Search

Background: Heart rate recovery (HRR) is a marker of vagal tone that is a powerful predictor of mortality in patients with coronary artery disease., Design: This study aims at evaluating the effects of long-term exercise training on HRR after acute myocardial infarction (AMI), in order to clarify whether prolonged exercise training could maintain a long-term improvement of HRR., Methods: Forty-four patients after AMI were enrolled in a 3-month hospital-based exercise training programme. At the end, patients were subdivided into two groups: group A (n=22), patients discharged with a specific home-based exercise training programme and instructions for improving leisure-time physical activity; group B (n=22), patients discharged with generic instructions to maintain physical activity. All patients underwent a cardiopulmonary exercise test before, at the end of 3 months exercise training and at 6 months follow-up., Results: At the end of the hospital-based exercise training programme we observed an increase in peak oxygen consumption [VO2peak; from 13.9+/-3.6 to 18+/-2.7 ml/kg per min (A) and from 14.1+/-3.9 to 17.9+/-2.1 ml/kg per min (B), P<0.001] and in HRR [from 17.1+/-1.8 to 23.4+/-1.4 beats/min (A), and from 18.8+/-2.1 to 24.3+/-1.9 beats/min (B), P<0.001]. At 6 months' follow-up we observed a further improvement in VO2peak (from 18.0+/-2.7 to 20.3+/-2.7 ml/kg per min, P<0.001) and in HRR (from 23.4+/-1.4 to 27.8+/-2.1 beats/min, P<0.001) in group A, but a significant decrease in VO2peak and in HRR in group B (P<0.001)., Conclusion: Long-term exercise training is useful for maintaining or improving the beneficial results of the standard 3-month exercise training programme on cardiovascular capacity and HRR. This observation may bear beneficial prognostic effects on patients after AMI.

Maximum aerobic power (VO2peak) as an indicator of body fitness is today a very well-known concept not just for athletes but also for the layman. Unfortunately, the accurate measurement of that variable has remained a complex and exhaustive laboratory procedure, which makes it inaccessible to many active people. In this paper we propose a quick estimate of it, mainly based on the heart rate off-kinetics immediately after an all-out 60-m sprint run. The design of this test took into account the recent availability of wrist wearable, heart band free, multi-sensor smart devices, which could also inertially detect the different phases of the sprint and check the distance run. 25 subjects undertook the 60-m test outdoor and a VO2peak test on the laboratory treadmill. Running average speed, HR excursion during the sprint and the time constant (τ) of HR exponential decay in the off-kinetics were fed into a multiple regression, with measured VO2peak as the dependent variable. Statistics revealed that within the investigated range (25-55 ml O2/(kg min)), despite a tendency to overestimate low values and underestimate high values, the three predictors confidently estimate individual VO2peak (R2 = 0.65, p < 0.001). The same analysis has been performed on a 5-s averaged time course of the same measured HR off-kinetics, as these are the most time resolved data for HR provided by many modern smart watches. Results indicate that despite of the substantial reduction in sample size, predicted VO2peak still explain 59% of the variability of the measured VO2peak. [ABSTRACT FROM AUTHOR]

We describe a wearable sensor developed for cardiac rehabilitation (CR) exercise. To effectively guide CR exercise, the dedicated CR wearable sensor (DCRW) automatically recommends the exercise intensity to the patient by comparing heart rate (HR) measured in real time with a predefined target heart rate zone (THZ) during exercise. The CR exercise includes three periods: pre-exercise, exercise with intensity guidance, and post-exercise. In the pre-exercise period, information such as THZ, exercise type, exercise stage order, and duration of each stage are set up through a smartphone application we developed for iPhones and Android devices. The set-up information is transmitted to the DCRW via Bluetooth communication. In the period of exercise with intensity guidance, the DCRW continuously estimates HR using a reflected pulse signal in the wrist. To achieve accurate HR measurements, we used multichannel photo sensors and increased the chances of acquiring a clean signal. Subsequently, we used singular value decomposition (SVD) for de-noising. For the median and variance of RMSEs in the measured HRs, our proposed method with DCRW provided lower values than those from a single channel-based method and template-based multiple-channel method for the entire exercise stage. In the post-exercise period, the DCRW transmits all the measured HR data to the smartphone application via Bluetooth communication, and the patient can monitor his/her own exercise history. [ABSTRACT FROM AUTHOR]

Copyright of Applied Physiology, Nutrition & Metabolism is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)