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JMIR Biomedical Engineering
Engineering for health technologies, medical devices, and innovative medical treatments and procedures
Background: The use of Web-based physical activity systems has been proposed as an easy method for collecting physical activity data. Behavior recording using a voice recognition system via the WEB might be effective. Objective: The objective of this study was to develop a behavior-recording application (APP) using voice recognition. The results from our developed APP were compared with objective data from a 3-axis accelerometer to assess the strengths and weaknesses of the new measurement system. Methods: A total of 20 participants (14 men, 6 women, 19.1 (SD 0.9) years of age) wore a 3-axis accelerometer and inputted behavioral data into their smartphones for a period of 7 days. The measure of intensity was metabolic equivalents (METs). Results: The Pearson correlations for the METs between the two methods were all positive and significant when the analysis was for over 10 hours, r = 0.545 (P =.017), and for over 14 hours with voice input, r = 0.750 (P =.008). The Bland-Altman 95% limits of agreement ranged from –0.35 to 0.54 METs (over 10 hours) and -0.26 to 0.47 (over 14 hours) between the two methods. The exercise intensity was higher according to the APP compared with the 3-axis accelerometer, indicating overestimation. Conclusions: Voice recognition APP appear to be useful for assessing physical activity with high accuracy. However, voice input compliance is an important factor.
Journal Description
JMIR Biomedical Engineering (JBME) is a new sister journal of JMIR (the leading open-access journal in health informatics), focusing on the application of engineering principles, technologies, and medical devices to medicine and biology.
As an open access journal, we are read by clinicians and patients alike and have (as are all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).
During a limited period of time, there are no fees to publish in this journal. Articles are carefully copyedited and XML-tagged, ready for submission in PubMed Central.
Dementia is a neurocognitive disorder, which affects older adults. There are currently no medication treatments available to cure dementia, but a number of biomedical technologies could be useful in assisting patients with dementia. With the continued growth of electronic commerce (e-commerce), online shopping for aging and health-related products will only continue to increase. Using the Tmall marketplace as an example, the purpose of this viewpoint is to describe the current trends of dementia-related products and devices available on an e-commerce platform. Feedback and critiques in the form of consumer reviews should be used to improve the design of dementia-related products. Online medical product consumers, however, must be vigilant about the effectiveness and risks of these biomedical devices.
Background: Stroke is increasingly one of the main causes of impairment and disability. Contextual and empirical evidence demonstrate that, mainly due to service delivery constraints, but also due to a move toward personalized health care in the comfort of patients’ homes, more stroke survivors undergo rehabilitation at home with minimal or no supervision. Due to this trend toward telerehabilitation, systems for stroke patient self-rehabilitation have become increasingly popular, with many solutions recently proposed based on technological advances in sensing, machine learning, and visualization. However, by targeting generic patient profiles, these systems often do not provide adequate rehabilitation service, as they are not tailored to specific patients’ needs. Objective: Our objective was to review state-of-the-art home rehabilitation systems and discuss their effectiveness from a patient-centric perspective. We aimed to analyze engagement enhancement of self-rehabilitation systems, as well as motivation, to identify the challenges in technology uptake. Methods: We performed a systematic literature search with 307,550 results. Then, through a narrative review, we selected 96 sources of existing home rehabilitation systems and we conducted a critical analysis. Based on the critical analysis, we formulated new criteria to be used when designing future solutions, addressing the need for increased patient involvement and individualism. We categorized the criteria based on (1) motivation, (2) acceptance, and (3) technological aspects affecting the incorporation of the technology in practice. We categorized all reviewed systems based on whether they successfully met each of the proposed criteria. Results: The criteria we identified were nonintrusive, nonwearable, motivation and engagement enhancing, individualized, supporting daily activities, cost-effective, simple, and transferable. We also examined the motivation method, suitability for elderly patients, and intended use as supplementary criteria. Through the detailed literature review and comparative analysis, we found no system reported in the literature that addressed all the set criteria. Most systems successfully addressed a subset of the criteria, but none successfully addressed all set goals of the ideal self-rehabilitation system for home use. Conclusions: We identified a gap in the state-of-the-art in telerehabilitation and propose a set of criteria for a novel patient-centric system to enhance patient engagement and motivation and deliver better self-rehabilitation commitment.
Background: Medical device catheters that are used in minimally invasive interventional medical procedures all follow the same integrated design and use paradigm. The features and elements of any catheter device are combined in a single unitary construction. A modular approach to the design, construction, and use of these types of interventional catheters may provide significant advantages and benefits not available with an integrated design paradigm. Objective: This paper aimed to present the design of a modular catheter system and the findings from an initial veterinary use as a case study for the potential of modular catheter systems in general. Methods: A modular catheter system was designed using commercially available angioplasty balloon dilatation catheters as one module in the system and a custom designed scoring adapter as the other module. The scoring adapter incorporates wires to add scoring features to the angioplasty balloon catheter to improve the dilatation performance during a pulmonary valvuloplasty procedure. The scoring adapter also includes a novel attachment mechanism to couple the scoring adapter to any 0.035-inch guidewire–compatible angioplasty balloon catheter. Results: The modular catheter system was successfully designed, manufactured, and used in an initial minimally invasive veterinary cardiovascular intervention to treat a case of canine subvalvular pulmonary stenosis. The scoring adapter and angioplasty balloon catheter were successfully combined tableside in the operating room at the time of the procedure and used to successfully dilate the subvalvular obstruction. Conclusions: The successful design and use of the presented modular catheter system demonstrates the feasibility and potential advantages of this type of paradigm to enable physicians to create interventional catheter devices at the time of a procedure guided by the procedural needs.
Background: A variety of claims are made regarding the effects of surface topography on implant osseointegration. The development of implant surfaces topography has been empirical, requiring numerous in vitro and in vivo tests. Most of these tests were not standardized, using different surfaces, cell populations, or animal models. The exact role of surface chemistry and topography on the early events of the osseointegration of dental implants remains poorly understood. Objective: The aim of this study was to consider the major claims made concerning the effects of titanium implant surface topography on osseointegration. The osseointegration rate of titanium dental implants is related to their composition and surface roughness. The different methods used for increasing surface roughness or applying osteoconductive coatings to titanium dental implants were reviewed. Important findings of consensus were highlighted, and existing controversies were revealed. Methods: This paper considered many of the research publications listed in Medical Literature Analysis and Retrieval System Online and presented in biomedical research publications and textbooks. Surface treatments, such as titanium plasma spraying, grit blasting, acid etching, alkaline etching, anodization, polymer demixing, sol-gel conversion, and their corresponding surface morphologies and properties were described. Results: Many in vitro evaluations are not predictive of or correlated with in vivo outcomes. In some culture models, increased surface topography positively affects proosteogenic cellular activities. Many studies reveal increase in bone-to-implant contact (BIC), with increased surface topography modifications on implant surfaces. Conclusions: Increased implant surface topography improves the BIC and the mechanical properties of the enhanced interface.
Background: As commercial motion tracking technology becomes more readily available, it is necessary to evaluate the accuracy of these systems before using them for biomechanical and motor rehabilitation applications. Objective: This study aimed to evaluate the relative position accuracy of the Oculus Touch controllers in a 2.4 x 2.4 m play-space. Methods: Static data samples (n=180) were acquired from the Oculus Touch controllers at step sizes ranging from 5 to 500 mm along 16 different points on the play-space floor with graph paper in the x (width), y (height), and z (depth) directions. The data were compared with reference values using measurements from digital calipers, accurate to 0.01 mm; physical blocks, for which heights were confirmed with digital calipers; and for larger step sizes (300 and 500 mm), a ruler with hatch marks to millimeter units. Results: It was found that the maximum position accuracy error of the system was 3.5 ± 2.5 mm at the largest step size of 500 mm along the z-axis. When normalized to step size, the largest error found was 12.7 ± 9.9% at the smallest step size in the y-axis at 6.23 mm. When the step size was <10 mm in any direction, the relative position accuracy increased considerably to above 2% (approximately 2 mm at maximum). An average noise value of 0.036 mm was determined. A comparison of these values to cited visual, goniometric, and proprioceptive resolutions concludes that this system is viable for tracking upper-limb movements for biomechanical and rehabilitation applications. The accuracy of the system was also compared with accuracy values from previous studies using other commercially available devices and a multicamera, marker-based professional motion tracking system. Conclusions: The study found that the linear position accuracy of the Oculus Touch controllers was within an agreeable range for measuring human kinematics in rehabilitative upper-limb exercise protocols. Further testing is required to ascertain acceptable repeatability in multiple sessions and rotational accuracy.
Background: Passive joint stiffness can influence the risk of injury and the ability to participate in sports and activities of daily living. However, little is known about how passive joint stiffness changes over time with intensive repetitive exercise, particularly when performing unilateral activities using the dominant upper limb. Objective: This study aimed to investigate the difference in passive wrist quasi-stiffness between the dominant and nondominant upper limb of competitive squash players, compare these results with a previous study on young unskilled subjects, and explore the impact of aging on wrist stiffness. Methods: A total of 7 healthy, right-side dominant male competitive squash players were recruited and examined using the Massachusetts Institute of Technology Wrist-Robot. Subjects were aged between 24 and 72 years (mean 43.7, SD 16.57) and had a mean of 20.6 years of squash playing experience (range 10-53 years, SD 13.85). Torque and displacement data were processed and applied to 2 different estimation methods, the fitting ellipse and the multiple regression method, to obtain wrist stiffness magnitude and orientation. Results: Young squash players (mean 30.75, SD 8.06 years) demonstrated a stiffer dominant wrist, with an average ratio of 1.51, compared with an average ratio of 1.18 in young unskilled subjects. The older squash players (mean 64.67, SD 6.35 years) revealed an average ratio of 0.86 (ie, the nondominant wrist was stiffer than the dominant wrist). There was a statistically significant difference between the magnitude of passive quasi-stiffness between the dominant and nondominant wrist of the young and older squash player groups (P=.004). Conclusions: Findings from this pilot study are novel and contribute to our understanding of the likely long-term effect of highly intensive, unilateral sports on wrist quasi-stiffness and the aging process: adults who participate in repetitive sporting exercise may experience greater joint quasi-stiffness when they are younger than 45 years and more flexibility when they are older than 60 years.
Background: Over the past 60 years, no technique used for treating cartilage disorders has been completely successful. Bioprinting provides a highly anticipated, novel alternative solution to this problem. However, identifying barriers to this new technology is crucial in order to overcome them when bioprinting reaches the implementation stage. This kind of research has been declared essential because clinical efficacy and safety studies alone do not always lead to successful implementation. Objective: This qualitative study aimed to explore the stance of orthopedic surgeons on the use of bioprinted cartilage grafts for cartilaginous lesions. The study sought to summarize and classify the barriers and facilitators of this technique and to identify the key factors for successful implementation of bioprinted cartilage in routine clinical practice. Methods: A qualitative thematic analysis method was used to evaluate data obtained from semistructured interviews and from focus groups. Data were collected between June 2017 and February 2018. Interviews focused on the collection of expert opinions on bioprinted cartilage. Results: The perceived barriers to the adoption of this technology were (1) awareness of a lack of information on the status and possibilities of this technology, (2) uncertainty regarding compliance with current health care regulations and policies, and (3) demands for clinical evidence. The facilitators were (1) lack of surgical alternatives, (2) the perception that research is the basis of the current health system, and (3) the hope of offering a better quality of life to patients. Conclusions: The results of this study are preliminary in nature and cannot be generalized without a broader group of participants. However, the key factors identified provide a frame of reference to help understand the challenges of bioprinted cartilage and help facilitate the transition toward its clinical use. These findings will also provide information for use at multidisciplinary meetings in scientific societies; create bridges between researchers, orthopedic surgeons, and regulators; and open a debate on the funding of this technique and the business model that needs to be developed.
Background: One of the problems in evaluating clinical practice guidelines (CPGs) is the occurrence of knowledge gaps. These gaps may occur when evaluation logics and definitions in analytics pipelines are translated differently. Objective: The objective of this paper is to develop a systematic method that will fill in the cognitive and computational gaps of CPG knowledge components in analytics pipelines. Methods: We used locally developed CPGs that resulted in care process models (CPMs). We derived adherence definitions from the CPMs, transformed them into computationally executable queries, and deployed them into an enterprise knowledge base that specializes in managing clinical knowledge content. We developed a visual analytics framework, whose data pipelines are connected to queries in the knowledge base, to automate the extraction of data from clinical databases and calculation of evaluation metrics. Results: In this pilot study, we implemented 21 CPMs within the proposed framework, which is connected to an enterprise data warehouse (EDW) as a data source. We built a Web–based dashboard for monitoring and evaluating adherence to the CPMs. The dashboard ran for 18 months during which CPM adherence definitions were updated a number of times. Conclusions: The proposed framework was demonstrated to accommodate complicated knowledge management for CPM adherence evaluation in analytics pipelines using a knowledge base. At the same time, knowledge consistency and computational efficiency were maintained.
Background: Heart rate variability (HRV) is derived from the series of R-R intervals extracted from an electrocardiographic (ECG) measurement. Ideally all components of the R-R series are the result of sinoatrial node depolarization. However, the actual R-R series are contaminated by outliers due to heart rhythm disturbances such as ectopic beats, which ought to be detected and corrected appropriately before HRV analysis. Objective: We have introduced a novel, lightweight, and near real-time method to detect and correct anomalies in the R-R series based on the singular spectrum analysis (SSA). This study aimed to assess the performance of the proposed method in terms of (1) detection performance (sensitivity, specificity, and accuracy); (2) root mean square error (RMSE) between the actual N-N series and the approximated outlier-cleaned R-R series; and (3) how it benchmarks against a competitor in terms of the relative RMSE. Methods: A lightweight SSA-based change-point detection procedure, improved through the use of a cumulative sum control chart with adaptive thresholds to reduce detection delays, monitored the series of R-R intervals in real time. Upon detection of an anomaly, the corrupted segment was substituted with the respective outlier-cleaned approximation obtained using recurrent SSA forecasting. Next, N-N intervals from a 5-minute ECG segment were extracted from each of the 18 records in the MIT-BIH Normal Sinus Rhythm Database. Then, for each such series, a number (randomly drawn integer between 1 and 6) of simulated ectopic beats were inserted at random positions within the series and results were averaged over 1000 Monte Carlo runs. Accordingly, 18,000 R-R records corresponding to 5-minute ECG segments were used to assess the detection performance whereas another 180,000 (10,000 for each record) were used to assess the error introduced in the correction step. Overall 198,000 R-R series were used in this study. Results: The proposed SSA-based algorithm reliably detected outliers in the R-R series and achieved an overall sensitivity of 96.6%, specificity of 98.4% and accuracy of 98.4%. Furthermore, it compared favorably in terms of discrepancies of the cleaned R-R series compared with the actual N-N series, outperforming an established correction method on average by almost 30%. Conclusions: The proposed algorithm, which leverages the power and versatility of the SSA to both automatically detect and correct artifacts in the R-R series, provides an effective and efficient complementary method and a potential alternative to the current manual-editing gold standard. Other important characteristics of the proposed method include the ability to operate in near real-time, the almost entirely model-free nature of the framework which does not require historical training data, and its overall low computational complexity.
Background: mHealth apps that measure heart rate using pulse photoplethysmography (PPG) are classified as class II (moderate-risk) Food and Drug Administration devices; therefore, these devices need clinical validation prior to public release. The Auralife Instant Blood Pressure app (AuraLife IBP app) is an mHealth app that measures blood pressure inaccurately based on a previous validation study. Its ability to measure heart rate has not been previously reported. Objective: The objective of our study was to assess the accuracy and precision of the AuraLife IBP app in measuring heart rate. Methods: We enrolled 85 adults from ambulatory clinics. Two measurements were obtained using the AuraLife IBP app, and 2 other measurements were achieved with a oscillometric device. The order of devices was randomized. Accuracy was assessed by calculating the relative and absolute mean differences between heart rate measurements obtained using each AuraLife IBP app and an average of both standard heart rate measurements. Precision was assessed by calculating the relative and absolute mean differences between individual measurements in the pair for each device. Results: The relative and absolute mean (SD) differences between the devices were 1.1 (3.5) and 2.8 (2.4) beats per minute (BPM), respectively. Meanwhile, the within-device relative and absolute mean differences, respectively, were <0.1 (2.2) and 1.7 (1.4) BPM for the standard device and −0.1 (3.2) and 2.2 (2.3) BPM for the AuraLife IBP app. Conclusions: The AuraLife IBP app had a high degree of accuracy and precision in the measurement of heart rate. This supports the use of PPG technology in smartphones for monitoring resting heart rate.
Background: The proposed experimental design was devised to determine whether a relationship exists between the occlusal load applied and the size of the markings produced from tooth contact when dental articulating paper and T-Scan are interposed alternatively. Objective: The objective of our study was to compare the relationship between contact markings on an articulating paper and T-Scan for an applied occlusal load. Methods: In this in vitro study, dentulous maxillary and mandibular dies were mounted on a metal jig and articulating paper and T-Scan sensor were placed alternatively between the casts. Loads simulating occlusal loads began at 25 N and incrementally continued up to 450 N. The resultant markings (180 marks resulting from articulating paper and 138 from T-Scan) were photographed, and the marks were analyzed using MOTIC image analysis and sketching software. Descriptive statistical analyses were performed using one-way analysis of variance, Student t test, and Pearson correlation coefficient method. Results: Statistical interpretation of the data indicated that with articulating paper, the mark area increased nonlinearly with increasing load and there was a false-positive result. The characteristics of the paper mark appearance did not describe the amount of occlusal load present on a given tooth. The contact marking obtained using T-Scan for an applied occlusal load indicated that the mark area increased with increase in the load and provided more predictable results of actual load content within the occlusal contact. Conclusions: The size of an articulating paper mark may not be a reliable predictor of the actual load content within the occlusal contact, whereas a T-Scan provides more predictable results of the actual load content within the occlusal contact.
Background: The use of Web-based physical activity systems has been proposed as an easy method for collecting physical activity data. Behavior recording using a voice recognition system via the WEB...
Background: The use of Web-based physical activity systems has been proposed as an easy method for collecting physical activity data. Behavior recording using a voice recognition system via the WEB might be effective. Objective: The objective of this study was to develop a behavior-recording application (APP) using voice recognition. The results from our developed APP were compared with objective data from a 3-axis accelerometer to assess the strengths and weaknesses of the new measurement system. Methods: A total of 20 participants (14 men, 6 women, 19.1 (SD 0.9) years of age) wore a 3-axis accelerometer and inputted behavioral data into their smartphones for a period of 7 days. The measure of intensity was metabolic equivalents (METs). Results: The Pearson correlations for the METs between the two methods were all positive and significant when the analysis was for over 10 hours, r = 0.545 (P =.017), and for over 14 hours with voice input, r = 0.750 (P =.008). The Bland-Altman 95% limits of agreement ranged from –0.35 to 0.54 METs (over 10 hours) and -0.26 to 0.47 (over 14 hours) between the two methods. The exercise intensity was higher according to the APP compared with the 3-axis accelerometer, indicating overestimation. Conclusions: Voice recognition APP appear to be useful for assessing physical activity with high accuracy. However, voice input compliance is an important factor.
