Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database

Effects of slow and regular breathing exercise on cardiopulmonary coupling and blood pressure

“…Then, each heartbeat was detected by using an automated QRS complex detection algorithm [11], and the detection result was verified by visual inspection. Consequently, the peak of each R wave was located and RR interval (RRI) time series from each subject was derived.…”

Assessing Effect of Beat Detector on Detection Dependent Signal Quality Indices

“…We selected a set of beat detector algorithms with open source implementation to detect beats in the ECG epochs we annotated. This set consisted of the Zong [7], Afonso [8], Pan [9], Hamilton [10], and Johannesen [11] beat detectors. Selected SQIs were calculated using beats detected by each of these detectors and reference beat annotations.…”

Pervasive computing at scale: Transforming the state of the art

“…Between 1990 and 2010 the number of mobile phone subscriptions grew by two orders of magnitude and in many parts of the world the current ratio is as high as 10 mobile phone users to one PC user [22]. In moving ahead to what smart phones will look like in the next decade, one can imagine a device that continuously tracks our lives, including location traces, readings from internal and external sensors, and logs of our mobile-based activities.…”

“…Smart health testbeds need to be designed and made available to the community along with smart health datasets. The MIT arrhythmia dataset [22], the PhysioNet physiologic signal dataset [21], and the CASAS dementia assessment dataset [43] are first steps in a direction we hope many other research groups will follow.…”

“…The definition of privacy will continue to evolve as pervasive computing systems scale. Usually people use multiple sources of knowledge including physical, social, and experiential information, to determine the utility and the safety of technologies [22].…”