METHODS: A pragmatic randomised controlled trial was conducted on 29 healthy sedentary adults (seven males and 22 females) in a 12-week exercise program. They were randomly assigned to group A (75 min/week, N.=15) or group B (150 min/week, N.=14) of moderate intensity aerobic exercise groups. HRR at 1-minute (HRR1), HRR at 2-minute (HRR2), and peak oxygen uptake (VO2peak) were measured pre- and post-intervention.
RESULTS: The improvements of HRR1 and HRR2 were seen in both groups but was only significant (P<0.05) for group A with HRR1, -4.07 bpm (post 24.47±6.42 - pre 20.40±5.51, P=0.018) and HHR2, -3.93 bpm (post 43.40±13.61 - pre 39.47±10.68, P=0.046). Group B showed increment of HRR1, -1.14 bpm (post 21.14±5.35 - pre 20.00±6.30, P=0.286) and HRR2, -2.5 bpm, (post 39.36±8.01 - pre 36.86±9.57, P=0.221). Improvement of the VO2peak was only significant in group B with an increment of 1.52±2.61 (P=0.049).
CONCLUSIONS: In conclusion, our study suggests that improvements in heart rate recovery (HRR1 and HRR2) among sedentary healthy adults can be achieved by engaging in moderate intensity exercise at a dose lower than the current recommended guidelines. The lower dose seems to be more attainable and may encourage exercise compliance. Future studies should further explore the effects of different exercise volumes on HRR in a larger sample size and also by controlling for BMI or gender.
METHODS: This article provides a comprehensive review of automated sleep stage scoring systems, which were created since the year 2000. The systems were developed for Electrocardiogram (ECG), Electroencephalogram (EEG), Electrooculogram (EOG), and a combination of signals.
RESULTS: Our review shows that all of these signals contain information for sleep stage scoring.
CONCLUSIONS: The result is important, because it allows us to shift our research focus away from information extraction methods to systemic improvements, such as patient comfort, redundancy, safety and cost.
Objective: This study aimed to perform a systematic review to describe the achievements made by the researchers, summarizing findings that have been found by previous researchers in feature extraction and CTG classification, to determine criteria and evaluation methods to the taxonomies of the proposed literature in the CTG field and to distinguish aspects from relevant research in the field of CTG.
Methods: Article search was done systematically using three databases: IEEE Xplore digital library, Science Direct, and Web of Science over a period of 5 years. The literature in the medical sciences and engineering was included in the search selection to provide a broader understanding for researchers.
Results: After screening 372 articles, and based on our protocol of exclusion and inclusion criteria, for the final set of articles, 50 articles were obtained. The research literature taxonomy was divided into four stages. The first stage discussed the proposed method which presented steps and algorithms in the pre-processing stage, feature extraction and classification as well as their use in CTG (20/50 papers). The second stage included the development of a system specifically on automatic feature extraction and CTG classification (7/50 papers). The third stage consisted of reviews and survey articles on automatic feature extraction and CTG classification (3/50 papers). The last stage discussed evaluation and comparative studies to determine the best method for extracting and classifying features with comparisons based on a set of criteria (20/50 articles).
Discussion: This study focused more on literature compared to techniques or methods. Also, this study conducts research and identification of various types of datasets used in surveys from publicly available, private, and commercial datasets. To analyze the results, researchers evaluated independent datasets using different techniques.
Conclusions: This systematic review contributes to understand and have insight into the relevant research in the field of CTG by surveying and classifying pertinent research efforts. This review will help to address the current research opportunities, problems and challenges, motivations, recommendations related to feature extraction and CTG classification, as well as the measurement of various performance and various data sets used by other researchers.
OBJECTIVE: The purpose of this study was to sense atrial contractions from the Micra ACC signal and provide AV synchronous pacing.
METHODS: The Micra Accelerometer Sensor Sub-Study (MASS) and MASS2 early feasibility studies showed intracardiac accelerations related to atrial contraction can be measured via ACC in the Micra leadless pacemaker. The Micra Atrial TRacking Using A Ventricular AccELerometer (MARVEL) study was a prospective multicenter study designed to characterize the closed-loop performance of an AV synchronous algorithm downloaded into previously implanted Micra devices. Atrioventricular synchrony (AVS) was measured during 30 minutes of rest and during VVI pacing. AVS was defined as a P wave visible on surface ECG followed by a ventricular event <300 ms.
RESULTS: A total of 64 patients completed the MARVEL study procedure at 12 centers in 9 countries. Patients were implanted with a Micra for a median of 6.0 months (range 0-41.4). High-degree AV block was present in 33 patients, whereas 31 had predominantly intrinsic conduction during the study. Average AVS during AV algorithm pacing was 87.0% (95% confidence interval 81.8%-90.9%), 80.0% in high-degree block patients and 94.4% in patients with intrinsic conduction. AVS was significantly greater (P