Wearable devices can predict the outcome of standardized 6-minute walk tests in heart disease

Schubert, Charlotte; Archer, Gareth; Zelis, Jo M.; Nordmeyer, Sarah; Runte, Kilian; Hennemuth, Anja; Berger, Felix; Falk, Volkmar; Tonino, Pim A.L.; Hose, Rod; Horst, Herman ter; Küehne, Titus; Kelm, Marcus

doi:10.1038/s41746-020-0299-2

Cited by 18 publications

(12 citation statements)

References 46 publications

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“…Nevertheless, dynamic stress testing includes the assessment of a personal maximum or submaximal workload, which can be substantially altered in HF. In conjunction with wearable devices, models based on such changes were recently shown to be capable of predicting the outcome of standardized 6-min walk tests in patients with heart disease ( 45 ). The adaptation of such models, as well as surveillance strategies to disease-specific aspects of HF, may help to better identify patients at risk providing data-driven approaches to patients and caregivers that can help to detect deterioration early on ( 46 ).…”

Section: Discussionmentioning

confidence: 99%

Hemodynamic Changes During Physiological and Pharmacological Stress Testing in Patients With Heart Failure: A Systematic Review and Meta-Analysis

Bingel

Messroghli

Weimar

et al. 2022

Front. Cardiovasc. Med.

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Although disease etiologies differ, heart failure patients with preserved and reduced ejection fraction (HFpEF and HFrEF, respectively) both present with clinical symptoms when under stress and impaired exercise capacity. The extent to which the adaptation of heart rate (HR), stroke volume (SV), and cardiac output (CO) under stress conditions is altered can be quantified by stress testing in conjunction with imaging methods and may help to detect the diminishment in a patient’s condition early. The aim of this meta-analysis was to quantify hemodynamic changes during physiological and pharmacological stress testing in patients with HF. A systematic literature search (PROSPERO 2020:CRD42020161212) in MEDLINE was conducted to assess hemodynamic changes under dynamic and pharmacological stress testing at different stress intensities in HFpEF and HFrEF patients. Pooled mean changes were estimated using a random effects model. Altogether, 140 study arms with 7,248 exercise tests were analyzed. High-intensity dynamic stress testing represented 73% of these data (70 study arms with 5,318 exercise tests), where: HR increased by 45.69 bpm (95% CI 44.51–46.88; I2 = 98.4%), SV by 13.49 ml (95% CI 6.87–20.10; I2 = 68.5%), and CO by 3.41 L/min (95% CI 2.86–3.95; I2 = 86.3%). No significant differences between HFrEF and HFpEF groups were found. Despite the limited availability of comparative studies, these reference values can help to estimate the expected hemodynamic responses in patients with HF. No differences in chronotropic reactions, changes in SV, or CO were found between HFrEF and HFpEF. When compared to healthy individuals, exercise tolerance, as well as associated HR and CO changes under moderate-high dynamic stress, was substantially impaired in both HF groups. This may contribute to a better disease understanding, future study planning, and patient-specific predictive models.Systematic Review Registration[https://www.crd.york.ac.uk/prospero/], identifier [CRD42020161212].

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Section: Discussionmentioning

confidence: 99%

Hemodynamic Changes During Physiological and Pharmacological Stress Testing in Patients With Heart Failure: A Systematic Review and Meta-Analysis

Bingel

Messroghli

Weimar

et al. 2022

Front. Cardiovasc. Med.

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“…Unintentional walk testing should not be viewed as a replacement for clinician-administered walk testing but rather as a complementary approach that allows obtaining intermediate values between walk tests performed at clinics. By combining clinician-administered and unintentional walk testing, also by including information on activity profiles (Schubert et al, 2020), the possibility opens to analyze properties of habitual and purposeful walking. Monitoring of trends in distance walked through unintentional testing might be especially useful when assessing the effectiveness and adherence to the training program at home environment, e.g., prescribed after major cardiovascular events.…”

Section: Discussionmentioning

confidence: 99%

Detection of Walk Tests in Free-Living Activities Using a Wrist-Worn Device

et al. 2021

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Exercise testing to assess the response to physical rehabilitation or lifestyle interventions is administered in clinics thus at best can be repeated only few times a year. This study explores a novel approach to collecting information on functional performance through walk tests, e.g., a 6-min walk test (6MWT), unintentionally performed in free-living activities. Walk tests are detected in step data provided by a wrist-worn device. Only those events of minute-to-minute variation in walking cadence, which is equal or lower than the empirically determined maximal SD (e.g., 5-steps), are considered as walk test candidates. Out of detected walk tests within the non-overlapping sliding time interval (e.g., 1-week), the one with the largest number of steps is chosen as the most representative. This approach is studied on a cohort of 99 subjects, assigned to the groups of patients with cardiovascular disease (CVD) and healthy subjects below and over 40-years-old, who were asked to wear the device while maintaining their usual physical activity regimen. The total wear time was 8,864 subject-days after excluding the intervals of occasionally discontinued monitoring. About 82% (23/28) of patients with CVD and 88% (21/24) of healthy subjects over 40-years-old had at least a single 6MWT over the 1st month of monitoring. About 52% of patients with CVD (12/23) and 91% (19/21) of healthy subjects over 40-years-old exceeded 500 m. Patients with CVD, on average, walked 46 m shorter 6MWT distance (p = 0.04) compared to healthy subjects. Unintentional walk testing is feasible and could be valuable for repeated assessment of functional performance outside the clinical setting.

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“…Our proposed algorithm does not require any information about the subject's height, weight/age and does not need any calibration to calculate the total distance walked. In contrast, current commercial and custom algorithms rely on the availability of such information as a part of a calibration process [23][24][25][26][27][28][29][30][31][32][33][34][35]. Therefore, we believe this is a significant improvement.…”

Section: Studymentioning

confidence: 99%

“…Various studies have used wearable sensors placed at different body parts to estimate the total distance walked during a walking test [23][24][25][26][27][28][29][30][31][32][33][34][35]. However, all of the commercial/custom algorithms used in these studies either require a priori information (age, height, weight) or calibration data to calculate the total distance walked.…”

Section: Introductionmentioning

confidence: 99%

Inertial Sensor Algorithm to Estimate Walk Distance

Shah

Curtze

Sowalsky³

et al. 2022

Sensors

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The “total distance walked” obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of gait while streamlining walk test administration. The aim of this study was to develop an inertial sensor-based algorithm to estimate the total distance walked using older subjects with impaired fasting glucose (Study I), and to test the generalizability of the proposed algorithm in patients with Multiple Sclerosis (Study II). All subjects wore two inertial sensors (Opals by Clario-APDM Wearable Technologies) on their feet. The walking distance algorithm was developed based on 108 older adults in Study I performing a 400 m walk test along a 20 m straight walkway. The validity of the algorithm was tested using a 6-minute walk test (6MWT) in two sub-studies of Study II with different lengths of a walkway, 15 m (Study II-A, n = 24) and 20 m (Study II-B, n = 22), respectively. The start and turn around points were marked with lines on the floor while smaller horizontal lines placed every 1 m served to calculate the manual distance walked (ground truth). The proposed algorithm calculates the forward distance traveled during each step as the change in the horizontal position from each foot-flat period to the subsequent foot-flat period. The total distance walked is then computed as the sum of walk distances for each stride, including turns. The proposed algorithm achieved an average absolute error rate of 1.92% with respect to a fixed 400 m distance for Study I. The same algorithm achieved an absolute error rate of 4.17% and 3.21% with respect to an averaged manual distance for 6MWT in Study II-A and Study II-B, respectively. These results demonstrate the potential of an inertial sensor-based algorithm to estimate a total distance walked with good accuracy with respect to the manual, clinical standard. Further work is needed to test the generalizability of the proposed algorithm with different administrators and populations, as well as larger diverse cohorts.

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Wearable devices can predict the outcome of standardized 6-minute walk tests in heart disease

Cited by 18 publications

References 46 publications

Hemodynamic Changes During Physiological and Pharmacological Stress Testing in Patients With Heart Failure: A Systematic Review and Meta-Analysis

Hemodynamic Changes During Physiological and Pharmacological Stress Testing in Patients With Heart Failure: A Systematic Review and Meta-Analysis

Detection of Walk Tests in Free-Living Activities Using a Wrist-Worn Device

Inertial Sensor Algorithm to Estimate Walk Distance

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