@Article{info:doi/10.2196/10126,
author="Steijlen, SM Annemarijn
and Jansen, MB Kaspar
and Albayrak, Armagan
and Verschure, O. Derk
and Van Wijk, F. Diederik",
title="A Novel 12-Lead Electrocardiographic System for Home Use: Development and Usability Testing",
journal="JMIR Mhealth Uhealth",
year="2018",
month="Jul",
day="30",
volume="6",
number="7",
pages="e10126",
keywords="12-lead ECG system",
keywords="electrocardiography",
keywords="home use",
keywords="handheld",
keywords="user-centered design",
abstract="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. ",
doi="10.2196/10126",
url="http://mhealth.jmir.org/2018/7/e10126/",
url="http://www.ncbi.nlm.nih.gov/pubmed/30061094"
}


@Article{info:doi/10.2196/mhealth.9884,
author="Lee, Jie-Eun
and Lee, Hwa Dong
and Oh, Jung Tae
and Kim, Min Kyoung
and Choi, Hee Sung
and Lim, Soo
and Park, Joo Young
and Park, Joon Do
and Jang, Chul Hak
and Moon, Hoon Jae",
title="Clinical Feasibility of Monitoring Resting Heart Rate Using a Wearable Activity Tracker in Patients With Thyrotoxicosis: Prospective Longitudinal Observational Study",
journal="JMIR Mhealth Uhealth",
year="2018",
month="Jul",
day="13",
volume="6",
number="7",
pages="e159",
keywords="activity tracker",
keywords="wearable device",
keywords="heart rate",
keywords="thyrotoxicosis",
keywords="hyperthyroidism",
keywords="Graves' disease",
abstract="Background: Symptoms and signs of thyrotoxicosis are nonspecific and assessing its clinical status is difficult with conventional physical examinations and history taking. Increased heart rate (HR) is one of the easiest signs to quantify this, and current wearable devices can monitor HR. Objective: We assessed the association between thyroid function and resting HR measured by a wearable activity tracker (WD-rHR) and evaluated the clinical feasibility of using this method in patients with thyrotoxicosis. Methods: Thirty patients with thyrotoxicosis and 10 controls were included in the study. Participants were instructed to use the wearable activity tracker during the study period so that activity and HR data could be collected. The primary study outcomes were verification of changes in WD-rHR during thyrotoxicosis treatment and associations between WD-rHR and thyroid function. Linear and logistic model generalized estimating equation analyses were performed and the results were compared to conventionally obtained resting HR during clinic visits (on-site resting HR) and the Hyperthyroidism Symptom Scale. Results: WD-rHR was higher in thyrotoxic patients than in the control groups and decreased in association with improvement of thyrotoxicosis. A one standard deviation--increase of WD-rHR of about 11 beats per minute (bpm) was associated with the increase of serum free T4 levels (beta=.492, 95\% CI 0.367-0.616, P<.001) and thyrotoxicosis risk (odds ratio [OR] 3.840, 95\% CI 2.113-6.978, P<.001). Although the Hyperthyroidism Symptom Scale showed similar results with WD-rHR, a 1 SD-increase of on-site rHR (about 16 beats per minute) showed a relatively lower beta and OR (beta=.396, 95\% CI 0.204-0.588, P<.001; OR 2.114, 95\% CI 1.365-3.273, P<.001) compared with WD-rHR. Conclusions: Heart rate data measured by a wearable device showed reasonable predictability of thyroid function. This simple, easy-to-measure parameter is clinically feasible and has the potential to manage thyroid dysfunction. Trial Registration: ClinicalTrials.gov NCT03009357; https://clinicaltrials.gov/ct2/show/NCT03009357 (Archived by WebCite at http://www.webcitation.org/70h55Llyg) ",
doi="10.2196/mhealth.9884",
url="http://mhealth.jmir.org/2018/7/e159/",
url="http://www.ncbi.nlm.nih.gov/pubmed/30006328"
}


@Article{info:doi/10.2196/10108,
author="Sartor, Francesco
and Papini, Gabriele
and Cox, Elisabeth Lieke Gertruda
and Cleland, John",
title="Methodological Shortcomings of Wrist-Worn Heart Rate Monitors Validations",
journal="J Med Internet Res",
year="2018",
month="Jul",
day="02",
volume="20",
number="7",
pages="e10108",
keywords="sensor technology",
keywords="accuracy",
keywords="wearable",
keywords="telemonitoring",
doi="10.2196/10108",
url="http://www.jmir.org/2018/7/e10108/",
url="http://www.ncbi.nlm.nih.gov/pubmed/29967000"
}


@Article{info:doi/10.2196/mhealth.9604,
author="Conn, J. Nicholas
and Schwarz, Q. Karl
and Borkholder, A. David",
title="Nontraditional Electrocardiogram and Algorithms for Inconspicuous In-Home Monitoring: Comparative Study",
journal="JMIR Mhealth Uhealth",
year="2018",
month="May",
day="28",
volume="6",
number="5",
pages="e120",
keywords="algorithms",
keywords="delineation",
keywords="ECG",
keywords="EDB",
keywords="electrocardiogram",
keywords="Internet of Things",
keywords="IoT",
keywords="MITDB",
keywords="signal quality",
keywords="wearable",
abstract="Background: Wearable and connected in-home medical devices are typically utilized in uncontrolled environments and often measure physiologic signals at suboptimal locations. Motion artifacts and reduced signal-to-noise ratio, compared with clinical grade equipment, results in a highly variable signal quality that can change significantly from moment to moment. The use of signal quality classification algorithms and robust feature delineation algorithms designed to achieve high accuracy on poor quality physiologic signals can prove beneficial in addressing concerns associated with measurement accuracy, confidence, and clinical validity. Objective: The objective of this study was to demonstrate the successful extraction of clinical grade measures using a custom signal quality classification algorithm for the rejection of poor-quality regions and a robust QRS delineation algorithm from a nonstandard electrocardiogram (ECG) integrated into a toilet seat; a device plagued by many of the same challenges as wearable technologies and other Internet of Things--based medical devices. Methods: The present algorithms were validated using a study of 25 normative subjects and 29 heart failure (HF) subjects. Measurements captured from a toilet seat-based buttocks electrocardiogram were compared with a simultaneously captured 12-lead clinical grade ECG. The ECG lead with the highest morphological correlation to buttocks electrocardiogram was used to determine the accuracy of the heart rate (HR), heart rate variability (HRV), which used the standard deviation of the normal-to-normal (SDNN) intervals between sinus beats, QRS duration, and the corrected QT interval (QTc). These algorithms were benchmarked using the MIT-BIH Arrhythmia Database (MITDB) and European ST-T Database (EDB), which are standardized databases commonly used to test QRS detection algorithms. Results: Clinical grade accuracy was achieved for all buttocks electrocardiogram measures compared with standard Lead II. For the normative cohort, the mean was ?0.0 (SD 0.3) bpm (N=141 recordings) for HR accuracy and ?1.0 (SD 3.4) ms for HRV (N=135). The QRS duration and the QTc interval had an accuracy of ?0.5 (SD 6.6) ms (N=85) and 14.5 (SD 11.1) ms (N=85), respectively. In the HF cohort, the accuracy for HR, HRV, QRS duration, and QTc interval was 0.0 (SD 0.3) bpm (N=109), ?6.6 (SD 13.2) ms (N=99), 2.9 (SD 11.5) ms (N=59), and 11.2 (SD 19.1) ms (N=58), respectively. When tested on MITDB and EDB, the algorithms presented herein had an overall sensitivity and positive predictive value of over 99.82\% (N=900,059 total beats), which is comparable to best in-class algorithms tuned specifically for use with these databases. Conclusions: The present algorithmic approach to data analysis of noisy physiologic data was successfully demonstrated using a toilet seat-based ECG remote monitoring system. This approach to the analysis of physiologic data captured from wearable and connected devices has future potential to enable new types of monitoring devices, providing new insights through daily, inconspicuous in-home monitoring. ",
doi="10.2196/mhealth.9604",
url="http://mhealth.jmir.org/2018/5/e120/"
}


@Article{info:doi/10.2196/cardio.9534,
author="Kehl, Devin
and Zimmer, Raymond
and Sudan, Madhuri
and Kedan, Ilan",
title="Handheld Ultrasound as a Novel Predictive Tool in Atrial Fibrillation: Prediction of Outcomes Following Electrical Cardioversion",
journal="JMIR Cardio",
year="2018",
month="Mar",
day="08",
volume="2",
number="1",
pages="e7",
keywords="atrial fibrillation",
keywords="cardioversion",
keywords="recurrence",
keywords="inferior vena cava",
keywords="hand held ultrasound",
keywords="point of care",
abstract="Background: Atrial fibrillation (AF) recurrence after successful direct current cardioversion (CV) is common, and clinical predictors may be useful. We evaluated the risk of early AF recurrence according to inferior vena cava (IVC) measurements by handheld ultrasound (HHU) at the time of CV. Objective: Assess HHU and objectively obtained measurements acquired at the point of care as potential clinical predictors of future clinical outcomes in patients with AF undergoing CV. Methods: Maximum IVC diameter (IVCd) and collapsibility with inspiration were measured by the Vscan HHU (General Electric Healthcare Division) in 128 patients immediately before and after successful CV for AF. Patients were followed by chart review for recurrence of AF. Results: Mean IVCd was 2.16 cm in AF pre-CV and 2.01 cm in sinus rhythm post-CV (P<.001). AF recurred within 30 days of CV in 34 of 128 patients (26.6\%). Among patients with IVCd <2.1 cm pre-CV and decrease in IVCd post-CV, AF recurrence was 12.1\%, compared to 31.6\% in patients not meeting these parameters (odds ratio [OR] 0.299, P=.04). This association persisted after adjustment for age, ejection fraction <50\%, left atrial enlargement, and amiodarone use (adjusted OR 0.185, P=.01). Among patients with IVCd post-CV <1.7 cm, AF recurrence was 13.5\%, compared to 31.9\% in patients not meeting this parameter (OR 0.185, P=.01). IVC parameters did not predict AF recurrence at 180 or 365 days. Conclusions: The presence of a normal IVCd pre-CV that becomes smaller post-CV and the presence of a small IVCd post-CV were each independently associated with reduced likelihood of early, but not late, AF recurrence. HHU assessment of IVCd at the time of CV may be useful to identify patients at low risk of early recurrence of AF after CV. ",
doi="10.2196/cardio.9534",
url="http://cardio.jmir.org/2018/1/e7/"
}


@Article{info:doi/10.2196/mhealth.8946,
author="Kang, Si-Hyuck
and Joe, Byunggill
and Yoon, Yeonyee
and Cho, Goo-Yeong
and Shin, Insik
and Suh, Jung-Won",
title="Cardiac Auscultation Using Smartphones: Pilot Study",
journal="JMIR Mhealth Uhealth",
year="2018",
month="Feb",
day="28",
volume="6",
number="2",
pages="e49",
keywords="cardiac auscultation",
keywords="physical examination",
keywords="smartphone",
keywords="mobile health care",
keywords="telemedicine",
abstract="Background: Cardiac auscultation is a cost-effective, noninvasive screening tool that can provide information about cardiovascular hemodynamics and disease. However, with advances in imaging and laboratory tests, the importance of cardiac auscultation is less appreciated in clinical practice. The widespread use of smartphones provides opportunities for nonmedical expert users to perform self-examination before hospital visits. Objective: The objective of our study was to assess the feasibility of cardiac auscultation using smartphones with no add-on devices for use at the prehospital stage. Methods: We performed a pilot study of patients with normal and pathologic heart sounds. Heart sounds were recorded on the skin of the chest wall using 3 smartphones: the Samsung Galaxy S5 and Galaxy S6, and the LG G3. Recorded heart sounds were processed and classified by a diagnostic algorithm using convolutional neural networks. We assessed diagnostic accuracy, as well as sensitivity, specificity, and predictive values. Results: A total of 46 participants underwent heart sound recording. After audio file processing, 30 of 46 (65\%) heart sounds were proven interpretable. Atrial fibrillation and diastolic murmur were significantly associated with failure to acquire interpretable heart sounds. The diagnostic algorithm classified the heart sounds into the correct category with high accuracy: Galaxy S5, 90\% (95\% CI 73\%-98\%); Galaxy S6, 87\% (95\% CI 69\%-96\%); and LG G3, 90\% (95\% CI 73\%-98\%). Sensitivity, specificity, positive predictive value, and negative predictive value were also acceptable for the 3 devices. Conclusions: Cardiac auscultation using smartphones was feasible. Discrimination using convolutional neural networks yielded high diagnostic accuracy. However, using the built-in microphones alone, the acquisition of reproducible and interpretable heart sounds was still a major challenge. Trial Registration: ClinicalTrials.gov NCT03273803; https://clinicaltrials.gov/ct2/show/NCT03273803 (Archived by WebCite at http://www.webcitation.org/6x6g1fHIu) ",
doi="10.2196/mhealth.8946",
url="http://mhealth.jmir.org/2018/2/e49/",
url="http://www.ncbi.nlm.nih.gov/pubmed/29490899"
}


@Article{info:doi/10.2196/cardio.8574,
author="Abt, Grant
and Bray, James
and Benson, Clare Amanda",
title="Measuring Moderate-Intensity Exercise with the Apple Watch: Validation Study",
journal="JMIR Cardio",
year="2018",
month="Feb",
day="28",
volume="2",
number="1",
pages="e6",
keywords="smartwatch",
keywords="wearables",
keywords="technology",
keywords="physical activity",
keywords="cardiovascular health, Apple Watch",
abstract="Background: Moderate fitness levels and habitual exercise have a protective effect for cardiovascular disease, stroke, type 2 diabetes, and all-cause mortality. The Apple Watch displays exercise completed at an intensity of a brisk walk or above using a green ``exercise'' ring. However, it is unknown if the exercise ring accurately represents an exercise intensity comparable to that defined as moderate-intensity. In order for health professionals to prescribe exercise intensity with confidence, consumer wearable devices need to be accurate and precise if they are to be used as part of a personalized medicine approach to disease management. Objective: The aim of this study was to examine the validity and reliability of the Apple Watch for measuring moderate-intensity exercise, as defined as 40-59\% oxygen consumption reserve (VO2R). Methods: Twenty recreationally active participants completed resting oxygen consumption (VO2rest) and maximal oxygen consumption (VO2 max) tests prior to a series of 5-minute bouts of treadmill walking at increasing speed while wearing an Apple Watch on both wrists, and with oxygen consumption measured continuously. Five-minute exercise bouts were added until the Apple Watch advanced the green ``exercise'' ring by 5 minutes (defined as the treadmill inflection speed). Validity was examined using a one-sample t-test, with interdevice and intradevice reliability reported as the standardized typical error and intraclass correlation. Results: The mean \%VO2R at the treadmill inflection speed was 30\% (SD 7) for both Apple Watches. There was a large underestimation of moderate-intensity exercise (left hand: mean difference = -10\% [95\% CI -14 to -7], d=-1.4; right hand: mean difference = -10\% [95\% CI -13 to -7], d=-1.5) when compared to the criterion of 40\% VO2R. Standardized typical errors for \%VO2R at the treadmill inflection speed were small to moderate, with intraclass correlations higher within trials compared to between trials. Conclusions: The Apple Watch threshold for moderate-intensity exercise was lower than the criterion, which would lead to an overestimation of moderate-intensity exercise minutes completed throughout the day. ",
doi="10.2196/cardio.8574",
url="http://cardio.jmir.org/2018/1/e6/"
}


@Article{info:doi/10.2196/cardio.8199,
author="Rozanski, M. Gabriela
and Aqui, Anthony
and Sivakumaran, Shajicaa
and Mansfield, Avril",
title="Consumer Wearable Devices for Activity Monitoring Among Individuals After a Stroke: A Prospective Comparison",
journal="JMIR Cardio",
year="2018",
month="Jan",
day="04",
volume="2",
number="1",
pages="e1",
keywords="physical activity",
keywords="heart rate",
keywords="accelerometry",
keywords="stroke rehabilitation",
keywords="walking",
abstract="Background: Activity monitoring is necessary to investigate sedentary behavior after a stroke. Consumer wearable devices are an attractive alternative to research-grade technology, but measurement properties have not been established. Objective: The purpose of this study was to determine the accuracy of 2 wrist-worn fitness trackers: Fitbit Charge HR (FBT) and Garmin Vivosmart (GAR). Methods: Adults attending in- or outpatient therapy for stroke (n=37) wore FBT and GAR each on 2 separate days, in addition to an X6 accelerometer and Actigraph chest strap monitor. Step counts and heart rate data were extracted, and the agreement between devices was determined using Pearson or Spearman correlation and paired t or Wilcoxon signed rank tests (one- and two-sided). Subgroup analyses were conducted. Results: Step counts from FBT and GAR positively correlated with the X6 accelerometer ($\rho$=.78 and $\rho$=.65, P<.001, respectively) but were significantly lower (P<.01). For individuals using a rollator, there was no significant correlation between step counts from the X6 accelerometer and either FBT ($\rho$=.42, P=.12) or GAR ($\rho$=.30, P=.27). Heart rate from Actigraph, FBT, and GAR demonstrated responsiveness to changes in activity. Both FBT and GAR positively correlated with Actigraph for average heart rate (r=.53 and .75, P<.01, respectively) and time in target zone ($\rho$=.49 and .74, P<.01, respectively); these measures were not significantly different, but nonequivalence was found. Conclusions: FBT and GAR had moderate to strong correlation with best available reference measures of walking activity in individuals with subacute stroke. Accuracy appears to be lower among rollator users and varies according to heart rhythm. Consumer wearables may be a viable option for large-scale studies of physical activity. ",
doi="10.2196/cardio.8199",
url="http://cardio.jmir.org/2018/1/e1/"
}


@Article{info:doi/10.2196/cardio.8301,
author="Moayedi, Yasbanoo
and Abdulmajeed, Raghad
and Duero Posada, Juan
and Foroutan, Farid
and Alba, Carolina Ana
and Cafazzo, Joseph
and Ross, Joan Heather",
title="Assessing the Use of Wrist-Worn Devices in Patients With Heart Failure: Feasibility Study",
journal="JMIR Cardio",
year="2017",
month="Dec",
day="19",
volume="1",
number="2",
pages="e8",
keywords="MeSH: exercise physiology",
keywords="heart rate tracker",
keywords="wrist worn devices",
keywords="Fitbit",
keywords="Apple watch",
keywords="heart failure",
keywords="steps",
abstract="Background: Exercise capacity and raised heart rate (HR) are important prognostic markers in patients with heart failure (HF). There has been significant interest in wrist-worn devices that track activity and HR. Objective: We aimed to assess the feasibility and accuracy of HR and activity tracking of the Fitbit and Apple Watch. Methods: We conducted a two-phase study assessing the accuracy of HR by Apple Watch and Fitbit in healthy participants. In Phase 1, 10 healthy individuals wore a Fitbit, an Apple Watch, and a GE SEER Light 5-electrode Holter monitor while exercising on a cycle ergometer with a 10-watt step ramp protocol from 0-100 watts. In Phase 2, 10 patients with HF and New York Heart Association (NYHA) Class II-III symptoms wore wrist devices for 14 days to capture overall step count/exercise levels. Results: Recorded HR by both wrist-worn devices had the best agreement with Holter readings at a workload of 60-100 watts when the rate of change of HR is less dynamic. Fitbit recorded a mean 8866 steps/day for NYHA II patients versus 4845 steps/day for NYHA III patients (P=.04). In contrast, Apple Watch recorded a mean 7027 steps/day for NYHA II patients and 4187 steps/day for NYHA III patients (P=.08). Conclusions: Both wrist-based devices are best suited for static HR rate measurements. In an outpatient setting, these devices may be adequate for average HR in patients with HF. When assessing exercise capacity, the Fitbit better differentiated patients with NYHA II versus NYHA III by the total number of steps recorded. This exploratory study indicates that these wrist-worn devices show promise in prognostication of HF in the continuous monitoring of outpatients. ",
doi="10.2196/cardio.8301",
url="http://cardio.jmir.org/2017/2/e8/"
}


@Article{info:doi/10.2196/jmir.8066,
author="Smeets, JP Christophe
and Vranken, Julie
and Van der Auwera, Jo
and Verbrugge, H. Frederik
and Mullens, Wilfried
and Dupont, Matthias
and Grieten, Lars
and De Canni{\`e}re, H{\'e}l{\`e}ne
and Lanssens, Dorien
and Vandenberk, Thijs
and Storms, Valerie
and Thijs, M. Inge
and Vandervoort, M. Pieter",
title="Bioimpedance Alerts from Cardiovascular Implantable Electronic Devices: Observational Study of Diagnostic Relevance and Clinical Outcomes",
journal="J Med Internet Res",
year="2017",
month="Nov",
day="23",
volume="19",
number="11",
pages="e393",
keywords="defibrillators, implantable",
keywords="cardiac resynchronization therapy",
keywords="telemedicine",
keywords="electric impedance",
keywords="algorithms",
keywords="call centers",
abstract="Background: The use of implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT) devices is expanding in the treatment of heart failure. Most of the current devices are equipped with remote monitoring functions, including bioimpedance for fluid status monitoring. The question remains whether bioimpedance measurements positively impact clinical outcome. Objective: The aim of this study was to provide a comprehensive overview of the clinical interventions taken based on remote bioimpedance monitoring alerts and their impact on clinical outcome. Methods: This is a single-center observational study of consecutive ICD and CRT patients (n=282) participating in protocol-driven remote follow-up. Bioimpedance alerts were analyzed with subsequently triggered interventions. Results: A total of 55.0\% (155/282) of patients had an ICD or CRT device equipped with a remote bioimpedance algorithm. During 34 (SD 12)?months of follow-up, 1751 remote monitoring alarm notifications were received (2.2 per patient-year of follow-up), comprising 2096 unique alerts (2.6 per patient-year of follow-up). Since 591 (28.2\%) of all incoming alerts were bioimpedance-related, patients with an ICD or CRT including a bioimpedance algorithm had significantly more alerts (3.4 versus 1.8 alerts per patient-year of follow-up, P<.001). Bioimpedance-only alerts resulted in a phone contact in 91.0\% (498/547) of cases, which triggered an actual intervention in 15.9\% (87/547) of cases, since in 75.1\% (411/547) of cases reenforcing heart failure education sufficed. Overall survival was lower in patients with a cardiovascular implantable electronic device with a bioimpedance algorithm; however, this difference was driven by differences in baseline characteristics (adjusted hazard ratio of 2.118, 95\% CI 0.845-5.791). No significant differences between both groups were observed in terms of the number of follow-up visits in the outpatient heart failure clinic, the number of hospital admissions with a primary diagnosis of heart failure, or mean length of hospital stay. Conclusions: Bioimpedance-only alerts constituted a substantial amount of incoming alerts when turned on during remote follow-up and triggered an additional intervention in only 16\% of cases since in 75\% of cases, providing general heart failure education sufficed. The high frequency of heart failure education that was provided could have contributed to fewer heart failure--related hospitalizations despite significant differences in baseline characteristics. ",
doi="10.2196/jmir.8066",
url="http://www.jmir.org/2017/11/e393/",
url="http://www.ncbi.nlm.nih.gov/pubmed/29170147"
}


@Article{info:doi/10.2196/mhealth.8233,
author="Gorny, Wilhelm Alexander
and Liew, Jia Seaw
and Tan, Seng Chuen
and M{\"u}ller-Riemenschneider, Falk",
title="Fitbit Charge HR Wireless Heart Rate Monitor: Validation Study Conducted Under Free-Living Conditions",
journal="JMIR Mhealth Uhealth",
year="2017",
month="Oct",
day="20",
volume="5",
number="10",
pages="e157",
keywords="heart rate",
keywords="photoplethysmography",
keywords="telemedicine",
keywords="validation studies",
abstract="Background: Many modern smart watches and activity trackers feature an optical sensor that estimates the wearer's heart rate. Recent studies have evaluated the performance of these consumer devices in the laboratory. Objective: The objective of our study was to examine the accuracy and sensitivity of a common wrist-worn tracker device in measuring heart rates and detecting 1-min bouts of moderate to vigorous physical activity (MVPA) under free-living conditions. Methods: Ten healthy volunteers were recruited from a large university in Singapore to participate in a limited field test, followed by a month of continuous data collection. During the field test, each participant would wear one Fitbit Charge HR activity tracker and one Polar H6 heart rate monitor. Fitbit measures were accessed at 1-min intervals, while Polar readings were available for 10-s intervals. We derived intraclass correlation coefficients (ICCs) for individual participants comparing heart rate estimates. We applied Centers for Disease Control and Prevention heart rate zone cut-offs to ascertain the sensitivity and specificity of Fitbit in identifying 1-min epochs falling into MVPA heart rate zone. Results: We collected paired heart rate data for 2509 1-min epochs in 10 individuals under free-living conditions of 3 to 6 hours. The overall ICC comparing 1-min Fitbit measures with average 10-s Polar H6 measures for the same epoch was .83 (95\% CI .63-.91). On average, the Fitbit tracker underestimated heart rate measures by ?5.96 bpm (standard error, SE=0.18). At the low intensity heart rate zone, the underestimate was smaller at ?4.22 bpm (SE=0.15). This underestimate grew to ?16.2 bpm (SE=0.74) in the MVPA heart rate zone. Fitbit devices detected 52.9\% (192/363) of MVPA heart rate zone epochs correctly. Positive and negative predictive values were 86.1\% (192/223) and 92.52\% (2115/2286), respectively. During subsequent 1 month of continuous data collection (270 person-days), only 3.9\% of 1-min epochs could be categorized as MVPA according to heart rate zones. This measure was affected by decreasing wear time and adherence over the period of follow-up. Conclusions: Under free-living conditions, Fitbit trackers are affected by significant systematic errors. Improvements in tracker accuracy and sensitivity when measuring MVPA are required before they can be considered for use in the context of exercise prescription to promote better health. ",
doi="10.2196/mhealth.8233",
url="http://mhealth.jmir.org/2017/10/e157/",
url="http://www.ncbi.nlm.nih.gov/pubmed/29055881"
}


@Article{info:doi/10.2196/mhealth.7254,
author="Vandenberk, Thijs
and Stans, Jelle
and Mortelmans, Christophe
and Van Haelst, Ruth
and Van Schelvergem, Gertjan
and Pelckmans, Caroline
and Smeets, JP Christophe
and Lanssens, Dorien
and De Canni{\`e}re, H{\'e}l{\`e}ne
and Storms, Valerie
and Thijs, M. Inge
and Vaes, Bert
and Vandervoort, M. Pieter",
title="Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study",
journal="JMIR Mhealth Uhealth",
year="2017",
month="Aug",
day="25",
volume="5",
number="8",
pages="e129",
keywords="heart rate",
keywords="software validation",
keywords="remote sensing technology",
abstract="Background: Photoplethysmography (PPG) is a proven way to measure heart rate (HR). This technology is already available in smartphones, which allows measuring HR only by using the smartphone. Given the widespread availability of smartphones, this creates a scalable way to enable mobile HR monitoring. An essential precondition is that these technologies are as reliable and accurate as the current clinical (gold) standards. At this moment, there is no consensus on a gold standard method for the validation of HR apps. This results in different validation processes that do not always reflect the veracious outcome of comparison. Objective: The aim of this paper was to investigate and describe the necessary elements in validating and comparing HR apps versus standard technology. Methods: The FibriCheck (Qompium) app was used in two separate prospective nonrandomized studies. In the first study, the HR of the FibriCheck app was consecutively compared with 2 different Food and Drug Administration (FDA)-cleared HR devices: the Nonin oximeter and the AliveCor Mobile ECG. In the second study, a next step in validation was performed by comparing the beat-to-beat intervals of the FibriCheck app to a synchronized ECG recording. Results: In the first study, the HR (BPM, beats per minute) of 88 random subjects consecutively measured with the 3 devices showed a correlation coefficient of .834 between FibriCheck and Nonin, .88 between FibriCheck and AliveCor, and .897 between Nonin and AliveCor. A single way analysis of variance (ANOVA; P=.61 was executed to test the hypothesis that there were no significant differences between the HRs as measured by the 3 devices. In the second study, 20,298 (ms) R-R intervals (RRI)--peak-to-peak intervals (PPI) from 229 subjects were analyzed. This resulted in a positive correlation (rs=.993, root mean square deviation [RMSE]=23.04 ms, and normalized root mean square error [NRMSE]=0.012) between the PPI from FibriCheck and the RRI from the wearable ECG. There was no significant difference (P=.92) between these intervals. Conclusions: Our findings suggest that the most suitable method for the validation of an HR app is a simultaneous measurement of the HR by the smartphone app and an ECG system, compared on the basis of beat-to-beat analysis. This approach could lead to more correct assessments of the accuracy of HR apps. ",
doi="10.2196/mhealth.7254",
url="http://mhealth.jmir.org/2017/8/e129/"
}


@Article{info:doi/10.2196/cardio.7915,
author="Peters, Mattson Robert
and Shivakumar, Nishkala
and Xu, Ran
and Javaherian, Kavon
and Sink, Eric
and Patel, Kunjan
and Brown, Angela
and Huynh, Justin
and Blanchard, Melvin
and Ross, Will
and Byrd, Jonathan",
title="Assessing the Utility of a Novel SMS- and Phone-Based System for Blood Pressure Control in Hypertensive Patients: Feasibility Study",
journal="JMIR Cardio",
year="2017",
month="Jul",
day="27",
volume="1",
number="2",
pages="e2",
keywords="telemedicine",
keywords="hypertension",
keywords="quality improvement",
keywords="text messaging",
keywords="primary care",
keywords="eHealth",
keywords="mHealth",
keywords="disease management",
abstract="Background: Although hypertension (HTN) is a major modifiable risk factor for arterial damage, blood pressure (BP) remains poorly controlled in the hypertensive population. Telemedicine is a promising adjunct intervention that may complement traditional therapies and improve adherence rates; however, current approaches have multiple barriers to entry, including the use of relatively expensive Bluetooth devices or the dependence on smart phone utilization, which tend to exclude low-income and more elderly populations. Objective: The aim of this study was to design and implement a new phone call- and short message service text messaging-based intervention, Epharmix's EpxHypertension, in a quality improvement project that demonstrates the feasibility of this system for BP control in a family medicine setting. Methods: We recruited 174 patients from a community clinic in St Louis from a database of patients diagnosed with HTN. An automated call or text messaging system was used to monitor patient-reported BPs. If determined to be elevated, physicians were notified by an email, text, or electronic medical record alert. Mean systolic BPs (SBPs) and diastolic BPs (DBPs) were compared at the beginning and end of 12 weeks. Results: After 12 weeks on the system, patients with a baseline SBP of 140 mm Hg or higher reduced SBP by 10.8 mm Hg (95\% CI ?14.5 to ?7.2, P<.001) and DBP by 6.6 mm Hg (95\% CI ?9.9 to ?3.4, P=.002), but no significant changes were observed in overall BPs and BPs in the group with baseline SBP less than 140 mm Hg. Conclusions: EpxHypertension provides a viable means to control HTN in patients with high baseline BPs despite previous therapy. This community implementation study demonstrates the feasibility of implementing EpxHypertension across a primary care setting without the need for smartphones or Bluetooth-linked BP cuffs. Future studies should evaluate its effectiveness in a randomized control trial compared with standard of care. ",
doi="10.2196/cardio.7915",
url="http://cardio.jmir.org/2017/2/e2/"
}


@Article{info:doi/10.2196/mhealth.6998,
author="Thompson, David
and Mackay, Teresa
and Matthews, Maria
and Edwards, Judith
and Peters, S. Nicholas
and Connolly, B. Susan",
title="Direct Adherence Measurement Using an Ingestible Sensor Compared With Self-Reporting in High-Risk Cardiovascular Disease Patients Who Knew They Were Being Measured: A Prospective Intervention",
journal="JMIR Mhealth Uhealth",
year="2017",
month="Jun",
day="12",
volume="5",
number="6",
pages="e76",
keywords="cardiac prevention and rehabilitation",
keywords="adherence",
keywords="mHealth",
keywords="remote monitoring",
keywords="cardiovascular diseases",
keywords="primary prevention",
keywords="medication adherence",
keywords="telemedicine",
abstract="Background: Use of appropriate cardioprotective medication is a cornerstone of cardiovascular disease prevention, but less-than-optimal patient adherence is common. Thus, strategies for improving adherence are recommended to adopt a multifaceted approach. Objective: The objective of our study was to test a system comprising a biodegradable, ingestible sensor for direct measurement of medication ingestion in a group of patients at elevated cardiovascular risk attending a cardiac prevention and rehabilitation program. Methods: In this prospective intervention trial in a single group of 21 patients running from April 2014 to June 2015, we measured adherence by self-report and adherence determined objectively by the system. The sensor emits a signal when it encounters the acidic environment of the stomach, detectable by an externally worn patch and linked software app. Longitudinal adherence data in the form of daily progress charts for sensed dosing events as compared with scheduled dosing are visible to patients on their tablet computer's medication dosing app, thus providing patients with continuous medication adherence feedback. We sought feedback on patient acceptability by questionnaire assessment. Participants used the system for the 12-week period of their cardiac prevention and rehabilitation program. Results: Only 1 patient at initial assessment and 1 patient at end-of-program assessment reported often missing medication. The remaining patients reported never missing medication or had missing data. Only 12 (57\%) of patients overall achieved system-determined adherence of 80\% or more, and 3 patients had scores below 40\%. Participants reported high levels of acceptability. Conclusions: This integrated system was well tolerated in a group of 21 patients over an appreciable time frame. Its ability to measure adherence reveals the sizeable disconnect between patient self-reported adherence and actual medication taking and has promising potential for clinical use as a tool to encourage better medication-taking behavior due to its ability to provide continuous patient-level feedback. ",
doi="10.2196/mhealth.6998",
url="http://mhealth.jmir.org/2017/6/e76/",
url="http://www.ncbi.nlm.nih.gov/pubmed/28606895"
}


@Article{info:doi/10.2196/cardio.6057,
author="Darling, Eric Chad
and Dovancescu, Silviu
and Saczynski, S. Jane
and Riistama, Jarno
and Sert Kuniyoshi, Fatima
and Rock, Joseph
and Meyer, E. Theo
and McManus, D. David",
title="Bioimpedance-Based Heart Failure Deterioration Prediction Using a Prototype Fluid Accumulation Vest-Mobile Phone Dyad: An Observational Study",
journal="JMIR Cardio",
year="2017",
month="Mar",
day="13",
volume="1",
number="1",
pages="e1",
keywords="telemedicine",
keywords="outpatient monitoring",
keywords="heart failure",
keywords="electric impedance",
abstract="Background: Recurrent heart failure (HF) events are common in patients discharged after acute decompensated heart failure (ADHF). New patient-centered technologies are needed to aid in detecting HF decompensation. Transthoracic bioimpedance noninvasively measures pulmonary fluid retention. Objective: The objectives of our study were to (1) determine whether transthoracic bioimpedance can be measured daily with a novel, noninvasive, wearable fluid accumulation vest (FAV) and transmitted using a mobile phone and (2) establish whether an automated algorithm analyzing daily thoracic bioimpedance values would predict recurrent HF events. Methods: We prospectively enrolled patients admitted for ADHF. Participants were trained to use a FAV--mobile phone dyad and asked to transmit bioimpedance measurements for 45 consecutive days. We examined the performance of an algorithm analyzing changes in transthoracic bioimpedance as a predictor of HF events (HF readmission, diuretic uptitration) over a 75-day follow-up. Results: We observed 64 HF events (18 HF readmissions and 46 diuretic uptitrations) in the 106 participants (67 years; 63.2\%, 67/106, male; 48.1\%, 51/106, with prior HF) who completed follow-up. History of HF was the only clinical or laboratory factor related to recurrent HF events (P=.04). Among study participants with sufficient FAV data (n=57), an algorithm analyzing thoracic bioimpedance showed 87\% sensitivity (95\% CI 82-92), 70\% specificity (95\% CI 68-72), and 72\% accuracy (95\% CI 70-74) for identifying recurrent HF events. Conclusions: Patients discharged after ADHF can measure and transmit daily transthoracic bioimpedance using a FAV--mobile phone dyad. Algorithms analyzing thoracic bioimpedance may help identify patients at risk for recurrent HF events after hospital discharge. ",
doi="10.2196/cardio.6057",
url="http://cardio.jmir.org/2017/1/e1/"
}


@Article{info:doi/10.2196/mhealth.7275,
author="Yan, P. Bryan
and Chan, KY Christy
and Li, KH Christien
and To, TL Olivia
and Lai, HS William
and Tse, Gary
and Poh, C. Yukkee
and Poh, Ming-Zher",
title="Resting and Postexercise Heart Rate Detection From Fingertip and Facial Photoplethysmography Using a Smartphone Camera: A Validation Study",
journal="JMIR Mhealth Uhealth",
year="2017",
month="Mar",
day="13",
volume="5",
number="3",
pages="e33",
keywords="heart rate",
keywords="mobile apps",
keywords="photoplethysmography",
keywords="smartphone",
keywords="mobile phone",
abstract="Background: Modern smartphones allow measurement of heart rate (HR) by detecting pulsatile photoplethysmographic (PPG) signals with built-in cameras from the fingertips or the face, without physical contact, by extracting subtle beat-to-beat variations of skin color. Objective: The objective of our study was to evaluate the accuracy of HR measurements at rest and after exercise using a smartphone-based PPG detection app. Methods: A total of 40 healthy participants (20 men; mean age 24.7, SD 5.2 years; von Luschan skin color range 14-27) underwent treadmill exercise using the Bruce protocol. We recorded simultaneous PPG signals for each participant by having them (1) facing the front camera and (2) placing their index fingertip over an iPhone's back camera. We analyzed the PPG signals from the Cardiio-Heart Rate Monitor + 7 Minute Workout (Cardiio) smartphone app for HR measurements compared with a continuous 12-lead electrocardiogram (ECG) as the reference. Recordings of 20 seconds' duration each were acquired at rest, and immediately after moderate- (50\%-70\% maximum HR) and vigorous- (70\%-85\% maximum HR) intensity exercise, and repeated successively until return to resting HR. We used Bland-Altman plots to examine agreement between ECG and PPG-estimated HR. The accuracy criterion was root mean square error (RMSE) ?5 beats/min or ?10\%, whichever was greater, according to the American National Standards Institute/Association for the Advancement of Medical Instrumentation EC-13 standard. Results: We analyzed a total of 631 fingertip and 626 facial PPG measurements. Fingertip PPG-estimated HRs were strongly correlated with resting ECG HR (r=.997, RMSE=1.03 beats/min or 1.40\%), postmoderate-intensity exercise (r=.994, RMSE=2.15 beats/min or 2.53\%), and postvigorous-intensity exercise HR (r=.995, RMSE=2.01 beats/min or 1.93\%). The correlation of facial PPG-estimated HR was stronger with resting ECG HR (r=.997, RMSE=1.02 beats/min or 1.44\%) than with postmoderate-intensity exercise (r=.982, RMSE=3.68 beats/min or 4.11\%) or with postvigorous-intensity exercise (r=.980, RMSE=3.84 beats/min or 3.73\%). Bland-Altman plots showed better agreement between ECG and fingertip PPG-estimated HR than between ECG and facial PPG-estimated HR. Conclusions: We found that HR detection by the Cardiio smartphone app was accurate at rest and after moderate- and vigorous-intensity exercise in a healthy young adult sample. Contact-free facial PPG detection is more convenient but is less accurate than finger PPG due to body motion after exercise. ",
doi="10.2196/mhealth.7275",
url="http://mhealth.jmir.org/2017/3/e33/",
url="http://www.ncbi.nlm.nih.gov/pubmed/28288955"
}