Exercise Testing in Wolff-Parkinson-White Syndrome

Review paper on WPW and athletes: Let sleeping dogs lie?

Accessory pathways are present in 1 in 300 young individuals. They are often asymptomatic and potentially lethal arrhythmias may be the first presentation. During long-term follow-up, up to 20% of asymptomatic individuals with pre-excitation go on to develop an arrhythmia and the absence of traditional clinical and electrophysiological high-risk markers does not guarantee the "safe" nature of an accessory pathway. The widespread availability of permanent cure for the condition at low risk by catheter ablation, creates an incentive to screen for accessory pathways with a 12-lead ECG, particularly in individuals who are perceived to be at increased risk, such as athletes and high-risk professions. We review the existing literature on the assessment and management of accessory pathways (Wolff-Parkinson-White [WPW] syndrome) and discuss its implications for the young athletic population.

Development of QRS detection algorithm designed for wearable cardiorespiratory system

An in-home sleep monitoring system was developed previously in our laboratory for monitoring electrocardiography (ECG) and respiratory signals. However, the ECG signal acquired with this system is prone to high-grade noise caused by motion artifact. Since the detection of the QRS complexes with high accuracy is very important in a computer-based analysis of the ECG, a high accuracy QRS detection algorithm is developed and based on the combination of heart rate indicators and morphological ECG features. The proposed algorithm is tested both on 16 h data acquired using the two sensors of our cardiorespiratory belt system, i.e., the polyvinylidene fluoride (PVDF) film and the conductive fabric sheets, and on all 48 records of the MIT/BIH Arrhythmia Database. Satisfying results are obtained for both databases, the sensitivity S(e) and positive predictivity P(+) were calculated for each case and results show S(e)=[96.98%, 93.76%] and P(+)=[97.81%, 99.48%] for conductive fabric and PVDF film sensors, respectively, and S(e)=99.77% and P(+)=99.64% in the case of the MIT/BIH Arrhythmia Database. Further, heart rate variability (HRV) measures were calculated using our system and a commercial system. A comparison between systems' results is done to show the usefulness of our developed algorithm used with our cardiorespiratory belt sensor.