feasible, this study fails to support the notion that such an approach can efficiently provide reliable estimates of metrics of interest. No significant differences in PR or PRV metrics were found at the end of the year compared with the beginning. Although these methods may offer useful applications to other domains, it may currently have limited utility in the contexts of physician training and wellness.

Trends in Scientific Reports on Cartilage Bioprinting: Scoping Review

Background

Satisfactory therapeutic strategies for cartilaginous lesion repair do not yet exist. This creates a challenge for surgeons and biomedical engineers and leads them to investigate the role of bioprinting and tissue engineering as viable treatments through orthopedic surgery, plastic surgery, and otorhinolaryngology. Recent increases in related scientific literature suggest that bioprinted cartilage may develop into a viable solution.

Objective

The objectives of this review were to (1) synthesize the scientific advances published to date, (2) identify unresolved technical problems regarding human application, and (3) identify more effective ways for the scientific community to transfer their findings to clinicians.

Methods

This scoping review considered articles published between 2009 and 2019 that were identified through searching PubMed, Scopus, Web of Science, and Google Scholar. Arksey and O'Malley’s five-step framework was used to delimit and direct the initial search results, from which we established the following research questions: (1) What do authors of current research say about human application? (2) What necessary technical improvements are identified in the research? (3) On which issues do the authors agree? and (4) What future research priorities emerge in the studies? We used the Cohen kappa statistic to validate the interrater reliability.

Results

The 13 articles included in the review demonstrated the feasibility of cartilage bioprinting in live animal studies. Some investigators are already considering short-term human experimentation, although technical limitations still need to be resolved. Both the use and manufacturing process of stem cells need to be standardized, and a consensus is needed regarding the composition of hydrogels. Using on-site printing strategies and predesigned implants may allow techniques to adapt to multiple situations. In addition, the predictive capacity of implant behavior may lead to optimal results.

Conclusions

Cartilage bioprinting for surgical applications is nearing its initial use in humans. Current research suggests that surgeons will soon be able to replace damaged tissue with bioprinted material.

Applying a User-Centered Approach to Building a Mobile Personal Health Record App: Development and Usability Study

Background

A personal health record (PHR) system encourages patients to engage with their own health care by giving them the ability to manage and keep track of their own health data. Of the numerous PHR systems available in the market, many are Web-based patient portals and a few are mobile apps. They have mainly been created by hospitals and electronic health record (EHR) vendors. One major limitation of these hospital-created PHR systems is that patients can only view specific health data extracted from their EHR. Patients do not have the freedom to add important personal health data they collect in their daily lives into their PHR. Therefore, there is an information gap between clinical visits.

Objective

The aim of this study was to develop and evaluate a new mobile PHR app that can be easily used to manage various types of personal health data to fill the information gap.

Methods

A user-centered approach was used to guide the development and evaluation of the new mobile PHR app. There were three steps in this study: needs assessment, app design and development, and conducting a usability study. First, a large-scale questionnaire study was conducted with the general population to gain an understanding of their needs and expectations with regard to a mobile PHR app. A mobile PHR app for personal medical data tracking and management was then created based on the results of the questionnaire study. End users were actively involved in all stages of the app development. Finally, a usability study was performed with participants to evaluate the usability of the mobile PHR app, which involved asking participants to finish a set of tasks and to respond to a usability questionnaire.

Results

In the questionnaire study for needs assessment, there were 609 participants in total. The answers from these participants revealed that they wanted to manage various types of personal health data in a mobile PHR app. Participants also reported some features they desired to have in the app. On the basis of the needs assessment findings, a new mobile PHR app (PittPHR) was created with 6 major modules: health records, history, trackers, contacts, appointments, and resources. This app allows users to customize the trackers according to their needs. In the usability study, there were 15 participants. The usability study participants expressed satisfaction with the app and provided comments and suggestions for further development.

Conclusions

This new mobile PHR app provides options for users to manage a wide range of personal health data conveniently in one place. The app fills the information gap between clinical visits. The study results indicated that this new mobile PHR app meets the need of users and that users welcome this app.

The use of photoplethysmography for assessing hypertension

The measurement of blood pressure (BP) is critical to the treatment and management of many medical conditions. High blood pressure is associated with many chronic disease conditions, and is a major source of mortality and morbidity around the world. For outpatient care as well as general health monitoring, there is great interest in being able to accurately and frequently measure BP outside of a clinical setting, using mobile or wearable devices. One possible solution is photoplethysmography (PPG), which is most commonly used in pulse oximetry in clinical settings for measuring oxygen saturation. PPG technology is becoming more readily available, inexpensive, convenient, and easily integrated into portable devices. Recent advances include the development of smartphones and wearable devices that collect pulse oximeter signals. In this article, we review (i) the state-of-the-art and the literature related to PPG signals collected by pulse oximeters, (ii) various theoretical approaches that have been adopted in PPG BP measurement studies, and (iii) the potential of PPG measurement devices as a wearable application. Past studies on changes in PPG signals and BP are highlighted, and the correlation between PPG signals and BP are discussed. We also review the combined use of features extracted from PPG and other physiological signals in estimating BP. Although the technology is not yet mature, it is anticipated that in the near future, accurate, continuous BP measurements may be available from mobile and wearable devices given their vast potential.

Optimizing Expectations via Mobile Apps: A New Approach for Examining and Enhancing Placebo Effects

There is growing interest in interventions that enhance placebo responses in clinical practice, given the possibility that this would lead to better patient health and more effective therapy outcomes. Previous studies suggest that placebo effects can be maximized by optimizing patients' outcome expectations. However, expectancy interventions are difficult to validate because of methodological challenges, such as reliable blinding of the clinician providing the intervention. Here we propose a novel approach using mobile apps that can provide highly standardized expectancy interventions in a blinded manner, while at the same time assessing data in everyday life using experience sampling methodology (e.g., symptom severity, expectations) and data from smartphone sensors. Methodological advantages include: 1) full standardization; 2) reliable blinding and randomization; 3) disentangling expectation effects from other factors associated with face-to-face interventions; 4) assessing short-term (days), long-term (months), and cumulative effects of expectancy interventions; and 5) investigating possible mechanisms of change. Randomization and expectancy interventions can be realized by the app (e.g., after the clinic/lab visit). As a result, studies can be blinded without the possibility for the clinician to influence study outcomes. Possible app-based expectancy interventions include, for example, verbal suggestions and imagery exercises, although a large number of possible interventions (e.g., hypnosis) could be evaluated using this innovative approach.

Orthopedic Surgeons' Perspectives on the Decision-Making Process for the Use of Bioprinter Cartilage Grafts: Web-Based Survey

BACKGROUND

Traumatic and degenerative lesions in the cartilage are one of the most difficult and frustrating types of injuries for orthopedic surgeons and patients. Future developments in medical science, regenerative medicine, and materials science may allow the repair of human body parts using 3D bioprinting techniques and serve as a basis for new therapies for tissue and organ regeneration. One future possibility is the treatment of joint cartilage defects with in vivo 3D printing from biological/biocompatible materials to produce a suitable cell attachment and proliferation environment in the damaged site and employ the natural recovery potential of the body. This study focuses on the perspectives of orthopedic surgeons regarding the key factors/determinants and perceived clinical value of a new therapeutic option.

OBJECTIVE

This study aimed to determine the knowledge and expectations of orthopedic surgeons regarding the clinical use of bioprinted cartilage.

METHODS

The survey, conducted anonymously and self-managed, was sent to orthopedic surgeons from the Catalan Society of Orthopedic and Traumatology Surgery. In accordance with the method devised by Eysenbach, the Checklist for Reporting Results of Internet E-Surveys was used to analyze the results. The following factors were taken into consideration: the type and origin of the information received; its relevance; the level of acceptance of new technologies; and how the technology is related to age, years, and place of experience in the field.

RESULTS

Of the 86 orthopedic surgeons included, 36 believed the age of the patient was a restriction, 53 believed the size of the lesion should be between 1 and 2 cm to be considered for this type of technology, and 51 believed that the graft should last more than 5 years. Surgeons over 50 years of age (38/86, 44%) gave more importance to clinical evidence as compared to surgeons from the other age groups.

CONCLUSIONS

The perspective of orthopedic surgeons depends highly on the information they receive and whether it is specialized and consistent, as this will condition their acceptance and implementation of the bioprinted cartilage.

The mTST - An mHealth approach for training and quality assurance of tuberculin skin test administration and reading

Background

The Tuberculin Skin Test (TST) is a relatively simple test for detecting latent tuberculosis infection (LTBI) but requires regular quality assurance to ensure proper technique for administration and reading. The objective of this study was to estimate the accuracy and reproducibility of an mhealth approach (the mTST) to measure the size of swelling immediately following TST administration (TST injection bleb) and after 48–72 hours (TST induration).

Methods

Five non-clinical and one clinical reviewer measured the size of TST injection blebs, and TST indurations using smartphone acquired photos of sites of TST administration and readings in patients, or saline injections in volunteers. The reference standard was the onsite measurement (measured by an experienced TB nurse) of the actual TST injection bleb, or induration. Agreement of reviewers’ measurements with the reference standard, as well as agreement within and between reviewers, was estimated using Cohen's kappa coefficient.

Results

Using the mTST method to assess bleb size in 64 photos of different TST injections, agreement between reviewers, and the reference standard was very good to excellent (κ ranged from 0.75 to 0.87), and within-reviewer reproducibility of readings was excellent (κ ranged from 0.86 to 0.96). Using the mTST method to assess TST induration in 72 photos, reviewers were able to detect no induration (<5mm) and induration of 15mm or greater with accuracy of 95% and 92% respectively, but accuracy was only 20% and 77% for reactions of 5-9mm and 10-14mm respectively.

Conclusion

The mTST approach appears to be a reliable tool to assess TST administration. The mTST approach was accurate to read indurations of 0-4mm or 15+mm, but less accurate for reactions of 5-14mm. We believe the mTST approach could be useful for training and quality assurance in locations where on-site supervision is not possible.

The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review

Background

Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband.

Objective

This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research.

Methods

We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV).

Results

The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF.

Conclusions

A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening.

Hypertension Assessment Using Photoplethysmography: A Risk Stratification Approach

Hypertension is a common chronic cardiovascular disease (CVD). Early screening and diagnosis of hypertension plays a major role in its prevention and in the control of CVDs. Our study discusses the early screening of hypertension while using the morphological features of photoplethysmography (PPG). Numerous morphological features of PPG and its derivative waves were defined and extracted. Six types of feature selection methods were chosen to screen and evaluate these PPG morphological features. The optimal features were comprehensively analyzed in relation to the physiological processes of the cardiovascular circulatory system. Particularly, the intrinsic relation and physiological significance between the formation process of systolic blood pressure (SBP) and PPG morphology features were analyzed in depth. A variety of linear and nonlinear classification models were established for the comparison trials. The F1 scores for the normotension versus prehypertension, normotension and prehypertension versus hypertension, and normotension versus hypertension trials were 72.97%, 81.82%, and 92.31%, respectively. In summary, this study established a PPG characteristic analysis model and established the intrinsic relationship between SBP and PPG characteristics. Finally, the risk stratification of hypertension at different stages was examined and compared based on the optimal feature subset.

Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification

Blood pressure is a basic physiological parameter in the cardiovascular circulatory system. Long-term abnormal blood pressure will lead to various cardiovascular diseases, making the early detection and assessment of hypertension profoundly significant for the prevention and treatment of cardiovascular diseases. In this paper, we investigate whether or not deep learning can provide better results for hypertension risk stratification when compared to the classical signal processing and feature extraction methods. We tested a deep learning method for the classification and evaluation of hypertension using photoplethysmography (PPG) signals based on the continuous wavelet transform (using Morse) and pretrained convolutional neural network (using GoogLeNet). We collected 121 data recordings from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) Database, each containing arterial blood pressure (ABP) and photoplethysmography (PPG) signals. The ABP signals were utilized to extract blood pressure category labels, and the PPG signals were used to train and test the model. According to the seventh report of the Joint National Committee, blood pressure levels are categorized as normotension (NT), prehypertension (PHT), and hypertension (HT). For the early diagnosis and assessment of HT, the timely detection of PHT and the accurate diagnosis of HT are significant. Therefore, three HT classification trials were set: NT vs. PHT, NT vs. HT, and (NT + PHT) vs. HT. The F-scores of these three classification trials were 80.52%, 92.55%, and 82.95%, respectively. The tested deep method achieved higher accuracy for hypertension risk stratification when compared to the classical signal processing and feature extraction method. Additionally, the method achieved comparable results to another approach that requires electrocardiogram and PPG signals.

Hypertension Assessment via ECG and PPG Signals: An Evaluation Using MIMIC Database

Cardiovascular diseases (CVDs) have become the biggest threat to human health, and they are accelerated by hypertension. The best way to avoid the many complications of CVDs is to manage and prevent hypertension at an early stage. However, there are no symptoms at all for most types of hypertension, especially for prehypertension. The awareness and control rates of hypertension are extremely low. In this study, a novel hypertension management method based on arterial wave propagation theory and photoplethysmography (PPG) morphological theory was researched to explore the physiological changes in different blood pressure (BP) levels. Pulse Arrival Time (PAT) and photoplethysmogram (PPG) features were extracted from electrocardiogram (ECG) and PPG signals to represent the arterial wave propagation theory and PPG morphological theory, respectively. Three feature sets, one containing PAT only, one containing PPG features only, and one containing both PAT and PPG features, were used to classify the different BP categories, defined as normotension, prehypertension, and hypertension. PPG features were shown to classify BP categories more accurately than PAT. Furthermore, PAT and PPG combined features improved the BP classification performance. The F1 scores to classify normotension versus prehypertension reached 84.34%, the scores for normotension versus hypertension reached 94.84%, and the scores for normotension plus prehypertension versus hypertension reached 88.49%. This indicates that the simultaneous collection of ECG and PPG signals could detect hypertension.

Electrical stimulation of the pudendal nerve promotes neuroregeneration and functional recovery from stress urinary incontinence in a rat model

The pudendal nerve can be injured during vaginal delivery of children, and slowed pudendal nerve regeneration has been correlated with development of stress urinary incontinence (SUI). Simultaneous injury to the pudendal nerve and its target muscle, the external urethral sphincter (EUS), during delivery likely leads to slowed neuroregeneration. The goal of this study was to determine if repeat electrical stimulation of the pudendal nerve improves SUI recovery and promotes neuroregeneration in a dual muscle and nerve injury rat model of SUI. Rats received electrical stimulation or sham stimulation of the pudendal nerve twice weekly for up to 2 wk after injury. A separate cohort of rats received sham injury and sham stimulation. Expression of brain-derived neurotrophic factor (BDNF) and β_II-tubulin expression in Onuf's nucleus were measured 2, 7, and 14 days after injury. Urodynamics, leak point pressure (LPP), and EUS electromyography (EMG) were recorded 14 days after injury. Electrical stimulation significantly increased expression of BDNF at all time points and β_II-tubulin 1 and 2 wk after injury. Two weeks after injury, LPP and EUS EMG during voiding and LPP testing were significantly decreased compared with sham-injured animals. Electrical stimulation significantly increased EUS activity during voiding, although LPP did not fully recover. Repeat pudendal nerve stimulation promotes neuromuscular continence mechanism recovery possibly via a neuroregenerative response through BDNF upregulation in the pudendal motoneurons in this model of SUI. Electrical stimulation of the pudendal nerve may therefore improve recovery after childbirth and ameliorate symptoms of SUI by promoting neuroregeneration after injury.

Digital Technology and Mobile Health in Behavioral Migraine Therapy: a Narrative Review

PURPOSE OF REVIEW

This article reviews the recent research and development of electronic health (eHealth) and, in particular, mobile health (mHealth) strategies to deliver behavioral treatment for migraine. Prospects for future development and research of mobile health in migraine are suggested.

RECENT FINDINGS

Advances in digital technology and mobile technology have led to an era where electronic and mobile approaches are applied to several aspects of healthcare. Electronic behavioral interventions for migraine seem to be acceptable and feasible, but efficacy measures are uncertain. Clinical trials on mHealth-based classical behavioral therapies, such as relaxation, biofeedback, and cognitive behavioral therapy are missing in the literature. Within mHealth, headache diaries are the most researched and scientifically developed. Still, there is a gap between commercially available apps and scientifically validated and developed apps. Digital technology and mobile health has not yet lived out its potential in behavioral migraine therapy. Application of proper usability and functionality designs towards the right market, together with appraisal of medical and technological recommendations, may facilitate rapid development of eHealth and mHealth, while also establishing scientific evidence.

A Novel 12-Lead Electrocardiographic System for Home Use: Development and Usability Testing

Background

Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality worldwide. Early diagnosis is of pivotal importance for patients with cardiac arrhythmias and ischemia to minimize the consequences like strokes and myocardial infarctions. The chance of capturing signals of arrhythmias or ischemia is substantially high when a 12-lead electrocardiogram (ECG) can be recorded at the moment when a patient experiences the symptoms. However, until now, available diagnostic systems (Holter monitors and other wearable ECG sensors) have not enabled patients to record a reliable 12-lead ECG at home.

Objective

The objective of this project was to develop a user-friendly system that enables persons with cardiac complaints to record a reliable 12-lead ECG at home to improve the diagnostic process and, consequently, reduce the time between the onset of symptoms and adequate treatment.

Methods

Using an iterative design approach, ECGraph was developed. The system consists of an ECG measurement system and a mobile app, which were developed with the help of several concept tests. To evaluate the design, a prototype of the final design was built and a final technical performance test and usability test were executed.

Results

The ECG measurement system consists of a belt and 4 limb straps. Ten wet Ag/AgCl electrodes are placed in the belt to optimize skin-electrode contact. The product is controlled via an app on the mobile phone of the user. Once a person experiences symptoms, he or she can put on the belt and record ECGs within a few minutes. Short instructions, supported by visualizations, offer guidance during use. ECGs are sent wirelessly to the caregiver, and the designated expert can quickly interpret the results. Usability tests with the final prototype (n=6) showed that the participants were able to put on the product within 8 minutes during first-time use. However, we expect that the placement of the product can be executed faster when the user becomes more familiar with the product. Areas of improvement focus mainly on confidence during product use. In the technical performance test, a 12-lead ECG was made and reproduced 6 times.

Conclusions

We developed a new 12-lead ECG system for home use. The product is expected to be more user-friendly than current hospital ECG systems and is designed to record more reliable data than current ECG systems for home use, which makes it suitable for expert interpretation. The system has great potential to be incorporated into an outpatient practice, so that arrhythmias and ischemia can be diagnosed and treated as early as possible.

Mobile phone-based evaluation of latent tuberculosis infection: Proof of concept for an integrated image capture and analysis system

BACKGROUND

The tuberculin skin test is the most widely used method for detecting latent tuberculosis infection in adults and active tuberculosis in children. We present the development of a mobile-phone based screening tool for measuring the tuberculin skin test induration.

METHOD

The tool makes use of a mobile application developed on the Android platform to capture images of an induration, and photogrammetric reconstruction using Agisoft PhotoScan to reconstruct the induration in 3D, followed by 3D measurement of the induration with the aid of functions from the Python programming language. The system enables capture of images by the person being screened for latent tuberculosis infection. Measurement precision was tested using a 3D printed induration. Real-world use of the tool was simulated by application to a set of mock skin indurations, created by a make-up artist, and the performance of the tool was evaluated. The usability of the application was assessed with the aid of a questionnaire completed by participants.

RESULTS

The tool was found to measure the 3D printed induration with greater precision than the current ruler and pen method, as indicated by the lower standard deviation produced (0.3 mm versus 1.1 mm in the literature). There was high correlation between manual and algorithm measurement of mock skin indurations. The height of the skin induration and the definition of its margins were found to influence the accuracy of 3D reconstruction and therefore the measurement error, under simulated real-world conditions. Based on assessment of the user experience in capturing images, a simplified user interface would benefit wide-spread implementation.

CONCLUSIONS

The mobile application shows good agreement with direct measurement. It provides an alternative method for measuring tuberculin skin test indurations and may remove the need for an in-person follow-up visit after test administration, thus improving latent tuberculosis infection screening throughput.

An optimal filter for short photoplethysmogram signals

A photoplethysmogram (PPG) contains a wealth of cardiovascular system information, and with the development of wearable technology, it has become the basic technique for evaluating cardiovascular health and detecting diseases. However, due to the varying environments in which wearable devices are used and, consequently, their varying susceptibility to noise interference, effective processing of PPG signals is challenging. Thus, the aim of this study was to determine the optimal filter and filter order to be used for PPG signal processing to make the systolic and diastolic waves more salient in the filtered PPG signal using the skewness quality index. Nine types of filters with 10 different orders were used to filter 219 (2.1s) short PPG signals. The signals were divided into three categories by PPG experts according to their noise levels: excellent, acceptable, or unfit. Results show that the Chebyshev II filter can improve the PPG signal quality more effectively than other types of filters and that the optimal order for the Chebyshev II filter is the 4^th order.

Ethical Issues for Direct-to-Consumer Digital Psychotherapy Apps: Addressing Accountability, Data Protection, and Consent

This paper focuses on the ethical challenges presented by direct-to-consumer (DTC) digital psychotherapy services that do not involve oversight by a professional mental health provider. DTC digital psychotherapy services can potentially assist in improving access to mental health care for the many people who would otherwise not have the resources or ability to connect with a therapist. However, the lack of adequate regulation in this area exacerbates concerns over how safety, privacy, accountability, and other ethical obligations to protect an individual in therapy are addressed within these services. In the traditional therapeutic relationship, there are ethical obligations that serve to protect the interests of the client and provide warnings. In contrast, in a DTC therapy app, there are no clear lines of accountability or associated ethical obligations to protect the user seeking mental health services. The types of DTC services that present ethical challenges include apps that use a digital platform to connect users to minimally trained nonprofessional counselors, as well as services that provide counseling steered by artificial intelligence and conversational agents. There is a need for adequate oversight of DTC nonprofessional psychotherapy services and additional empirical research to inform policy that will provide protection to the consumer.

Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis

In the digital medicine field, biosignals, such as those of an electrocardiogram (ECG), are collected regularly for screening and diagnosis, and there continues to be an increasingly substantial shift towards collecting long-term ECG signals for remote monitoring, e.g., in smart homes. ECG signal collection is quite simple and only requires the use of inexpensive sensors, an active Internet connection, and a mobile device that acts as the medium between the sensors and the Internet (e.g., a mobile phone or laptop). Despite the ease and convenience of remote ECG data collection and transmission, the amount of time and energy required for the related remote computational processes remains a major limitation. This short note discusses a biosignal approach that uses fewer biomedical data for screening and diagnosis that is, compared to current data collection methods, equally, if not more, efficient.

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B / K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance ( CR = 6 and PRD = 1.88 ) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring.

Efficient ECG Compression and QRS Detection for E-Health Applications

Current medical screening and diagnostic procedures have shifted toward recording longer electrocardiogram (ECG) signals, which have traditionally been processed on personal computers (PCs) with high-speed multi-core processors and efficient memory processing. Battery-driven devices are now more commonly used for the same purpose and thus exploring highly efficient, low-power alternatives for local ECG signal collection and processing is essential for efficient and convenient clinical use. Several ECG compression methods have been reported in the current literature with limited discussion on the performance of the compressed and the reconstructed ECG signals in terms of the QRS complex detection accuracy. This paper proposes and evaluates different compression methods based not only on the compression ratio (CR) and percentage root-mean-square difference (PRD), but also based on the accuracy of QRS detection. In this paper, we have developed a lossy method (Methods III) and compared them to the most current lossless and lossy ECG compression methods (Method I and Method II, respectively). The proposed lossy compression method (Method III) achieves CR of 4.5×, PRD of 0.53, as well as an overall sensitivity of 99.78% and positive predictivity of 99.92% are achieved (when coupled with an existing QRS detection algorithm) on the MIT-BIH Arrhythmia database and an overall sensitivity of 99.90% and positive predictivity of 99.84% on the QT database.

TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach

Biomedical signals contain features that represent physiological events, and each of these events has peaks. The analysis of biomedical signals for monitoring or diagnosing diseases requires the detection of these peaks, making event detection a crucial step in biomedical signal processing. Many researchers have difficulty detecting these peaks to investigate, interpret and analyze their corresponding events. To date, there is no generic framework that captures these events in a robust, efficient and consistent manner. A new method referred to for the first time as two event-related moving averages ("TERMA") involves event-related moving averages and detects events in biomedical signals. The TERMA framework is flexible and universal and consists of six independent LEGO building bricks to achieve high accuracy detection of biomedical events. Results recommend that the window sizes for the two moving averages ( W 1 and W 2 ) have to follow the inequality ( 8 × W 1 ) ≥ W 2 ≥ ( 2 × W 1 ) . Moreover, TERMA is a simple yet efficient event detector that is suitable for wearable devices, point-of-care devices, fitness trackers and smart watches, compared to more complex machine learning solutions.